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LIPS vs MOSA: A Replicated Empirical Study on Automated Test Case Generation

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 10452)


Replication is a fundamental pillar in the construction of scientific knowledge. Test data generation for procedural programs can be tackled using a single-target or a many-objective approach. The proponents of LIPS, a novel single-target test generator, conducted a preliminary empirical study to compare their approach with MOSA, an alternative many-objective test generator. However, their empirical investigation suffers from several external and internal validity threats, does not consider complex programs with many branches and does not include any qualitative analysis to interpret the results. In this paper, we report the results of a replication of the original study designed to address its major limitations and threats to validity. The new findings draw a completely different picture on the pros and cons of single-target vs many-objective approaches to test case generation.

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    The number of branches reported here is sometimes slightly different from that of the original study because EvoSuite performs the instrumentation and counts the branches at the byte code, not source code, level.

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Correspondence to Annibale Panichella .

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Panichella, A., Kifetew, F.M., Tonella, P. (2017). LIPS vs MOSA: A Replicated Empirical Study on Automated Test Case Generation. In: Menzies, T., Petke, J. (eds) Search Based Software Engineering. SSBSE 2017. Lecture Notes in Computer Science(), vol 10452. Springer, Cham.

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  • Print ISBN: 978-3-319-66298-5

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