The Software Analysis Workbench (SAW) is a tool for constructing mathematical models of the computational behavior of software, transforming these models, and proving properties about them.

SAW can currently construct models of a subset of programs written in Cryptol, LLVM (and therefore C), and JVM (and therefore Java). The models take the form of typed functional programs, so in a sense SAW can be considered a translator from imperative programs to their functional equivalents. Various external proof tools, including a variety of SAT and SMT solvers, can be used to prove properties about SAW functional models. Models can be constructed from arbitrary Cryptol programs, and can typically be constructed from C and Java programs that have fixed-size inputs and outputs and that terminate after a fixed number of iterations of any loop (or a fixed number of recursive calls). One common use case is to verify that an algorithm specification in Cryptol is equivalent to an algorithm implementation in C or Java.

The process of extracting models from programs, manipulating them, forming queries about them, and sending them to external provers is orchestrated using a special purpose language called SAWScript. SAWScript is a typed functional language with support for sequencing of imperative commmands.

The rest of this document first describes how to use the SAW tool, saw, and outlines the structure of the SAWScript language and its relationship to Cryptol. It then presents the SAWScript commands that transform functional models and prove properties about them. Finally, it describes the specific commands available for constructing models from imperative programs in a variety of languages.

Invoking SAW

The primary mechanism for interacting with SAW is through the saw executable included as part of the standard binary distribution. With no arguments, saw starts a read-evaluate-print loop (REPL) that allows the user to interactively evaluate commands in the SAWScript language. With one file name argument, it executes the specified file as a SAWScript program.

In addition to a file name, the saw executable accepts several command-line options:

-h, -?, --help

Print a help message.

-V, --version

Show the version of the SAWScript interpreter.

-c path, --classpath=path

Specify a colon-delimited list of paths to search for Java classes.

-i path, --import-path=path

Specify a colon-delimited list of paths to search for imports.

-t, --extra-type-checking

Perform extra type checking of intermediate values.

-I, --interactive

Run interactively (with a REPL).

-j path, --jars=path

Specify a colon-delimited list of paths to .jar files to search for Java classes.

-d num, --sim-verbose=num

Set the verbosity level of the Java and LLVM simulators.

-v num, --verbose=num

Set the verbosity level of the SAWScript interpreter.

SAW also uses several environment variables for configuration:


Specify a colon-delimited list of directory paths to search for Cryptol imports (including the Cryptol prelude).


Specify a colon-delimited list of directory paths to search for imports.


Specify the path of the .jar file containing the core Java libraries.

On Windows, semicolon-delimited lists are used instead of colon-delimited lists.

Structure of SAWScript

A SAWScript program consists, at the top level, of a sequence of commands to be executed in order. Each command is terminated with a semicolon. For example, the print command displays a textual representation of its argument. Suppose the following text is stored in the file print.saw:

print 3;

The command saw print.saw will then yield output similar to the following:

Loading module Cryptol
Loading file "print.saw"

The same code can be run from the interactive REPL:

sawscript> print 3;

At the REPL, terminating semicolons can be omitted:

sawscript> print 3

To make common use cases simpler, bare values at the REPL are treated as if they were arguments to print:

sawscript> 3

One SAWScript file can be included in another using the include command, which takes the name of the file to be included as an argument. For example:

include "print.saw";

Basic Types and Values

All values in SAWScript have types, and these types are determined and checked before a program runs (that is, SAWScript is statically typed). The basic types available are similar to those in many other languages.

  • The Int type represents unbounded mathematical integers. Integer constants can be written in decimal notation (e.g., 42), hexadecimal notation (0x2a), and binary (0b00101010). However, unlike many languages, integers in SAWScript are used primarily as constants. Arithmetic is usually encoded in Cryptol, as discussed in the next section.

  • The Boolean type, Bool, contains the values true and false, like in many other languages. As with integers, computations on Boolean values usually occur in Cryptol.

  • Values of any type can be aggregated into tuples. For example, the value (true, 10) has the type (Bool, Int).

  • Values of any type can also be aggregated into records, which are exactly like tuples except that their components have names. For example, the value { b = true, n = 10 } has the type { b : Bool, n : Int }.

  • A sequence of values of the same type can be stored in a list. For example, the value [true, false, true] has the type [Bool].

  • Strings of textual characters can be represented in the String type. For example, the value "example" has type String.

  • The “unit” type, written (), is essentially a placeholder. It has only one value, also written (). Values of type () convey no information. We will show in later sections several cases where this is useful.

SAWScript also includes some more specialized types that do not have straightforward counterparts in most other languages. These will appear in later sections.

Basic Expression Forms

One of the key forms of top-level command in SAWScript is a binding, introduced with the let keyword, which gives a name to a value. For example:

sawscript> let x = 5
sawscript> x

Bindings can have parameters, in which case they define functions. For instance, the following function takes one parameter and constructs a list containing that parameter as its single element.

sawscript> let f x = [x]
sawscript> f "text"

Functions themselves are values and have types. The type of a function that takes an argument of type a and returns a result of type b is a -> b.

Function types are typically inferred, as in the example f above. In this case, because f only creates a list with the given argument, and because it is possible to create a list of any element type, f can be applied to an argument of any type. We say, therefore, that f is polymorphic. Concretely, we write the type of f as {a} a -> [a], meaning it takes a value of any type (denoted a) and returns a list containing elements of that same type. This means we can also apply f to 10:

sawscript> f 10

However, we may want to specify that a function has a more specific type. In this case, we could restrict f to operate only on Int parameters.

sawscript> let f (x : Int) = [x]

This will work identically to the original f on an Int parameter:

sawscript> f 10

However, it will fail for a String parameter:

sawscript> f "text"

type mismatch: String -> t.0 and Int -> [Int]
 at "_" (REPL)
mismatched type constructors: String and Int

Type annotations can be applied to any expression. The notation (e : t) indicates that expression e is expected to have type t and that it is an error for e to have a different type. Most types in SAWScript are inferred automatically, but specifying them explicitly can sometimes enhance readability.

Because functions are values, functions can return other functions. We make use of this feature when writing functions of multiple arguments. Consider the function g, similar to f but with two arguments:

sawscript> let g x y = [x, y]

Like f, g is polymorphic. Its type is {a} a -> a -> [a]. This means it takes an argument of type a and returns a function that takes an argument of the same type a and returns a list of a values. We can therefore apply g to any two arguments of the same type:

sawscript> g 2 3
sawscript> g true false

But type checking will fail if we apply it to two values of different types:

sawscript> g 2 false

type mismatch: Bool -> t.0 and Int -> [Int]
 at "_" (REPL)
mismatched type constructors: Bool and Int

So far we have used two related terms, function and command, and we take these to mean slightly different things. A function is any value with a function type (e.g., Int -> [Int]). A command is a function where the result type is one of a specific set of special types. These special types are parameterized (like the list type), and allow us to restrict command usage to specific contexts.

The most important command type is the TopLevel type, indicating a command that can run at the top level (directly at the REPL, or as one of the top level commands in a script file). The print command has the type {a} a -> TopLevel (), where TopLevel () means that it is a command that runs in the TopLevel context and returns a value of type () (that is, no useful information). In other words, it has a side effect (printing some text to the screen) but doesn’t produce any information to use in the rest of the SAWScript program. This is the primary usage of the () type.

It can sometimes be useful to bind a sequence of commands together in a unit. This can be accomplished with the do { ... } construct. For example:

sawscript> let print_two = do { print "first"; print "second"; }
sawscript> print_two

The bound value, print_two, has type TopLevel (), since that is the type of its last command.

Note that in the previous example the printing doesn’t occur until print_two directly appears at the REPL. The let expression does not cause those commands to run. The construct that runs a command is written using the <- operator. This operator works like let except that it says to run the command listed on the right hand side and bind the result, rather than binding the variable to the command itself. Using <- instead of let in the previous example yields:

sawscript> print_two <- do { print "first"; print "second"; }
sawscript> print_two

Here, the print commands run first, and then print_two gets the value returned by the second print command, namely (). Any command listed alone at the REPL, the top level in a script, or inside a do block is treated as implicitly having a <- that binds its result to an unnamed variable (that is, discards it).

In some cases it can be useful to have more control over the value returned by a do block. The return command allows us to do this. For example, say we wanted to write a function that would print a message before and after running some arbitrary command and then return the result of that command. We could write:

let run_with_message c =
  do {
    print "Starting.";
    res <- c;
    print "Done.";
    return res;

x <- run_with_message (return 3);
print x;

If we put this script in run.saw and run it with saw, we get something like:

Loading module Cryptol
Loading file "run.saw"

Note that it ran the first print command, then the caller-specified command, then the second print command. The result stored in x at the end is the result of the return command passed in as an argument.

Other Basic Functions

Aside from the functions we have listed so far, there are a number of other operations for working with basic data structures and interacting with the operating system.

The following functions work on lists:

concat : {a} [a] -> [a] -> [a]

head : {a} [a] -> a

tail : {a} [a] -> [a]

length : {a} [a] -> Int

null : {a} [a] -> Bool

nth : {a} [a] -> Int -> a

for : {m, a, b} [a] -> (a -> m b) -> m [b]

The concat function takes two lists and returns the concatenation of the two. The head function returns the first element of a list, and the tail function returns everything except the first element. The length function counts the number of elements in a list, and the null function indicates whether a list is empty (has zero elements). The nth function returns the element at the given position, with nth l 0 being equivalent to head l. The for command takes a list and a function that runs in some command context. The passed command will be called once for every element of the list, in order, and for will ultimately return a list of all of the results produced by the command.

