Methodology for the quantification of the effect of patterns and anti-patterns association on the software quality

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

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Author(s)

  • Shahid Hussain
  • Muhammad Khalid Sohail
  • Ghufran Ahmad
  • Muhammad Rafiq Mufti
  • Hasan Ali Khatak

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)414-422
Journal / PublicationIET Software
Volume13
Issue number5
Online published5 Jul 2019
Publication statusPublished - Oct 2019

Abstract

The employment of design patterns is considered as a benchmark of software quality in terms of reducing the number of software faults. However, the quantification of the information about the hinder design issues such as the number of roles, type of design pattern, and their association with anti-pattern classes is still required. The authors propose a new methodology to evaluate the impact of certain design issues on the software quality in terms of quantification of fault density. Firstly, they mine the required information about the classes of each system under study. Secondly, they describe taxonomy to group the classes. Subsequently, they used statistical techniques to formulate and benchmark the results. They include the analysis of four open source projects with six design patterns and six anti-patterns in the case study. The main consequences are (i) the pattern participant classes are less dense in faults, (ii) the classes involved in the structural association between design patterns and anti-patterns are denser in faults, (iii) the pattern participant classes with multi-role and anti-pattern smell association is denser in faults as compared to others. The significant difference between fault density distributions of groups of classes is still unclear and required further empirical investigation.

Citation Format(s)

Methodology for the quantification of the effect of patterns and anti-patterns association on the software quality. / Hussain, Shahid; Keung, Jacky; Sohail, Muhammad Khalid; Khan, Arif Ali; Ahmad, Ghufran; Mufti, Muhammad Rafiq; Khatak, Hasan Ali.

In: IET Software, Vol. 13, No. 5, 10.2019, p. 414-422.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal