Dynamic Symbolic Execution Guided by Data Dependency Analysis for High Structural Coverage

Do, T., Fong, A.C.M. and Pears, R. (2013) Dynamic Symbolic Execution Guided by Data Dependency Analysis for High Structural Coverage. In: ENASE 2012 Communications in Computer and Information Sciences (CCIS), pp. 3-15. (doi: 10.1007/978-3-642-45422-6_1)

Abstract

Dynamic symbolic execution has been shown to be an effective technique for automated test input generation. When applied to large-scale and complex programs, its scalability however is limited due to the combinatorial explosion of the path space. We propose to take advantage of data flow analysis to better perform dynamic symbolic execution in the context of generating test inputs for maximum structural coverage. In particular, we utilize the chaining mechanism to (1) extract precise guidance to direct dynamic symbolic execution towards exploring uncovered code elements and (2) meanwhile significantly optimize the path exploration process. Preliminary experiments conducted to evaluate the performance of the proposed approach have shown very encouraging results.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Fong, Dr Alvis Cheuk Min
• Authors: Do, T., Fong, A.C.M., and Pears, R.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 1865-0929