For interacting with the operating system, we have:

get_opt : Int -> String

exec : String -> [String] -> String -> TopLevel String

exit : Int -> TopLevel ()

The get_opt function returns the command-line argument to saw at the given index. Argument 0 is always the name of the saw executable itself, and higher indices represent later arguments. The exec command runs an external program given, respectively, an executable name, a list of arguments, and a string to send to the standard input of the program. The exec command returns the standard output from the program it executes and prints standard error to the screen. Finally, the exit command stops execution of the current script and returns the given exit code to the operating system.

Finally, there are a few miscellaneous functions and commands. The show function computes the textual representation of its argument in the same way as print, but instead of displaying the value it returns it as a String value for later use in the program. This can be useful for constructing more detailed messages later. The str_concat function, which concatenates two String values, can also be useful in this case.

The time command runs any other TopLevel command and prints out the time it took to execute. If you want to use the time value later in the program, the with_time function returns both the original result of the timed command and the time taken to execute it (in milliseconds), without printing anything in the process.

show : {a} a -> String

str_concat : String -> String -> String

time : {a} TopLevel a -> TopLevel a

with_time : {a} TopLevel a -> TopLevel (Int, a)

The Term Type

Perhaps the most important type in SAWScript, and the one most unlike the built-in types of most other languages, is the Term type. Essentially, a value of type Term precisely describes all possible computations performed by some program. In particular, if two Term values are equivalent, then the programs that they represent will always compute the same results given the same inputs. We will say more later about exactly what it means for two terms to be equivalent, and how to determine whether two terms are equivalent.

Before exploring the Term type more deeply, it is important to understand the role of the Cryptol language in SAW.

Cryptol and its Role in SAW

Cyptol is a domain-specific language originally designed for the high-level specification of cryptographic algorithms. It is general enough, however, to describe a wide variety of programs, and is particularly applicable to describing computations that operate on streams of data of some fixed size.

In addition to being integrated into SAW, Cryptol is a standalone language with its own manual:


SAW includes deep support for Cryptol, and in fact requires the use of Cryptol for most non-trivial tasks. To fully understand the rest of this manual and to effectively use SAW, you will need to develop at least a rudimentary understanding of Cryptol.

The primary use of Cryptol within SAWScript is to construct values of type Term. Although Term values can be constructed from various sources, inline Cryptol expressions are the most direct and convenient way to create them.

Specifically, a Cryptol expression can be placed inside double curly braces ({{ and }}), resulting in a value of type Term. As a very simple example, there is no built-in integer addition operation in SAWScript. However, we can use Cryptol’s built-in integer addition operator within SAWScript as follows:

sawscript> let t = {{ 0x22 + 0x33 }}
sawscript> print t

Although it printed out in the same way as an Int, it is important to note that t actually has type Term. We can see how this term is represented internally, before being evaluated, with the print_term function.

sawscript> print_term t
  (Prelude.Vec 8 Prelude.Bool)
     (Cryptol.TCNum 8)
  (Prelude.bvNat 8 34)
  (Prelude.bvNat 8 51)

For the moment, it’s not important to understand what this output means. We show it only to clarify that Term values have their own internal structure that goes beyond what exists in SAWScript. The internal representation of Term values is in a language called SAWCore. The full semantics of SAWCore are beyond the scope of this manual.

The text constructed by print_term can also be accessed programmatically (instead of printing to the screen) using the show_term function, which returns a String. The show_term function is not a command, so it executes directly and does not need <- to bind its result. Therefore, the following will have the same result as the print_term command above:

sawscript> let s = show_term t
sawscript> print s

Numbers are printed in decimal notation by default when printing terms, but the following two commands can change that behavior.

set_ascii : Bool -> TopLevel ()

set_base : Int -> TopLevel ()

The set_ascii command, when passed true, makes subsequent print_term or show_term commands print sequences of bytes as ASCII strings (and doesn’t affect printing of anything else). The set_base command, which supports any base from 2 through 36 (inclusive), prints all bit vectors in the given base.

A Term that represents an integer (any bit vector, as affected by set_base) can be translated into a SAWScript Int using the eval_int : Term -> Int function. This function returns an Int if the Term can be represented as one, and fails at runtime otherwise.

sawscript> print (eval_int t)
sawscript> print (eval_int {{ True }})

"eval_int" (<stdin>:1:1):
eval_int: argument is not a finite bitvector
sawscript> print (eval_int {{ [True] }})

Similarly, values of type Bit in Cryptol can be translated into values of type Bool in SAWScript using the eval_bool : Term -> Bool function:

sawscript> let b = {{ True }}
sawscript> print_term b
sawscript> print (eval_bool b)

In addition to being able to extract integer and Boolean values from Cryptol expressions, Term values can be injected into Cryptol expressions. When SAWScript evaluates a Cryptol expression between {{ and }} delimiters, it does so with several extra bindings in scope:

  • Any value in scope of SAWScript type Bool is visible in Cryptol expressions as a value of type Bit.

  • Any value in scope of SAWScript type Int is visible in Cryptol expressions as a type variable. Type variables can be demoted to numeric bit vector values using the backtick (`) operator.

  • Any value in scope of SAWScript type Term is visible in Cryptol expressions as a value with the Cryptol type corresponding to the internal type of the term. The power of this conversion is that the Term does not need to have originally been derived from a Cryptol expression.

In addition to these rules, bindings created at the Cryptol level, either from included files or inside Cryptol quoting brackets, are visible only to later Cryptol expressions, and not as SAWScript variables.

To make these rules more concrete, consider the following examples. If we bind a SAWScript Int, we can use it as a Cryptol type variable. If we create a Term variable that internally has function type, we can apply it to an argument within a Cryptol expression, but not at the SAWScript level:

sawscript> let n = 8
sawscript> let {{ f (x : [n]) = x + 1 }}
sawscript> print {{ f 2 }}
sawscript> print (f 2)

unbound variable: "f" (<stdin>:1:8)

If f was a binding of a SAWScript variable to a Term of function type, we would get a different error:

sawscript> let f = {{ \(x : [n]) -> x + 1 }}
sawscript> print {{ f 2 }}
sawscript> print (f 2)

type mismatch: Int -> t.0 and Term
 at "_" (REPL)
 mismatched type constructors: (->) and Term

One subtlety of dealing with Terms constructed from Cryptol is that because the Cryptol expressions themselves are type checked by the Cryptol type checker, and because they may make use of other Term values already in scope, they are not type checked until the Cryptol brackets are evaluated. So type errors at the Cryptol level may occur at runtime from the SAWScript perspective (though they occur before the Cryptol expressions are run).

So far, we have talked about using Cryptol value expressions. However, SAWScript can also work with Cryptol types. The most direct way to refer to a Cryptol type is to use type brackets: {| and |}. Any Cryptol type written between these brackets becomes a Type value in SAWScript. Some types in Cryptol are size types, and isomorphic to integers. These can be translated into SAWScript integers with the eval_size function. For example:

sawscript> let {{ type n = 16 }}
sawscript> eval_size {| n |}
sawscript> eval_size {| 16 |}

For non-size types, eval_size fails at runtime:

sawscript> eval_size {| [16] |}

"eval_size" (<stdin>:1:1):
eval_size: not a numeric type

In addition to the use of brackets to write Cryptol expressions inline, several built-in functions can extract Term values from Cryptol files in other ways. The import command at the top level imports all top-level definitions from a Cryptol file and places them in scope within later bracketed expressions.

The cryptol_load command behaves similarly, but returns a CryptolModule instead. If any CryptolModule is in scope, its contents are available qualified with the name of the CryptolModule variable. To see how this works, consider the cryptol_prims function, of type () -> CryptolModule. This function returns a built-in module containing a collection of useful Cryptol definitions that are not available in the standard Cryptol Prelude.

The definitions in this module include (in Cryptol syntax):

trunc : {m, n} (fin m, fin n) => [m + n] -> [n]

uext : {m, n} (fin m, fin n) => [n] -> [m + n]

sgt : {n} (fin n) => [n] -> [n] -> Bit

sge : {n} (fin n) => [n] -> [n] -> Bit

slt : {n} (fin n) => [n] -> [n] -> Bit

sle : {n} (fin n) => [n] -> [n] -> Bit

These perform bit-vector operations of truncation (trunc), unsigned extension (uext), and signed comparison (sgt, sge, slt, and sle). These definitions are typically accessed through binding cryptol_prims to a local variable:

sawscript> set_base 16
sawscript> let m = cryptol_prims ()
sawscript> let x = {{ (m::trunc 0x23) : [4] }}
sawscript> print x

The 8-bit value 0x23 was truncated to a 4-bit value 0x3.

Finally, a specific definition can be extracted from a CryptolModule more explicitly using the cryptol_extract command:

cryptol_extract : CryptolModule -> String -> TopLevel Term

Transforming Term Values

The three primary functions of SAW are extracting models (Term values) from programs, transforming those models, and proving properties about models using external provers. So far we’ve shown how to construct Term values from Cryptol programs; later sections will describe how to extract them from other programs. Now we show how to use the various term transformation features available in SAW.


Rewriting a Term consists of applying one or more rewrite rules to it, resulting in a new Term. A rewrite rule in SAW can be specified in multiple ways:

  • as the definition of a function that can be unfolded,
  • as a term of Boolean type (or a function returning a Boolean) that is an equality statement, and
  • as a term of equality type with a body that encodes a proof that the equality in the type is valid.

Each of these forms is a Term of a different shape. In each case the term logically consists of two parts, each of which may contain variables (bound by enclosing lambda expressions). By thinking of the variables as holes that may match any sub-term, the two parts of each term can both be seen as patterns. The left-hand pattern describes a term to match (which may be a sub-term of the full term being rewritten), and the right-hand pattern describes a term to replace it with. Any variable in the right-hand pattern must also appear in the left-hand pattern and will be instantiated with whatever sub-term matched that variable in the original term.

