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

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dc.contributor.author Hussain, Shahid
dc.contributor.author Sohail, Muhammad Khalid
dc.contributor.author Ahmad, Ghufran
dc.contributor.author Mufti, Muhammad Rafiq
dc.contributor.author Khatak, Hasan Ali
dc.date.accessioned 2019-11-14T06:45:00Z
dc.date.available 2019-11-14T06:45:00Z
dc.date.issued 2019-10-10
dc.identifier.issn 1751-8814
dc.identifier.uri http://142.54.178.187:9060/xmlui/handle/123456789/1222
dc.description.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 en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject COMSATS en_US
dc.subject software quality en_US
dc.subject software fault tolerance en_US
dc.subject public domain software en_US
dc.title Methodology for the quantification of the effect of patterns and anti-patterns association on the software quality en_US
dc.type Article en_US


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