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Journals / Celal Bayar Üniversitesi Fen Bilimleri Dergisi / 2018 / Cilt: 14 - Sayı: 3

Software Fault Prediction in Object Oriented Software Systems Using Ensemble Classifiers

Emin BORANDAĞ
Fatih YÜCALAR
Kamil AKARSU
Pages
297–302
Publication Date
2018-09-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this study, by using machine learning algorithms and software metrics; software error estimation has been carried out with a developed software

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The main aim of software projects is developing software programs to meet functional and non-functional requirements within the project budget and at a particular time.
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Key Findings & Data:When software is tested, it is very significant that software errors are found in the early phases.
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Conclusion & Impact:In this study, by using machine learning algorithms and software metrics; software error estimation has been carried out with a developed software
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Data Mining · Software Fault Prediction · Rotation Forest Algorithm

Abstract

The main aim of software projects is developing software programs to meet functional and non-functional requirements within the project budget and at a particular time. The greatest challenge in reaching this goal is the software errors that were found in the software projects. The most basic technique that is used to solve software errors is testing the software programs according to the methods in the literature. These methods are the software tests that are basically conducted by software developers, although they have different methods of verification and validation according to their size, experience, techniques or tools they use. When software is tested, it is very significant that software errors are found in the early phases. Software error estimation is a proven method of effectiveness and validity that increases the quality of software and reduces the cost of software development. In this study, by using machine learning algorithms and software metrics; software error estimation has been carried out with a developed software

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Cite This Article

BORANDAĞ, E., YÜCALAR, F., AKARSU, K. (2018). Software Fault Prediction in Object Oriented Software Systems Using Ensemble Classifiers. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, Cilt: 14 - Sayı: 3, 297–302. https://ajindex.com/articles/107071

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