For example, say we have the following Cryptol function:

 \(x:[8]) -> (x * 2) + 1

We might for some reason want to replace multiplication by a power of two with a shift. We can describe this replacement using an equality statement in Cryptol:

\(y:[8]) -> (y * 2) == (y << 1)

Interpreting this as a rewrite rule, it says that for any 8-bit vector (call it y for now), we can replace y * 2 with y << 1. Applying this rule to the earlier expression would then yield:

 \(x:[8]) -> (x << 1) + 1

The general philosophy of rewriting is that the left and right patterns, while syntactically different, should be semantically equivalent. Therefore, applying a set of rewrite rules should not change the fundamental meaning of the term being rewritten. SAW is particularly focused on the task of proving that some logical statement expressed as a Term is always true. If that is in fact the case, then the entire term can be replaced by the term True without changing its meaning. The rewriting process can in some cases, by repeatedly applying rules that themselves are known to be valid, reduce a complex term entirely to True, which constitutes a proof of the original statement. In other cases, rewriting can simplify terms before sending them to external automated provers that can then finish the job. Sometimes this simplification can help the automated provers run more quickly, and sometimes it can help them prove things they would otherwise be unable to prove by applying reasoning steps (rewrite rules) that are not available to the automated provers.

In practical use, rewrite rules can be aggregated into Simpset values in SAWScript. A few pre-defined Simpset values exist:

empty_ss : Simpset
basic_ss : Simpset
cryptol_ss : () -> Simpset

The first is the empty set of rules. Rewriting with it should have no effect, but it is useful as an argument to some of the functions that construct larger Simpset values. The basic_ss constant is a collection of rules that are useful in most proof scripts. The cryptol_ss value includes a collection of Cryptol-specific rules. Some of these simplify away the abstractions introduced in the translation from Cryptol to SAWCore, which can be useful when proving equivalence between Cryptol and non-Cryptol code. Leaving these abstractions in place is appropriate when comparing only Cryptol code, however, so cryptol_ss is not included in basic_ss.

The next set of functions add either a single rule or a list of rules to an existing Simpset.

addsimp' : Term -> Simpset -> Simpset

addsimps' : [Term] -> Simpset -> Simpset

Given a Simpset, the rewrite command applies it to an existing Term to produce a new Term.

rewrite : Simpset -> Term -> Term

To make this more concrete, we examine how the rewriting example sketched above, to convert multiplication into shift, can work in practice. We simplify everything with cryptol_ss as we go along so that the Terms don’t get too cluttered. First, we declare the term to be transformed:

sawscript> let term = rewrite (cryptol_ss ()) {{ \(x:[8]) -> (x * 2) + 1 }};
sawscript> print_term term;
\(x::Prelude.Vec 8 Prelude.Bool) ->
  Prelude.bvAdd 8
    (Prelude.bvMul 8 x
       (Prelude.bvNat 8 2))
    (Prelude.bvNat 8 1)

Next, we declare the rewrite rule:

sawscript> let rule = rewrite (cryptol_ss ()) {{ \(y:[8]) -> (y * 2) == (y << 1) }};
sawscript> print_term rule;
let { x0 = Prelude.Vec 8 Prelude.Bool;
 in \(y::x0) ->
      Prelude.eq x0
        (Prelude.bvMul 8 y
           (Prelude.bvNat 8 2))
        (Prelude.bvShiftL 8 Prelude.Bool
           (Prelude.bvNat 1 1))

Finally, we apply the rule to the target term:

sawscript> let result = rewrite (addsimp' rule empty_ss) term;
sawscript> print_term result;
\(x::Prelude.Vec 8 Prelude.Bool) ->
  Prelude.bvAdd 8
    (Prelude.bvShiftL 8 Prelude.Bool
       (Prelude.bvNat 1 1))
    (Prelude.bvNat 8 1)

Note that addsimp' and addsimps' take a Term or list of Terms; these could in principle be anything, and are not necessarily terms representing logically valid equalities. They have ' suffixes because they are not intended to be the primary interface to rewriting. When using these functions, the soundness of the proof process depends on the correctness of these rules as a side condition.

The primary interface to rewriting uses the Theorem type instead of the Term type, as shown in the signatures for addsimp and addsimps.

addsimp : Theorem -> Simpset -> Simpset

addsimps : [Theorem] -> Simpset -> Simpset

A Theorem is essentially a Term that is proven correct in some way. In general, a Theorem can be any statement, and may not be useful as a rewrite rule. However, if it has the shape described earlier, it can be used for rewriting. In the “Proofs about Terms” section, we’ll describe how to construct Theorem values from Term values.

In the absence of user-constructed Theorem values, there are some additional built-in rules that are not included in either basic_ss and cryptol_ss because they are not always beneficial, but that can sometimes be helpful or essential.

add_cryptol_eqs : [String] -> Simpset -> Simpset

add_prelude_defs : [String] -> Simpset -> Simpset

add_prelude_eqs : [String] -> Simpset -> Simpset

The cryptol_ss simpset includes rewrite rules to unfold all definitions in the Cryptol SAWCore module, but does not include any of the terms of equality type. The add_cryptol_eqs function adds the terms of equality type with the given names to the given Simpset. The add_prelude_defs and add_prelude_eqs functions add definition unfolding rules and equality-typed terms, respectively, from the SAWCore Prelude module.

Finally, it’s possible to construct a theorem from an arbitrary SAWCore expression (rather than a Cryptol expression), using the core_axiom function.

core_axiom : String -> Theorem

Any Theorem introduced by this function is assumed to be correct, so use it with caution.

Folding and Unfolding

A SAWCore term can be given a name using the define function, and is then by default printed as that name alone. A named subterm can be “unfolded” so that the original definition appears again.

define : String -> Term -> TopLevel Term

unfold_term : [String] -> Term -> Term

For example:

sawscript> let t = {{ 0x22 }}
sawscript> print_term t
Prelude.bvNat 8 34
sawscript> t' <- define "t" t
sawscript> print_term t'
sawscript> let t'' = unfold_term ["t"] t'
sawscript> print_term t''
Prelude.bvNat 8 34

This process of folding and unfolding is useful both to make large terms easier for humans to work with and to make automated proofs more tractable. We’ll describe the latter in more detail when we discuss interacting with external provers.

In some cases, folding happens automatically when constructing Cryptol expressions. Consider the following example:

sawscript> let t = {{ 0x22 }}
sawscript> print_term t
Prelude.bvNat 8 34
sawscript> let {{ t' = 0x22 }}
sawscript> print_term {{ t' }}

This illustrates that a bare expression in Cryptol braces gets translated directly to a SAWCore term. However, a Cryptol definition gets translated into a folded SAWCore term. In addition, because the second definition of t occurs at the Cryptol level, rather than the SAWScript level, it is visible only inside Cryptol braces. Definitions imported from Cryptol source files are also initially folded and can be unfolded as needed.

Other Built-in Transformation and Inspection Functions

In addition to the Term transformation functions described so far, a variety of others also exist.

beta_reduce_term : Term -> Term

replace : Term -> Term -> Term -> TopLevel Term

The beta_reduce_term function takes any sub-expression of the form (\x -> t) v in the given Term and replaces it with a transformed version of t in which all instances of x are replaced by v.

The replace function replaces arbitrary subterms. A call to replace x y t replaces any instance of x inside t with y.

Assessing the size of a term can be particularly useful during benchmarking. SAWScript provides two mechanisms for this.

term_size : Term -> Int

term_tree_size : Term -> Int

The first, term_size, calculates the number of nodes in the Directed Acyclic Graph (DAG) representation of a Term used internally by SAW. This is the most appropriate way of determining the resource use of a particular term. The second, term_tree_size, calculates how large a Term would be if it were represented by a tree instead of a DAG. This can, in general, be much, much larger than the number returned by term_size, and serves primarily as a way of assessing, for a specific term, how much benefit there is to the term sharing used by the DAG representation.

Finally, there are a few commands related to the internal SAWCore type of a Term.

check_term : Term -> TopLevel ()

type : Term -> Type

The check_term command checks that the internal structure of a Term is well-formed and that it passes all of the rules of the SAWCore type checker. The type function returns the type of a particular Term, which can then be used to, for example, construct a new fresh variable with fresh_symbolic.

Loading and Storing Terms

Most frequently, Term values in SAWScript come from Cryptol, JVM, or LLVM programs, or some transformation thereof. However, it is also possible to obtain them from various other sources.

parse_core : String -> Term

read_aig : String -> TopLevel Term

read_bytes : String -> TopLevel Term

read_core : String -> TopLevel Term

The parse_core function parses a String containing a term in SAWCore syntax, returning a Term. The read_core command is similar, but obtains the text from the given file and expects it to be in the simpler SAWCore external representation format, rather than the human-readable syntax shown so far. The read_aig command returns a Term representation of an And-Inverter-Graph (AIG) file in AIGER format. The read_bytes command reads a constant sequence of bytes from a file and represents it as a Term. Its result will always have Cryptol type [n][8] for some n.

It is also possible to write Term values into files in various formats, including: AIGER (write_aig), CNF (write_cnf), SAWCore external representation (write_core), and SMT-Lib version 2 (write_smtlib2).

write_aig : String -> Term -> TopLevel ()

write_cnf : String -> Term -> TopLevel ()

write_core : String -> Term -> TopLevel ()

write_smtlib2 : String -> Term -> TopLevel ()

Proofs about Terms

The goal of SAW is to facilitate proofs about the behavior of programs. It may be useful to prove some small fact to use as a rewrite rule in later proofs, but ultimately these rewrite rules come together into a proof of some higher-level property about a software system.

