26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2018), November 4–9, 2018, Lake Buena Vista, FL, USA

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Symbolic Execution and Constraint Solving
Research Papers
Parameterized Model Counting for String and Numeric Constraints
Abdulbaki Aydin, William Eiers, Lucas Bang, Tegan Brennan, Miroslav Gavrilov, Tevfik Bultan, and Fang Yu
(Microsoft, USA; University of California at Santa Barbara, USA; National Chengchi University, Taiwan)
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Abstract: Recently, symbolic program analysis techniques have been extended to quantitative analyses using model counting constraint solvers. Given a constraint and a bound, a model counting constraint solver computes the number of solutions for the constraint within the bound. We present a parameterized model counting constraint solver for string and numeric constraints. We first construct a multi-track deterministic finite state automaton that accepts all solutions to the given constraint. We limit the numeric constraints to linear integer arithmetic, and for non-regular string constraints we over-approximate the solution set. Counting the number of accepting paths in the generated automaton solves the model counting problem. Our approach is parameterized in the sense that, we do not assume a finite domain size during automata construction, resulting in a potentially infinite set of solutions, and our model counting approach works for arbitrarily large bounds. We experimentally demonstrate the effectiveness of our approach on a large set of string and numeric constraints extracted from software applications. We experimentally compare our tool to five existing model counting constraint solvers for string and numeric constraints and demonstrate that our tool is as efficient and as or more precise than other solvers. Moreover, our tool can handle mixed constraints with string and integer variables that no other tool can.


Time stamp: 2019-05-22T09:49:34+02:00