Evolutionary testing: A case study

Stella Levin*, Amiram Yehudai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

The paper presents a case study of applying genetic algorithms (GAs) to the automatic test data generation problem. We present the basic techniques implemented in our prototype test generation system, whose goal is to get branch coverage of the program under testing. We used our tool to experiment with simple programs, programs that have been used by others for test strategies benchmarking and the UNIX utility uniq. The effectiveness of GA-based testing system is compared with a Random testing system. We found that for simple programs both testing systems work fine, but as the complexity of the program or the complexity of input domain grows, GA-based testing system significantly outperforms Random testing.

Original languageEnglish
Title of host publicationHardware and Software, Verification and Testing - Second International Haifa Venfication Conference, HVC 2006, Revised Selected Papers
PublisherSpringer Verlag
Pages155-165
Number of pages11
ISBN (Print)9783540708889
DOIs
StatePublished - 2007
Event2nd International Haifa Verification Conference, HVC 2006 - Haifa, Israel
Duration: 23 Oct 200626 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4383 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Haifa Verification Conference, HVC 2006
Country/TerritoryIsrael
CityHaifa
Period23/10/0626/10/06

Keywords

  • Automatic test generation
  • Genetic algorithms
  • Software testing

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