Whether proving small lemmas (in the form of rewrite rules) or a top-level theorem, the process builds on the idea of a proof script that is run by one of the top level proof commands.

prove_print : ProofScript SatResult -> Term -> TopLevel Theorem

sat_print : ProofScript SatResult -> Term -> TopLevel ()

The prove_print command takes a proof script (which we’ll describe next) and a Term. The Term should be of function type with a return value of Bool (Bit at the Cryptol level). It will then use the proof script to attempt to show that the Term returns True for all possible inputs. If it is successful, it will print Valid and return a Theorem. If not, it will abort.

The sat_print command is similar except that it looks for a single value for which the Term evaluates to True and prints out that value, returning nothing.

A similar command to prove_print, prove_core, can produce a Theorem from a string containing a SAWCore term.

prove_core : ProofScript SatResult -> String -> TopLevel Theorem

Automated Tactics

The simplest proof scripts just specify the automated prover to use. The ProofScript values abc and z3 select the ABC and Z3 theorem provers, respectively, and are typically good choices.

For example, combining prove_print with abc:

sawscript> t <- prove_print abc {{ \(x:[8]) -> x+x == x*2 }}
sawscript> t
Theorem (let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
      x1 = Cryptol.ePArith x0;
 in \(x::Prelude.Vec 8 Prelude.Bool) ->
      Cryptol.ecEq x0
        (Cryptol.ePCmp x0)
        (Cryptol.ecPlus x0 x1 x x)
        (Cryptol.ecMul x0 x1 x
           (Prelude.bvNat 8 2)))

Similarly, sat_print will show that the function returns True for one specific input (which it should, since we already know it returns True for all inputs):

sawscript> sat_print abc {{ \(x:[8]) -> x+x == x*2 }}
Sat: [x = 0]

In addition to these, the boolector, cvc4, mathsat, and yices provers are available. The internal decision procedure rme, short for Reed-Muller Expansion, is an automated prover that works particularly well on the Galois field operations that show up, for example, in AES.

In more complex cases, some pre-processing can be helpful or necessary before handing the problem off to an automated prover. The pre-processing can involve rewriting, beta reduction, unfolding, the use of provers that require slightly more configuration, or the use of provers that do very little real work.

Proof Script Diagnostics

During development of a proof, it can be useful to print various information about the current goal. The following tactics are useful in that context.

print_goal : ProofScript ()

print_goal_consts : ProofScript ()

print_goal_depth : Int -> ProofScript ()

print_goal_size : ProofScript ()

The print_goal tactic prints the entire goal in SAWCore syntax. The print_goal_depth is intended for especially large goals. It takes an integer argument, n, and prints the goal up to depth n. Any elided subterms are printed with a ... notation. The print_goal_consts tactic prints a list of the names of subterms that are folded in the current goal, and print_goal_size prints the number of nodes in the DAG representation of the goal.

Rewriting in Proof Scripts

The simplify command works just like the rewrite command, except that it works in a ProofScript context and implicitly transforms the current (unnamed) goal rather than taking a Term as a parameter.

simplify : Simpset -> ProofScript ()

Other Transformations

Some useful transformations are not easily specified using equality statements, and instead have special tactics.

beta_reduce_goal : ProofScript ()

unfolding : [String] -> ProofScript ()

The beta_reduce_goal tactic takes any sub-expression of the form (\x -> t) v and replaces it with a transformed version of t in which all instances of x are replaced by v.

The unfolding tactic works like unfold_term but on the current goal. Using unfolding is mostly valuable for proofs based entirely on rewriting, since default behavior for automated provers is to unfold everything before sending a goal to a prover. However, with Z3 and CVC4, it is possible to indicate that specific named subterms should be represented as uninterpreted functions.

unint_cvc4 : [String] -> ProofScript SatResult

unint_yices : [String] -> ProofScript SatResult

unint_z3 : [String] -> ProofScript SatResult

The list of String arguments in these cases indicates the names of the subterms to leave folded, and therefore present as uninterpreted functions to the prover. To determine which folded constants appear in a goal, use the print_goal_consts function described above.

Ultimately, we plan to implement a more generic tactic that leaves certain constants uninterpreted in whatever prover is ultimately used (provided that uninterpreted functions are expressible in the prover).

Other External Provers

In addition to the built-in automated provers already discussed, SAW supports more generic interfaces to other arbitrary theorem provers supporting specific interfaces.

external_aig_solver : String -> [String] -> ProofScript SatResult

external_cnf_solver : String -> [String] -> ProofScript SatResult

The external_aig_solver function supports theorem provers that can take input as a single-output AIGER file. The first argument is the name of the executable to run. The second argument is the list of command-line parameters to pass to that executable. Within this list, any element that consists of %f on its own is replaced with the name of the temporary AIGER file generated for the proof goal. The output from the solver is expected to be in DIMACS solution format.

The external_cnf_solver function works similarly but for SAT solvers that take input in DIMACS CNF format and produce output in DIMACS solution format.

Offline Provers

For provers that must be invoked in more complex ways, or to defer proof until a later time, there are functions to write the current goal to a file in various formats, and then assume that the goal is valid through the rest of the script.

offline_aig : String -> ProofScript SatResult

offline_cnf : String -> ProofScript SatResult

offline_extcore : String -> ProofScript SatResult

offline_smtlib2 : String -> ProofScript SatResult

offline_unint_smtlib2 : [String] -> String -> ProofScript SatResult

These support the AIGER, DIMACS CNF, shared SAWCore, and SMT-Lib v2 formats, respectively. The shared representation for SAWCore is described in the saw-script repository. The offline_unint_smtlib2 command represents the folded subterms listed in its first argument as uninterpreted functions.

Miscellaneous Tactics

Some proofs can be completed using unsound placeholders, or using techniques that do not require significant computation.

assume_unsat : ProofScript SatResult

assume_valid : ProofScript ProofResult

quickcheck : Int -> ProofScript SatResult

trivial : ProofScript SatResult

The assume_unsat and assume_valid tactics indicate that the current goal should be considered unsatisfiable or valid, depending on whether the proof script is checking satisfiability or validity. At the moment, java_verify and llvm_verify run their proofs in the a satisfiability-checking context, so assume_unsat is currently the appropriate tactic. This is likely to change in the future.

The quickcheck tactic runs the goal on the given number of random inputs, and succeeds if the result of evaluation is always True. This is unsound, but can be helpful during proof development, or as a way to provide some evidence for the validity of a specification believed to be true but difficult or infeasible to prove.

The trivial tactic states that the current goal should be trivially true (i.e., the constant True or a function that immediately returns True). It fails if that is not the case.

Proof Failure and Satisfying Assignments

The prove_print and sat_print commands print out their essential results (potentially returning a Theorem in the case of prove_print). In some cases, though, one may want to act programmatically on the result of a proof rather than displaying it.

The prove and sat commands allow this sort of programmatic analysis of proof results. To allow this, they use two types we haven’t mentioned yet: ProofResult and SatResult. These are different from the other types in SAWScript because they encode the possibility of two outcomes. In the case of ProofResult, a statement may be valid or there may be a counter-example. In the case of SatResult, there may be a satisfying assignment or the statement may be unsatisfiable.

prove : ProofScript SatResult -> Term -> TopLevel ProofResult

sat : ProofScript SatResult -> Term -> TopLevel SatResult

To operate on these new types, SAWScript includes a pair of functions:

caseProofResult : {b} ProofResult -> b -> (Term -> b) -> b

caseSatResult : {b} SatResult -> b -> (Term -> b) -> b

The caseProofResult function takes a ProofResult, a value to return in the case that the statement is valid, and a function to run on the counter-example, if there is one. The caseSatResult function has the same shape: it returns its first argument if the result represents an unsatisfiable statement, or its second argument applied to a satisfying assignment if it finds one.

AIG Values and Proofs

Most SAWScript programs operate on Term values, and in most cases this is the appropriate representation. It is possible, however, to represent the same function that a Term may represent using a different data structure: an And-Inverter-Graph (AIG). An AIG is a representation of a Boolean function as a circuit composed entirely of AND gates and inverters. Hardware synthesis and verification tools, including the ABC tool that SAW has built in, can do efficient verification and particularly equivalence checking on AIGs.

To take advantage of this capability, a handful of built-in commands can operate on AIGs.

bitblast : Term -> TopLevel AIG

cec : AIG -> AIG -> TopLevel ProofResult

load_aig : String -> TopLevel AIG

save_aig : String -> AIG -> TopLevel ()

save_aig_as_cnf : String -> AIG -> TopLevel ()

The bitblast command represents a Term as an AIG by “blasting” all of its primitive operations (things like bit-vector addition) down to the level of individual bits. The cec command, for Combinational Equivalence Check, will compare two AIGs, returning a ProofResult representing whether the two are equivalent. The load_aig and save_aig commands work with external representations of AIG data structures in the AIGER format. Finally, save_aig_as_cnf will write an AIG out in CNF format for input into a standard SAT solver.

Symbolic Execution

Analysis of Java and LLVM within SAWScript relies heavily on symbolic execution, so some background on how this process works can help with understanding the behavior of the available built-in functions.

At the most abstract level, symbolic execution works like normal program execution except that the values of all variables within the program can be arbitrary expressions, potentially containing free variables, rather than concrete values. Therefore, each symbolic execution corresponds to some set of possible concrete executions.

