Using SMT to check specifications for errors

SMT solvers are incredibly flexible tools for analyzing complex systems. In my previous post, I showed how you can: generate a symbolic execution trace from running an instrumented interpreter on some input values; turn the trace into an SMT circuit; and use an SMT solver to check that the SMT circuit matches your original trace. This post will explore how we can check assertions, array index bounds, etc. to find bugs in the specification and how we can enumerate all the paths through a specification.

Checking assertions

The “AddWithCarry” function that I am using as my running example does not contain any assertions — but it does contain this line

result = unsigned_sum[0 +: N]; // same value as signed_sum[0 +: N]

So, for the sake of continuing the example, let’s turn that comment into an assertion

assert unsigned_sum[0 +: N] == signed_sum[0 +: N];

In the execution trace, this will generate something like this:

%14 = getslice_bits(0, 32, %8)
%t15 = getslice_bits(0, 32, %13)
%t16 = eq_bits(%14, %t15)
assert %t17 "functions/AddWithCarry.asl" 8

Saying that line 8 of file “functions/AddWithCarry.asl” asserts that condition %t16 holds. As we are translating the trace to SMT, we can generate a metadata file that contains information about this assertion:

AWC.json:
    {
        "assertions" : [
            ("t17", "functions/AddWithCarry.asl", 8)
        ]
    }

We can use this list of assertions to check that the assertions all hold for all possible inputs that follow the same path

; only consider inputs that lead to this path
(assert (not v16))
(assert v19)

; check for any input that causes the assertion to fail
(assert (not t17))

When we run z3 on this check, it can’t find any failing inputs

$ z3 t2.smt
unsat

This is good news: it means that the comment is actually true!

Implicit assertions

Of course, programs have lots of implicit assertions too:

  • array indexes must be in bounds
  • bitslice indexes must be in bounds
  • bitslices must have a non-negative width
  • division by zero is not allowed

For each of these, we can add checks to check for failures. For example, given the expression x[N-1], we will generate a check that 0 <= N-1 < N. This is going to result in a lot of checks — many of which will trivially pass. But SMT solvers are very efficient at dealing with trivial checks like this so let’s just go ahead and spray the code with checks like this, use Z3 to check them all and then, once we know that they all pass we could generate a fresh SMT file that omits the checks. (Or maybe we just leave them in?)

Finding other paths

So far, all we are doing is exploring one path at a time. So we have checked that an assertion does not fail on one path but that does not guarantee that it does not fail on any of the other paths that may exist.

This series of threads is focussed on concolic execution where we generate a symbolic execution trace by executing an instrumented interpreter on some concrete input values. On the running example from the previous post, the trace recorded that it hit two conditional branches

branch %16 = FALSE
branch %19 = TRUE

The trace is only valid for inputs that would take the same path so I added these assertions to restrict execution to the same path through the code.

(assert (not v16))
(assert v19)

More generally, I might have a long list of branches b1, b2, b3, … bm. And what I want to do is to explore paths that differ in at least one of these conditions. So I am going to use the SMT solver to try to find several different branch condition sequences:

!b1
b1, !b2
b1, b2, !b3
...
b1, b2, b3, ... !bm

On my running example, this gives me two sets of assertions to try:

(assert v16)

and

(assert (not v16))
(assert (not v19))

Running with these two sets of assertions generates two sets of input values

#xfffffffe #x00000001 #b0
#xb9d1fe83 #xc60f00ff #b1

Once we have these values, we can rerun the interpreter to generate new traces and then we can repeat the process of generating alternative branch sequences to generate traces for alternative paths through the function under test. It’s not long before this finds a fourth (final) path through the function and an input value that can trigger it.

#x7bfbff67 #x0403fe96 #b0

Going further

Checking assertions, indexes, etc. is good — but we can go further. An obvious thing to do is to try to write down any invariants that you expect to hold about the overall processor state. Another option is to scour the natural language part of the specification looking for more properties we can check. I wrote a couple of posts about doing that here and here and I wrote a paper about it.

Written on February 9, 2019. The opinions expressed are my own views and not my employer's.