LIPS vs MOSA: A replicated empirical study on automated test case generation

Annibale Panichella, Fitsum Meshesha Kifetew, Paolo Tonella

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationSearch Based Software Engineering - 9th International Symposium, SSBSE 2017, Proceedings
PublisherSpringer
Pages83-98
Number of pages16
Volume10452 LNCS
ISBN (Print)9783319662985
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event9th International Symposium on Search-Based Software Engineering, SSBSE 2017 - Paderborn, Germany
Duration: 9 Sep 201711 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10452 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Symposium on Search-Based Software Engineering, SSBSE 2017
CountryGermany
CityPaderborn
Period9/09/1711/09/17

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