As a concrete example, consider the following C program that returns the maximum of two values:

unsigned int max(unsigned int x, unsigned int y) {
    if (y > x) {
        return y;
    } else {
        return x;

If you call this function with two concrete inputs, like this:

int r = max(5, 4);

then it will assign the value 5 to r. However, we can also consider what it will do for arbitrary inputs. Consider the following example:

int r = max(a, b);

where a and b are variables with unknown values. It is still possible to describe the result of the max function in terms of a and b. The following expression describes the value of r:

ite (b > a) b a

where ite is the “if-then-else” mathematical function, which based on the value of the first argument returns either the second or third. One subtlety of constructing this expression, however, is the treatment of conditionals in the original program. For any concrete values of a and b, only one branch of the if statement will execute. During symbolic execution, on the other hand, it is necessary to execute both branches, track two different program states (each composed of symbolic values), and then merge those states after executing the if statement. This merging process takes into account the original branch condition and introduces the ite expression.

A symbolic execution system, then, is very similar to an interpreter that has a different notion of what constitutes a value and executes all paths through the program instead of just one. Therefore, the execution process is similar to that of a normal interpreter, and the process of generating a model for a piece of code is similar to building a test harness for that same code.

More specifically, the setup process for a test harness typically takes the following form:

  • Initialize or allocate any resources needed by the code. For Java and LLVM code, this typically means allocating memory and setting the initial values of variables.

  • Execute the code.

  • Check the desired properties of the system state after the code completes.

Accordingly, three pieces of information are particularly relevant to the symbolic execution process, and are therefore needed as input to the symbolic execution system:

  • The initial (potentially symbolic) state of the system.

  • The code to execute.

  • The final state of the system, and which parts of it are relevant to the properties being tested.

In the following sections, we describe how the Java and LLVM analysis primitives work in the context of these key concepts. We start with the simplest situation, in which the structure of the initial and final states can be directly inferred, and move on to more complex cases that require more information from the user.

Symbolic Termination

In the previous section we described the process of executing multiple branches and merging the results when encountering a conditional statement in the program. When a program contains loops, the branch that chooses to continue or terminate a loop could go either way. Therefore, without a bit more information, the most obvious implementation of symbolic execution would never terminate when executing programs that contain loops.

The solution to this problem is to analyze the branch condition whenever considering multiple branches. If the condition for one branch can never be true in the context of the current symbolic state, there is no reason to execute that branch, and skipping it can make it possible for symbolic execution to terminate.

Directly comparing the branch condition to a constant can sometimes be enough to ensure termination. For example, in simple, bounded loops like the following, comparison with a constant is sufficient.

for (int i = 0; i < 10; i++) {
    // do something

In this case, the value of i is always concrete, and will eventually reach the value 10, at which point the branch corresponding to continuing the loop will be infeasible.

As a more complex example, consider the following function:

uint8_t f(uint8_t i) {
  int done = 0;
  while (!done) {
    if (i % 8 == 0) done = 1;
    i += 5;
  return i;

The loop in this function can only be determined to symbolically terminate if the analysis takes into account algebraic rules about common multiples. Similarly, it can be difficult to prove that a base case is eventually reached for all inputs to a recursive program.

In this particular case, however, the code is guaranteed to terminate after a fixed number of iterations (where the number of possible iterations is a function of the number of bits in the integers being used). To show that the last iteration is in fact the last possible one, it’s necessary to do more than just compare the branch condition with a constant. Instead, we can use the same proof tools that we use to ultimately analyze the generated models to, early in the process, prove that certain branch conditions can never be true (i.e., are unsatisfiable).

Normally, most of the Java and LLVM analysis commands simply compare branch conditions to the constant True or False to determine whether a branch may be feasible. However, each form of analysis allows branch satisfiability checking to be turned on if needed, in which case functions like f above will terminate.

Now, we examine the details of the specific commands available to analyze JVM and LLVM programs.

Loading Code

The first step in analyzing any code is to load it into the system.

To load LLVM code, simply provide the location of a valid bitcode file to the llvm_load_module function.

llvm_load_module : String -> TopLevel LLVMModule

The resulting LLVMModule can be passed into the various functions described below to perform analysis of specific LLVM functions.

Loading Java code is slightly more complex, because of the more structured nature of Java packages. First, when running saw, two flags control where to look for classes. The -j flag takes the name of a JAR file as an argument and adds the contents of that file to the class database. The -c flag takes the name of a directory as an argument and adds all class files found in that directory (and its subdirectories) to the class database. By default, the current directory is included in the class path. However, the Java runtime and standard library (usually called rt.jar) is generally required for any non-trivial Java code, and can be installed in a wide variety of different locations. Therefore, for most Java analysis, you must provide a -j argument specifying where to find this file.

Once the class path is configured, you can pass the name of a class to the java_load_class function.

java_load_class : String -> TopLevel JavaClass

The resulting JavaClass can be passed into the various functions described below to perform analysis of specific Java methods.

Direct Extraction

In the case of the max function described earlier, the relevant inputs and outputs are immediately apparent. The function takes two integer arguments, always uses both of them, and returns a single integer value, making no other changes to the program state.

In cases like this, a direct translation is possible, given only an identification of which code to execute. Two functions exist to handle such simple code:

java_extract : JavaClass -> String -> JavaSetup () -> TopLevel Term

llvm_extract : LLVMModule -> String -> LLVMSetup () -> TopLevel Term

The structure of these two functions is essentially identical. The first argument describes where to look for code (in either a Java class or an LLVM module, loaded as described in the previous section). The second argument is the name of the method or function to extract.

The third argument provides the ability to configure other aspects of the symbolic execution process. At the moment, only one option is available: pass in java_pure or llvm_pure, for Java and LLVM respectively, and the default extraction process is simply to set both arguments to fresh symbolic variables.

When the ..._extract functions complete, they return a Term corresponding to the value returned by the function or method.

These functions currently work only for code that takes some fixed number of integral parameters, returns an integral result, and does not access any dynamically-allocated memory (although temporary memory allocated during execution and not visible afterward is allowed).

Creating Symbolic Variables

The direct extraction process just discussed automatically introduces symbolic variables and then abstracts over them, yielding a SAWScript Term that reflects the semantics of the original Java or LLVM code. For simple functions, this is often the most convenient interface. For more complex code, however, it can be necessary (or more natural) to specifically introduce fresh variables and indicate what portions of the program state they correspond to.

The function fresh_symbolic is responsible for creating new variables in this context.

fresh_symbolic : String -> Type -> TopLevel Term

The first argument is a name used for pretty-printing of terms and counter-examples. In many cases it makes sense for this to be the same as the name used within SAWScript, as in the following:

x <- fresh_symbolic "x" ty;

However, using the same name is not required.

The second argument to fresh_symbolic is the type of the fresh variable. Ultimately, this will be a SAWCore type; however, it is usually convenient to specify it using Cryptol syntax with the type quoting brackets {| and |}. For example, creating a 32-bit integer, as might be used to represent a Java int or an LLVM i32, can be done as follows:

x <- fresh_symbolic "x" {| [32] |};

Although symbolic execution works best on symbolic variables, which are “unbound” or “free”, most of the proof infrastructure within SAW uses variables that are bound by an enclosing lambda expression. Given a Term with free symbolic variables, we can construct a lambda term that binds them in several ways.

abstract_symbolic : Term -> Term

lambda : Term -> Term -> Term

lambdas : [Term] -> Term -> Term

The abstract_symbolic function is the simplest, but gives you the least control. It finds all symbolic variables in the Term and constructs a lambda expression binding each one, in some order. The result is a function of some number of arguments, one for each symbolic variable.

sawscript> x <- fresh_symbolic "x" {| [8] |}
sawscript> let t = {{ x + x }}
sawscript> print_term t
let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
 in Cryptol.ecPlus x0
      (Cryptol.ePArith x0)
sawscript> let f = abstract_symbolic t
sawscript> print_term f
let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
 in \(x::Prelude.Vec 8 Prelude.Bool) ->
      Cryptol.ecPlus x0
        (Cryptol.ePArith x0)

If there are multiple symbolic variables in the Term passed to abstract_symbolic, the ordering of parameters can be hard to predict. In some cases (such as when a proof is the immediate next step, and it’s expected to succeed) the order isn’t important. In others, it’s nice to have more control over the order.

The building block for controlled binding is lambda. It takes two terms: the one to transform, and the portion of the term to abstract over. Generally, the first Term is one obtained from fresh_symbolic and the second is a Term that would be passed to abstract_symbolic.

sawscript> let f = lambda x t
sawscript> print_term f
let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
 in \(x::Prelude.Vec 8 Prelude.Bool) ->
      Cryptol.ecPlus x0
        (Cryptol.ePArith x0)

For Terms with more than one symbolic variable, lambdas allows you to list the order in which they should be bound. Consider, for example, a Term which adds two symbolic variables:

sawscript> x1 <- fresh_symbolic "x1" {| [8] |}
sawscript> x2 <- fresh_symbolic "x2" {| [8] |}
sawscript> let t = {{ x1 + x2 }}
sawscript> print_term t
let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
      x1 = Prelude.Vec 8 Prelude.Bool;
 in Cryptol.ecPlus x0
      (Cryptol.ePArith x0)

We can turn t into a function that takes x1 followed by x2:

sawscript> let f1 = lambdas [x1, x2] t
sawscript> print_term f1
let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
      x1 = Prelude.Vec 8 Prelude.Bool;
 in \(x1::x1) ->
      \(x2::x1) ->
        Cryptol.ecPlus x0
          (Cryptol.ePArith x0)

Or we can turn t into a function that takes x2 followed by x1:

sawscript> let f1 = lambdas [x2, x1] t
sawscript> print_term f1
let { x0 = Cryptol.TCSeq (Cryptol.TCNum 8) Cryptol.TCBit;
      x1 = Prelude.Vec 8 Prelude.Bool;
 in \(x2::x1) ->
      \(x1::x1) ->
        Cryptol.ecPlus x0
          (Cryptol.ePArith x0)

Monolithic Symbolic Execution

In many cases, the inputs and outputs of a function are more complex than supported by the direct extraction process just described. In that case, it’s necessary to provide more information. In particular, following the structure described earlier, we need:

  • For every pointer or object reference, how much storage space it refers to.
  • A list of (potentially symbolic) values for some elements of the initial program state.
  • A list of elements of the final program state to treat as outputs.

