Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

8-2019

Abstract

Automated test case generation is attractive as it can reduce developer workload. To generate test cases, many Symbolic Execution approaches first produce Path Conditions (PCs), a set of constraints, and pass them to a Satisfiability Modulo Theories (SMT) solver. Despite numerous prior studies, automated test case generation by Symbolic Execution is still slow, partly due to SMT solvers’ high computationally complexity. We introduce InSPeCT, a Path Condition solver, that leverages elements of ILS (Iterated Local Search) and Tabu List. ILS is not computational intensive and focuses on generating solutions in search spaces while Tabu List prevents the use of previously generated infeasible solutions. InSPeCT is evaluated against two state-of-the-art solvers, MLB and Z3, on ten Java subject programs of varying size and complexity. The results show that InSPeCT is able to solve 16% more PCs than MLB and 41% more PCs than Z3. On average, it is 103 and 5 times faster than Z3 and MLB, respectively. It also generates tests with higher test coverage than both MLB and Z3.

Keywords

Iterated Local search, Path condition, Automated test case generation, Infeasible solutions

Discipline

Computer Sciences | Databases and Information Systems | Theory and Algorithms

Research Areas

Data Science and Engineering

Publication

2019 15th IEEE International Conference on Automation Science and Engineering (CASE): Vancouver, August 22-26: Proceedings

First Page

1724

Last Page

1729

ISBN

9781728103556

Identifier

10.1109/COASE.2019.8843039

Publisher

IEEE

City or Country

Piscataway, NJ

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/COASE.2019.8843039

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