HAMPI: A Solver for String Constraints

Many automatic testing, analysis, and verification techniques for programs can be effectively reduced to a constraint-generation phase followed by a constraint-solving phase. This separation of concerns often leads to more effective and maintainable tools. The increasing efficiency of off-the-shelf constraint solvers makes this approach even more compelling. However, there are few, if any, effective and sufficiently expressive off-the-shelf solvers for string constraints generated by analysis techniques for string-manipulating programs. We designed and implemented Hampi, a solver for string constraints over bounded string variables. Hampi constraints express membership in regular languages and bounded context-free languages. Hampi constraints may contain context-free-language definitions, regular-language definitions and operations, and the membership predicate. Given a set of constraints, Hampi outputs a string that satisfies all the constraints, or reports that the constraints are unsatisfiable. Hampi is expressive and efficient, and can be successfully applied to testing and analysis of real programs. Our experiments use Hampi in: static and dynamic analyses for finding SQL injection vulnerabilities in Web applications; automated bug finding in C programs using systematic testing; and compare Hampi with another string solver. Hampi's source code, documentation, and the experimental data are available at http://people.csail.mit.edu/akiezun/hampi

Constraint Solving on Bounded String Variables

Abstract Constraints on strings of unknown length occur in a wide variety of real-world problems, such as test case generation, program analysis, model checking, and web security. We describe a set of con-straints sufficient to model many standard benchmark problems from these fields. For strings of an unknown length bounded by an integer, we describe propagators for these constraints. Finally, we provide an experi-mental comparison between a state-of-the-art dedicated string solver, CP approaches utilising fixed-length string solving, and our implementation extending an off-the-shelf CP solver.