This capability is provided by the following built-in functions:

java_symexec : JavaClass ->
               String ->
               [(String, Term)] ->
               [String] ->
               Bool ->
               TopLevel Term

llvm_symexec : LLVMModule ->
               String ->
               [(String, Int)] ->
               [(String, Term, Int)] ->
               [(String, Int)] ->
               Bool ->
               TopLevel Term

For both functions, the first two arguments are the same as for the direct extraction functions from the previous section, identifying what code to execute. The final argument for both indicates whether or not to do branch satisfiability checking.

The remaining arguments are slightly different for the two functions, due to the differences between JVM and LLVM programs.

For java_symexec, the third argument, of type [(String, Term)], provides information to configure the initial state of the program. Each String is an expression describing a component of the state, such as the name of a parameter, or a field of an object. Each Term provides the initial value of that component (which may include symbolic variables returned by fresh_symbolic).

The syntax of these expressions is as follows:

  • Arguments to the method being analyzed can be referred to by name (if the .class file contains debugging information, as it will if compiled with javac -g). The expression referring to the value of the argument x in the max example is simply x. For Java methods that do not have debugging information, arguments can be named positionally with args[0], args[1] and so on. The name this refers to the same implicit parameter as the keyword in Java.

  • The expression form pkg.C.f refers to the static field f of class C in package pkg (and deeper nesting of packages is allowed).

  • The expression return refers to the return value of the method under analysis.

  • For an expression e of object type, e.f refers to the instance field f of the object described by e.

  • The value of an expression of array type is the entire contents of the array. There is currently no way to refer to individual elements of an array.

The fourth argument of java_symexec is a list of expressions describing the elements of the state to return as outputs. The returned Term will be of tuple type if this list contains more than one element, or simply the value of the one state element if the list contains only one. In addition to the expressions listed above, this list can contain the special variable $safety, which refers to a Term describing the conditions under which the result of symbolic execution is well-defined. It can be useful to obtain this Term and prove that it’s always valid (that the program is always safe), or that it’s valid under the expected preconditions.

The llvm_symexec command uses an expression syntax similar to that for java_symexec, but not identical. The syntax is as follows:

  • Arguments to the function being analyzed can be referred to by name (if the name is reflected in the LLVM code, as it is with code generated by some versions of Clang). The expression referring to the value of the argument x in the max example is simply x. For LLVM functions that do not have named arguments (such as those generated by the Rust compiler), arguments can be named positionally with args[0], args[1] and so on.

  • Global variables can be referred to directly by name.

  • The expression return refers to the return value of the function under analysis.

  • For any valid expression e referring to something with pointer type, the expression *e refers to the value pointed to. There are some differences between this and the equivalent expression in C, however. If, for instance, e has type int *, then *e will have type int. If e referred to a pointer to an array, the C expression *e would refer to the first element of that array. In SAWScript, it refers to the entire contents of the array, and there is no way to refer to individual elements of an array.

  • For any valid expression e referring to a pointer to a struct, the expression e->n, for some natural number n, refers to the nth field of that struct. If the LLVM file contains debugging information, the field names used in the original C types are also allowed.

  • For any valid expression e referring to a struct (directly, not via pointer), the expression e.n, for some natural number n, refers to the nth field of that struct. This is particularly useful for fields of nested structs, even if the outer struct is passed by pointer. As for indirect fields, names are allowed if debugging information is present.

In addition to the different expression language, the arguments are similar but not identical. The third argument, of type [(String, Int)], indicates for each pointer how many elements it points to. Before execution, SAW will allocate the given number of elements of the static type of the given expression. The strings given here should be expressions identifying pointers rather than the values of those pointers.

The fourth argument, of type [(String, Term, Int)], indicates the initial values to write to the program state before execution. The elements of this list should include value expressions. For example, if a function has an argument named p of type int *, the allocation list might contain the element ("p", 1), whereas the initial values list might contain the element ("*p", v, 1), for some value v. The Int portion of each tuple indicates how large the term is: for a term with Cryptol type [n]a, the Int argument should be n. In the future we expect this value to be inferred.

Finally, the fifth argument, of type [(String, Int)], indicates the elements to read from the final state. For each entry, the String should be a value expression and the Int parameter indicates how many elements to read. The number of elements does not need to be the same as the number of elements allocated or written in the initial state. However, reading past the end of an object or reading a location that has not been initialized will lead to an error. In this list, the special name $safety works in the same way as for Java.


The following code is a complete example of using the java_symexec function.

// show that add(x,y) == add(y,x) for all x and y
cadd <- java_load_class "Add";
x <- fresh_symbolic "x" {| [32] |};
y <- fresh_symbolic "y" {| [32] |};
res <- java_symexec cadd "add" [("x", x), ("y", y)] ["return", "$safety"] true;
let jadd = {{ res.0 }};
let safe = {{ res.1 }};
jadd' <- abstract_symbolic jadd;
print_term jadd';
print "Proving commutativity:";
prove_print abc {{ \a b -> jadd' a b == jadd' b a }};
print "Proving safety:";
prove_print abc safe;
print "Done.";

This code first loads the Add class and creates two 32-bit symbolic variables, x and y. It then symbolically executes the add method with the symbolic variables just created as its two arguments, and returns the symbolic expression denoting the method’s return value.

Once the script has a Term in hand (the variable ja), it prints the term and then translates the version containing symbolic variables into a function that takes concrete values for those variables as arguments. Finally, it proves that the resulting function is commutative.

Running this script through saw gives the following output:

% saw -j <path to>rt.jar java_symexec.saw
Loading file "java_symexec.saw"
let { x0 = Prelude.Vec 32 Prelude.Bool;
 in \(x::x0) ->
      \(y::x0) -> Prelude.bvAdd 32 x y
Proving commutivity:
Proving safety:


Although the symexec functions are more flexible than the extract functions, they still have some limitations and assumptions.

  • When allocating memory for objects or arrays, each allocation is done independently. There is currently no way to create data structures that share sub-structures. No aliasing is possible. Therefore, it is important to take into account that any proofs performed on the results of symbolic execution will not necessarily reflect the behavior of the code being analyzed if it is run in a context where its inputs involve aliasing or overlapping memory regions.

  • The sizes and pointer relationships between objects in the heap must be specified before doing symbolic execution. Therefore, the results may not reflect the behavior of the code when called with, for example, arrays of different sizes.

  • In Java, any variables of class type are initialized to refer to an object of that specific, statically-declared type, while in general they may refer to objects of subtypes of that type. Therefore, the code under analysis may behave differently when given parameters of more specific types.

Specification-Based Verification

The built-in functions described so far work by extracting models of code that can then be used for a variety of purposes, including proofs about the properties of the code.

When the goal is to prove equivalence between some Java or LLVM code and a specification, however, a more declarative approach is sometimes convenient. The following two functions allow for combined model extraction and verification.

java_verify : JavaClass ->
              String ->
              [JavaMethodSpec] ->
              JavaSetup () ->
              TopLevel JavaMethodSpec

llvm_verify : LLVMModule ->
              String ->
              [LLVMMethodSpec] ->
              LLVMSetup () ->
              TopLevel LLVMMethodSpec

Like all of the functions for Java and LLVM analysis, the first two parameters indicate what code to analyze. The third parameter is used for compositional verification, as described in the next section. For now, we will use the empty list. The final parameter describes the specification of the code to be analyzed, comprised of commands of type JavaSetup or LLVMSetup. In most cases, this parameter will be a do block containing a sequence of commands of the appropriate type. Java and LLVM specifications are slightly different, but make use of largely the same set of concepts.

  • Several commands are available to configure the contents of the initial state before symbolic execution.

  • Several commands are available to describe what to check in the final state after symbolic execution.

  • One final command describes how to prove that the code under analysis matches the specification.

The following sections describe the details of configuring initial states, stating the expected properties of the final state, and proving that the final state actually satisfies those properties.

Configuring the Initial State

The first step in configuring the initial state is to specify which program variables are important, and to specify the types of those variables more precisely. The symbolic execution system currently expects the layout of memory before symbolic execution to be completely specified. As in llvm_symexec, SAW needs information about how much space every pointer or reference variable points to. With one exception, SAW assumes that every pointer points to a distinct region of memory.

Because of this structure, separate functions are used to describe variables with values of base types and variables of pointer type.

For simple integer values, we use java_var or llvm_var.

java_var : String -> JavaType -> JavaSetup Term

llvm_var : String -> LLVMType -> LLVMSetup Term

These functions both take a variable name and a type. The variable names use the same syntax described earlier for java_symexec and llvm_symexec. The types are built up using the following functions:

java_bool : JavaType
java_byte : JavaType
java_char : JavaType
java_short : JavaType
java_int : JavaType
java_long : JavaType
java_float : JavaType
java_double : JavaType
java_class : String -> JavaType
java_array : Int -> JavaType -> JavaType

llvm_int : Int -> LLVMType
llvm_array : Int -> LLVMType -> LLVMType
llvm_struct : String -> LLVMType
llvm_float : LLVMType
llvm_double : LLVMType

Most of these types are straightforward mappings to the standard Java and LLVM types. The one key difference is that arrays must have a fixed, concrete size. Therefore, all analysis results are valid only under the assumption that any arrays have the specific size indicated, and may not hold for other sizes. The llvm_int function also takes an Int parameter indicating the variable’s bit width.

