A multi-objective approach to testing resource allocation in modular software systems

Zai WANG, Ke TANG, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

15 Citations (Scopus)

Abstract

Nowadays, as the software systems become increasingly large and complex, the problem of allocating the limited testing-resource during the testing phase has become more and more difficult. In this paper, we propose to solve the testing-resource allocation problem (TRAP) using multi-objective evolutionary algorithms. Specifically, we formulate TRAP as two multi-objective problems. First, we consider the reliability of the system and the testing cost as two objectives. In the second formulation, the total testing-resource consumed is also taken into account as the third goal. Two multi-objective evolutionary algorithms, Non-dominated Sorting Genetic Algorithm II (NSGA2) and Multi-Objective Differential Evolution Algorithms (MODE), are applied to solve the TRAP in the two scenarios. This is the first time that the TRAP is explicitly formulated and solved by multi-objective evolutionary approaches. Advantages of our approaches over the state-of-the-art single-objective approaches are demonstrated on two parallel-series modular software models. © 2008 IEEE.
Original languageEnglish
Title of host publication2008 IEEE Congress on Evolutionary Computation, CEC 2008
Pages1148-1153
Number of pages6
DOIs
Publication statusPublished - Jun 2008
Externally publishedYes

Keywords

  • Multi-Objective Evolutionary Algorithm
  • Parallel-Series Modular Software System
  • Software Reliability

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