An evolutionary algorithm for performance optimization at software architecture level

Xin Du, Youcong Ni, Peng Ye, Xin Yao, Leandro L. Minku, Ruliang Xiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Architecture-based software performance optimization can not only significantly save time but also reduce cost. A few rule-based performance optimization approaches at software architecture (SA) level have been proposed in recent years. However, in these approaches, the number of rules being used and the order of application of each rule are uncertain in the optimization process and these uncertainties have not been fully considered so far. As a result, the search space for performance improvement is limited, possibly excluding optimal solutions. Aiming to solve this problem, we propose an evolutionary algorithm for rule-based performance optimization at SA level named EA4PO. First, the rule-based software performance optimization at SA level is abstracted into a mathematical model called RPOM. RPOM can precisely characterize the mathematical relation between the usage of rules and the optimal solution in the performance improvement space. Then, a framework named RSEF is designed to support the execution of rule sequences. Based on RPOM and RSEF, EA4PO is proposed to find the optimal performance improvement solution. In EA4PO, an adaptive mutation operator is designed to guide the search direction by fully considering heuristic information of rule usage during the evolution. Finally, the effectiveness of EA4PO is validated by comparing EA4PO with a typical rule-based approach. The results show that EA4PO can explore a relatively larger space and get better solutions.

Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)9781479974924
Publication statusPublished - 10 Sept 2015
EventIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan
Duration: 25 May 201528 May 2015


ConferenceIEEE Congress on Evolutionary Computation, CEC 2015


  • evolutionary algorithm
  • performance analysis
  • performance optimization algorithm
  • rule
  • search-based software engineering
  • software architecture

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Mathematics


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