LLVM types can also be specified in LLVM syntax directly by using the llvm_type function.

llvm_type : String -> LLVMType

For example, llvm_type "i32" yields the same result as llvm_int 32.

The Term returned by java_var and llvm_var is a representation of the initial value of the variable being declared. It can be used in any later expression.

While java_var and llvm_var declare elements of the program state that have values representable in the logic of SAW, pointers and references exist only inside the simulator; they are not representable before or after symbolic execution. Different functions are used to declare variables of pointer or reference type.

java_class_var : String -> JavaType -> JavaSetup ()

llvm_ptr : String -> LLVMType -> LLVMSetup ()

The first argument of each function is the name of the state element it refers to. For java_class_var, the second argument is the type of the object, which should always be the result of the java_class function called with an appropriate class name. Arrays in Java are treated as if they were values, rather than references, since their values are directly representable in SAWCore. For llvm_ptr, the second argument is the type of the value pointed to. Both functions return no useful value (the unit type ()), since the values of pointers are not meaningful in SAWCore. In LLVM, arrays are represented as pointers; therefore, the pointer and the value pointed to must be declared separately.

llvm_ptr "a" (llvm_array 10 (llvm_int 32));
a <- llvm_var "*a" (llvm_array 10 (llvm_int 32));

The java_assert and llvm_assert functions take a Term of boolean type as an argument, which states a condition that must be true in the initial state before the function under analysis executes. The term can refer to the initial values of any declared program variables.

When the condition required of an initial state is that a variable always has a specific, concrete value, optimized forms of these functions are available. The java_assert_eq and llvm_assert_eq functions take two arguments: an expression naming a location in the program state, and a Term representing an initial value. These functions work as destructive updates in the state of the symbolic simulator, and can make branch conditions more likely to reduce to constants. This means that, although ..._assert and ..._assert_eq functions can be used to make semantically-equivalent statements, using the latter can make symbolic termination more likely.

Finally, although the default configuration of the symbolic simulators in SAW is to make every pointer or reference refer to a fresh region of memory separate from all other pointers, it is possible to override this behavior for Java programs by declaring that a set of references can alias each other.

java_may_alias : [String] -> JavaSetup ()

This function takes a list of names referring to references, and declares that any element of this set may (or may not) alias any other. Because this is a may-alias relationship, the verification process involves a separate proof for each possible aliasing configuration. At the moment, LLVM heaps must be completely disjoint.

Another precondition relevant only to Java concerns the set of classes that are initialized before execution of a particular method. To state that the proof of the method being specified assumes that a class C is already initialized, use java_requires_class "C".

java_requires_class : String -> JavaSetup ()

During verification, the java_requires_class clause instructs the simulator to initialize the named class before executing the method to be verified.

Finally, one more precondition is relevant only to LLVM programs. The llvm_assert_null function works like llvm_assert_eq except that it works only on pointer variables and assigns the implicit value NULL.

llvm_assert_null : String -> LLVMSetup ()

Specifying the Final State

The simplest statement about the expected final state of the method or function under analysis is a declaration of what value it should return (generally as a function of the variables declared as part of the initial state).

java_return : Term -> JavaSetup ()

llvm_return : Term -> LLVMSetup ()

llvm_return_arbitrary : LLVMSetup ()

The llvm_return_arbitrary command indicates that the function does return a value, but that we don’t want to specify what value it returns.

To account for side effects, the following two functions allow declaration of the final expected value that the program state should contain for a specific pvariable when execution finishes.

java_ensure_eq : String -> Term -> JavaSetup ()

llvm_ensure_eq : String -> Term -> LLVMSetup ()

For the most part, these two functions may refer to the same set of variables used to set up the initial state. However, for functions that return pointers or objects, the special name return is also available. It can be used in java_class_var and llvm_ptr calls to declare the more specific object or array type of a return value, and in the ..._ensure_eq function to declare the associated values. For LLVM arrays, the typical usage is as follows.

llvm_ensure_eq "*return" v;

The return expression is also useful for fields of returned objects or structs.

java_ensure_eq "return.f" v;

llvm_ensure_eq "return->0" v;

Finally, for LLVM programs it is possible to state that the function being analyzed is expected to allocate a new object, stored in a given location.

llvm_allocates : String -> LLVMSetup ()

When executing an override containing llvm_allocates, the override allocates a new object of the appropriate type and stores a pointer to it in the given location.

Running Proofs

Once the constraints on the initial and final states have been declared, what remains is to prove that the code under analysis actually meets these specifications. The goal of SAW is to automate this proof as much as possible, but some degree of input into the proof process is occasionally necessary, and can be provided with the following functions.

java_verify_tactic : ProofScript SatResult -> JavaSetup ()

llvm_verify_tactic : ProofScript SatResult -> LLVMSetup ()

The proof script argument to these functions specifies how to perform the proof. If the setup block does not call one of these functions, SAW prints a warning message and skips the proof; this can sometimes be a useful behavior during debugging, or in compositional verification as described later.

The process of verification checks all user-specified postconditions, and also checks that the safety condition (as referred to by $safety in *_symexec) is valid, and therefore that symbolic execution is always well defined (under the supplied pre-conditions).

Compositional Verification

The primary advantage of the specification-based approach to verification is that it allows for compositional reasoning. That is, when proving properties of a given method or function, we can make use of properties we have already proved about its callees rather than analyzing them anew. This enables us to reason about much larger and more complex systems than otherwise possible.

The java_verify and llvm_verify functions returns values of type JavaMethodSpec and LLVMMethodSpec, respectively. These values are opaque objects that internally contain both the information provided in the associated JavaSetup or LLVMSetup blocks and the results of the verification process.

Any of these MethodSpec objects can be passed in via the third argument of the ..._verify functions. For any function or method specified by one of these parameters, the simulator will not follow calls to the associated target. Instead, it will perform the following steps:

  • Check that all ..._assert and ..._assert_eq statements in the specification are satisfied.
  • For Java programs, check that any aliasing is compatible with the aliasing restrictions stated with java_may_alias.
  • For Java programs, check that all classes required by the target method have already been initialized.
  • Update the simulator state as described in the specification.

Normally, a MethodSpec is the result of both simulation and proof of the target code. However, in some cases, it can be useful to use a MethodSpec to specify some code that either doesn’t exist or is hard to prove. In those cases, the java_no_simulate or llvm_no_simulate function can be used to indicate not to even try to simulate the code being specified, and instead return a MethodSpec that is assumed to be correct. A MethodSpec with *_no_simulate can be used to provide a specification for a function or method that is declared but not defined within the code being analyzed.

The default behavior of java_verify disallows allocation within the method being analyzed. This restriction makes it possible to reason about all possible effects of a method, since only effects specified with java_ensure_eq or java_modify are allowed. For many cryptographic applications, this behavior is ideal, because it is important to know whether, for instance, temporary variables storing key material have been cleared after use. Garbage on the heap that has been collected but not cleared could let confidential information leak. If allocation is not a concern in a particular application, the java_allow_alloc function makes allocation legal within the method being specified.

Controlling Symbolic Execution

One other set of commands is available to control the symbolic execution process. These commands control the use of satisfiability checking to determine whether both paths are feasible when encountering branches in the program, which is particularly relevant for branches controlling the iteration of loops.

java_sat_branches : Bool -> JavaSetup ()
llvm_sat_branches : Bool -> LLVMSetup ()

The Bool parameter has the same effect as the Bool parameter passed to java_symexec and llvm_symexec.

Finally, in some cases, pointers in LLVM can become what look like complex symbolic values during symbolic simulation, even though they can be simplified down to constants. Using these complex pointers directly is slow, and simplifying them can greatly speed up symbolic execution of some programs. For other programs, however, the simplification is wasted effort. Therefore, the llvm_simplify_addrs command turns the simplification of pointer expressions on (with parameter true) or off (with parameter false).

llvm_simplify_addrs : Bool -> LLVMSetup ()

LLVM Verification Using Crucible

The verification commands presented for Java and LLVM so far use language-specific symbolic execution infrastructure. More recently, we have developed a new library for symbolic execution of imperative programs that is intended to be relatively agnostic to the specific source language in question. It exposes an intermediate representation based on control-flow graphs containing relatively simple instructions that can be used as the target of translation from a variety of source languages. We have successfully used it for LLVM, Matlab, and a variety of machine code ISAs, and have ongoing efforts to use it for several other languages.

In addition to being language-agnostic, Crucible has a larger feature set and generally better performance than the previous symbolic execution engines for Java and LLVM.

As an alternative to the LLVM verification commands presented earlier, an experimental set of commands for doing verification using Crucible also exist. At the moment, the key command is crucible_llvm_verify, with roughly similar functionality to llvm_verify. Counterparts of llvm_extract and llvm_symexec do not currently exist, but are planned.

As with llvm_verify, crucible_llvm_verify requires a specification as input, describing what the function under analysis is intended to do. The mechanism for setting up a specification is similar to that for llvm_verify, but uses a slightly different set of commands.

The most significant difference is that creating fresh symbolic values, describing allocation, and describing the initial value of allocated memory are distinct operations. This can sometimes result in more verbose specifications, but is more flexible and more amenable to abstraction. So, with a good set of common patterns encapsulated in functions, specifications can ultimately become more concise and understandable.

