Crash Reproduction Using Helper Objectives

Conference paper (2020)

Authors

P. Derakhshanfar Software Engineering - EEMCS
Xavier Devroey Software Engineering - EEMCS
A.E. Zaidman Software Engineering - EEMCS
A. van Deursen Software Technology
A. Panichella Software Engineering - EEMCS
Research Group
Software Engineering (EEMCS) (TU Delft)
Copyright: © 2020 P. Derakhshanfar, Xavier Devroey, A.E. Zaidman, A. van Deursen, A. Panichella
DOI
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https://doi.org/10.1145/3377929.3390077
MOEA Crash reproduction Search-based software testing
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Published Date

2020

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Software Engineering

Abstract

Evolutionary-based crash reproduction techniques aid developers in their debugging practices by generating a test case that reproduces a crash given its stack trace. In these techniques, the search process is typically guided by a single search objective called Crash Distance. Previous studies have shown that current approaches could only reproduce a limited number of crashes due to a lack of diversity in the population during the search. In this study, we address this issue by applying Multi-Objectivization using Helper-Objectives (MO-HO) on crash reproduction. In particular, we add two helper-objectives to the Crash Distance to improve the diversity of the generated test cases and consequently enhance the guidance of the search process. We assessed MO-HO against the single-objective crash reproduction. Our results show that MO-HO can reproduce two additional crashes that were not previously reproducible by the single-objective approach.