Multi-objective approaches to optimal testing resource allocation in modular software systems


Research output: Journal PublicationsJournal Article (refereed)peer-review

77 Citations (Scopus)


Software testing is an important issue in software engineering. As software systems become increasingly large and complex, the problem of how to optimally allocate the limited testing resource during the testing phase has become more important, and difficult. Traditional Optimal Testing Resource Allocation Problems (OTRAPs) involve seeking an optimal allocation of a limited amount of testing resource to a number of activities with respect to some objectives (e.g., reliability, or cost). We suggest solving OTRAPs with Multi-Objective Evolutionary Algorithms (MOEAs). Specifically, we formulate OTRAPs as two types of multi-objective problems. First, we consider the reliability of the system and the testing cost as two objectives. Second, the total testing resource consumed is also taken into account as the third objective. The advantages of MOEAs over state-of-the-art single objective approaches to OTRAPs will be shown through empirical studies. Our study has revealed that a well-known MOEA, namely Nondominated Sorting Genetic Algorithm II (NSGA-II), performs well on the first problem formulation, but fails on the second one. Hence, a Harmonic Distance Based Multi-Objective Evolutionary Algorithm (HaD-MOEA) is proposed and evaluated in this paper. Comprehensive experimental studies on both parallel-series, and star-structure modular software systems have shown the superiority of HaD-MOEA over NSGA-II for OTRAPs. © 2006 IEEE.
Original languageEnglish
Article number5549979
Pages (from-to)563-575
Number of pages13
JournalIEEE Transactions on Reliability
Issue number3
Early online date18 Aug 2010
Publication statusPublished - Sept 2010
Externally publishedYes

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under Grant 60802036 and Grant U0835002, by the Engineering and Physical Sciences Research Council (EPSRC Grant EP/D052785/1), and by the Fund for Foreign Scholars in University Research and Teaching Programs (111 project) in China under Grant B07033.


  • Multi-objective evolutionary algorithm
  • parallel-series modular software system
  • software engineering
  • software reliability
  • software testing
  • star-structure modular software system


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