A Novel Mask-Coding Representation for Set Cover Problems with Applications in Test Suite Minimisation

Author

Yoo, Shin

Author_Institution

Centre for Res. on Search, King´´s Coll. London, London, UK

fYear

2010

fDate

7-9 Sept. 2010

Firstpage

19

Lastpage

28

Abstract

Multi-Objective Set Cover problem forms the basis of many optimisation problems in software testing because the concept of code coverage is based on the set theory. This paper presents Mask-Coding, a novel representation of solutions for set cover optimisation problems that explores the problem space rather than the solution space. The new representation is empirically evaluated with set cover problems formulated from real code coverage data. The results show that Mask-Coding representation can improve both the convergence and diversity of the Pareto-efficient solution set of the multi-objective set cover optimisation.

Keywords

minimisation; program testing; set theory; Pareto-efficient solution set; code coverage; mask-coding representation; multiobjective set cover problem; optimisation problems; set theory; software testing; test suite minimisation; Convergence; Greedy algorithms; Optimization; Redundancy; Search problems; Software testing; Space exploration; search-based software engineering; set-cover representation; test suite minimisation;

fLanguage

English

Publisher

ieee

Conference_Titel

Search Based Software Engineering (SSBSE), 2010 Second International Symposium on

Conference_Location

Benevento

Print_ISBN

978-1-4244-8341-9

Type

conf

DOI

10.1109/SSBSE.2010.12

Filename

5635169