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

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/31433

Title :	LIPS vs MOSA: a Replicated Empirical Study on Automated Test Case Generation
Language :	English
Author, co-author :	Panichella, Annibale [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Kifetew, Fitsum [Fondazione Bruno Kessler]
	Tonella, Paolo [Fondazione Bruno Kessler]
Publication date :	9-Sep-2017
Main document title :	International Symposium on Search Based Software Engineering (SSBSE) 2017
Publisher :	Springer
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	International Symposium on Search Based Software Engineering (SSBSE) 2017
Event date :	from 09-09-2017 to 11-09-2017
Event place (city) :	Paderborn
Event country :	Germany
Abstract :	[en] 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.
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)
Target :	Researchers ; Professionals ; General public
Permalink :	http://hdl.handle.net/10993/31433

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