Speaker: Pouria Derakhshanfar
When: September 16, 2020, 14:00 - 15:00
Where: Online

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 talk, I will present our recent work on the redesign of the search-objectives for crash reproduction by (i) 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. And (ii) the introduction of a new secondary objective, called Basic Block Coverage (BBC), taking into account the coverage of implicit code branches during the search.

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