A Systematic Review of Ensemble Techniques for Software Defect and Change Prediction

Khanna, Megha

doi:10.37190/e-Inf220105

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Tytuł artykułu

A Systematic Review of Ensemble Techniques for Software Defect and Change Prediction

Autorzy

Khanna Megha

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DOI

10.37190/e-Inf220105

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Background: The use of ensemble techniques have steadily gained popularity in several software quality assurance activities. These aggregated classifiers have proven to be superior than their constituent base models. Though ensemble techniques have been widely used in key areas such as Software Defect Prediction (SDP) and Software Change Prediction (SCP), the current state-of-the-art concerning the use of these techniques needs scrutinization. Aim: The study aims to assess, evaluate and uncover possible research gaps with respect to the use of ensemble techniques in SDP and SCP. Method: This study conducts an extensive literature review of 77 primary studies on the basis of the category, application, rules of formulation, performance, and possible threats of the proposed/utilized ensemble techniques. Results: Ensemble techniques were primarily categorized on the basis of similarity, aggregation, relationship, diversity, and dependency of their base models. They were also found effective in several applications such as their use as a learning algorithm for developing SDP/SCP models and for addressing the class imbalance issue. Conclusion: The results of the review ascertain the need of more studies to propose, assess, validate, and compare various categories of ensemble techniques for diverse applications in SDP/SCP such as transfer learning and online learning.

Słowa kluczowe

ensemble learning software change prediction software defect prediction software quality systematic review

Wydawca

Oficyna Wydawnicza Politechniki Wrocławskiej

Czasopismo

e-Informatica Software Engineering Journal

Rocznik

2022

Tom

Vol. 16, nr 1

Strony

art. no. 220105

Opis fizyczny

Bibliogr. 120 poz., rys., tab.

Twórcy

autor

Khanna Megha

meghakhanna86@gmail.com

Department of Computer Science, Sri Guru Gobind Singh College of Commerce, University of Delhi

Bibliografia

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