Running a Verification

Verification with Crucible is controlled by the crucible_llvm_verify command.

crucible_llvm_verify : LLVMModule ->
                       String ->
                       [CrucibleMethodSpec] ->
                       Bool ->
                       CrucibleSetup () ->
                       ProofScript SatResult ->
                       TopLevel CrucibleMethodSpec

The first two arguments specify the module and function name to verify, as with llvm_verify. The third argument specifies the list of already-verified specifications to use as overrides for compositional verification (though note that the types of specifications used by llvm_verify and crucible_llvm_verify are different, so they can’t be used interchangeably). The fourth argument specifies whether to do path satisfiability checking, and the fifth gives the specification of the function to be verified. Finally, the last argument gives the proof script to use for verification (which is separated from the specification itself, unlike llvm_verify). The result is a proved specification that can be used to simplify verification of functions that call this one.

Now we describe how to construct a value of type CrucibleSetup ().

Structure of a Specification

A specifications for Crucible consists of three logical components:

  • A specification of the initial state before execution of the function.

  • A description of how to call the function within that state.

  • A specification of the expected final value of the program state.

These three portions of the specification are written in sequence within a do block of CrucibleSetup type. The command crucible_execute_func separates the specification of the initial state from the specification of the final state, and specifies the arguments to the function in terms of the initial state. Most of the commands available for state description will work either before or after crucible_execute_func, though with slightly different meaning.

Creating Fresh Variables

In any case where you want to prove a property of a function for an entire class of inputs (perhaps all inputs) rather than concrete values, the initial values of at least some elements of the program state must contain fresh variables. These are created in a specification with the crucible_fresh_var command.

crucible_fresh_var : String -> LLVMType -> CrucibleSetup Term

The first parameter is a name, used only for presentation. It’s possible (though not recommended) to create multiple variables with the same name, but SAW will distinguish between them internally. The second parameter is the LLVM type of the variable. The resulting Term can be used in various subsequent commands.

The SetupValue Type

Many specifications require reasoning about both pure values and about the configuration of the heap. The SetupValue type corresponds to values that can occur during symbolic execution, which includes both Term values, pointers, and composite types consisting of either of these (both structures and arrays).

The crucible_term function creates a SetupValue from a Term:

crucible_term : Term -> SetupValue


Once the initial state has been configured, the crucible_execute_func command specifies the parameters of the function being analyzed in terms of the state elements already configured.

crucible_execute_func : [SetupValue] -> CrucibleSetup ()

Return Values

The crucible_points_to command can be used to specify changes to portions of the memory accessed by pointer. For return values, however, use the crucible_return command instead.

crucible_return : SetupValue -> CrucibleSetup ()

A First Simple Example

The commands introuduced so far are sufficient to verify simple programs that do not use pointers (or that use them only internally). Consider, for instance the program that adds its two arguments together:

uint32_t add(uint32_t x, uint32_t y) {
    return x + y;

We can specify this function’s expected behavior as follows:

let add_setup = do {
    x <- crucible_fresh_var "x" (llvm_int 32);
    y <- crucible_fresh_var "y" (llvm_int 32);
    crucible_execute_func [crucible_term x, crucible_term y];
    crucible_return (crucible_term {{ x + y : [32] }});

We can then compile the C file add.c into the bitcode file add.bc and verify it with ABC:

m <- llvm_load_module "add.bc";
add_ms <- crucible_llvm_verify m "add" [] false add_setup abc;

Now say we have a doubling function written in terms of add:

uint32_t dbl(uint32_t x) {
    return add(x, x);

It has a similar specification:

let dbl_setup = do {
    x <- crucible_fresh_var "x" (llvm_int 32);
    crucible_execute_func [crucible_term x];
    crucible_return (crucible_term {{ x + x : [32] }});

And we can verify it using what we’ve already proved about add:

crucible_llvm_verify m "dbl" [add_ms] false dbl_setup abc;

In this case, doing the verification compositionally doesn’t save much, since the functions are so simple, but it illustrates the approach.

Specifying Heap Layout

Most functions that operate on pointers expect that certain pointers point to allocated memory before they are called. The crucible_alloc command allows you to specify that a function expects a particular pointer to refer to an allocated region appropriate for a specific type.

crucible_alloc : LLVMType -> CrucibleSetup SetupValue

This command returns a SetupValue consisting of a pointer to the allocated space, which can be used wherever a pointer-valued SetupValue can be used.

In the initial state, crucible_alloc specifies that the function expects a pointer to allocated space to exist. In the final state, it specifies that the function itself performs an allocation.

It’s also possible to construct fresh pointers that do not point to allocated memory (which can be useful for functions that manipulate pointers but not the values they point to):

crucible_fresh_pointer : LLVMType -> CrucibleSetup SetupValue

The NULL pointer is called crucible_null:

crucible_null : SetupValue

Pointers to global variables or functions can be accessed with crucible_global:

crucible_global : String -> SetupValue

Specifying Heap Values

Pointers returned by crucible_alloc don’t, initially, point to anything. So if you pass such a pointer directly into a function that tried to dereference it, symbolic execution will fail with a message about an invalid load. For some functions, such as those that are intended to initialize data structures (writing to the memory pointed to, but never reading from it), this sort of uninitialized memory is appropriate. In most cases, however, it’s more useful to state that a pointer points to some specific (usually symbolic) value, which you can do with the crucible_points_to command.

crucible_points_to : SetupValue -> SetupValue -> CrucibleSetup ()

This command takes two SetupValue arguments, the first of which must be a pointer, and states that the memory specified by that pointer should contain the value given in the second argument (which may be any type of SetupValue).

When used in the final state, crucible_points_to specifies that the given pointer should point to the given value when the function finishes.

Working with Compound Types

The commands mentioned so far give us no way to specify the values of compound types (arrays or structs). Compound values can be dealt with either piecewise or in their entirety. To access them piecewise, the crucible_elem function yields a pointer to an internal element of a compound value.

crucible_elem : SetupValue -> Int -> SetupValue

For arrays, the Int parameter is the array index. For struct values, it is the field index. For struct values, it can be more convenient to use field names. If debugging information is available in the bitcode file, the crucible_field function yields a pointer to a particular named field:

crucible_field : SetupValue -> String -> SetupValue

Either of these functions can be used with crucible_points_to to specify the value of a particular array element or struct field. Sometimes, however, it is more convenient to specify all array elemnts or field values at onces. The crucible_array and crucible_struct functions construct compound values from lists of element values.

crucible_array : [SetupValue] -> SetupValue
crucible_struct : [SetupValue] -> SetupValue

Preconditions and Postconditions

Sometimes a function is only well-defined under certain conditions, or sometimes you may be interested in certain initial conditions that give rise to specific final conditions. For these cases, you can specify an arbitrary predicate as a pre-condition or post-condition, using any values in scope at the time.

crucible_precond : Term -> CrucibleSetup ()
crucible_postcond : Term -> CrucibleSetup ()

These two commands take Term arguments, and therefore cannot describe the values of pointers. The crucible_equal command states that two SetupValues should be equal, and can be used in either the initial or the final state.

crucible_equal : SetupValue -> SetupValue -> CrucibleSetup ()

The use of crucible_equal can also sometimes lead to more efficient symbolic execution when the predicate of interest is an equality.

A Heap-Based Example

To tie all of the command descriptions from the previous sections together, consider the case of verifying the correctness of a C program that computes the dot product of two vectors, where the length and value of each vector are encapsulated together in a struct.

The dot product can be concisely specified in Cryptol as follows:

dotprod : {n, a} (fin n, fin a) => [n][a] -> [n][a] -> [a]
dotprod xs ys = sum (zip (*) xs ys)

To implement this in C, let’s first consider the type of vectors:

typedef struct {
    uint32_t *elts;
    uint32_t size;
} vec_t;

This struct contains a pointer to an array of 32-bit elements, and a 32-bit value indicating how many elements that array has.

We can compute the dot product of two of these vectors with the following C code (which uses the size of the shorter vector if they differ in size).

uint32_t dotprod_struct(vec_t *x, vec_t *y) {
    uint32_t size = MIN(x->size, y->size);
    uint32_t res = 0;
    for(size_t i = 0; i < size; i++) {
        res += x->elts[i] * y->elts[i];
    return res;

The entirety of this implementation can be found in the examples/llvm/dotprod_struct.c file in the saw-script repository.

To verify this program in SAW, it will be convenient to define a couple of utility functions (which are generally useful for many heap-manipulating programs). First, combining allocation and initialization to a specific value can make many scripts more concise:

let alloc_init ty v = do {
    p <- crucible_alloc ty;
    crucible_points_to p v;
    return p;

This creates a pointer p pointing to enough space to store type ty, and then indicates that the pointer points to value v (which should be of that same type).

A common case for allocation and initialization together is when the initial value should be entirely symbolic.

let ptr_to_fresh n ty = do {
    x <- crucible_fresh_var n ty;
    p <- alloc_init ty (crucible_term x);
    return (x, p);

This function returns the pointer just allocated along with the fresh symbolic value it points to.

Given these two utility functions, the dotprod_struct function can be specified as follows:

let dotprod_spec n = do {
    let nt = crucible_term {{ `n : [32] }};
    (xs, xsp) <- ptr_to_fresh "xs" (llvm_array n (llvm_int 32));
    (ys, ysp) <- ptr_to_fresh "ys" (llvm_array n (llvm_int 32));
    let xval = crucible_struct [ xsp, nt ];
    let yval = crucible_struct [ ysp, nt ];
    xp <- alloc_init (llvm_struct "struct.vec_t") xval;
    yp <- alloc_init (llvm_struct "struct.vec_t") yval;
    crucible_execute_func [xp, yp];
    crucible_return (crucible_term {{ dotprod xs ys }});

Any instantiation of this specification is for a specific vector length n, and assumes that both input vectors have that length. That length n automatically becomes a type variable in the subsequent Cryptol expressions, and the backtick operator is used to reify that type as a bit vector of length 32.

The entire script can be found in the dotprod_struct-crucible.saw file alongside dotprod_struct.c.