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Computer Science > Software Engineering

Title: Towards Efficient Data-flow Test Data Generation Using KLEE

Abstract: Dataflow coverage, one of the white-box testing criteria, focuses on the relations between variable definitions and their uses.Several empirical studies have proved data-flow testing is more effective than control-flow testing. However, data-flow testing still cannot find its adoption in practice, due to the lack of effective tool support. To this end, we propose a guided symbolic execution approach to efficiently search for program paths to satisfy data-flow coverage criteria. We implemented this approach on KLEE and evaluated with 30 program subjects which are constructed by the subjects used in previous data-flow testing literature, SIR, SV-COMP benchmarks. Moreover, we are planning to integrate the data-flow testing technique into the new proposed symbolic execution engine, SmartUnit, which is a cloud-based unit testing service for industrial software, supporting coverage-based testing. It has successfully helped several well-known corporations and institutions in China to adopt coverage-based testing in practice, totally tested more than one million lines of real code from industry.
Subjects: Software Engineering (cs.SE)
Cite as: arXiv:1803.06516 [cs.SE]
  (or arXiv:1803.06516v1 [cs.SE] for this version)

Submission history

From: Chengyu Zhang [view email]
[v1] Sat, 17 Mar 2018 14:45:57 GMT (551kb,D)