Classification framework for faulty-software using enhanced exploratory whale optimizer-based feature selection scheme and random forest ensemble learning

Software Fault Prediction (SFP) is an important process to detect the faulty components of the software to detect faulty classes or faulty modules early in the software development life cycle. In this paper, a machine learning framework is proposed for SFP. Initially, pre-processing and re-sampling...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Abu Doush, Iyad (author)
مؤلفون آخرون:	Al-Betar, Mohammed Azmi (author), AAwadallah, Mohammed (author), Mafarja, Majdi (author), Thaher, Thaer (author), Too, Jingwei (author), Turabieh, Hamza (author)
منشور في:	2023
الوصول للمادة أونلاين:	http://hdl.handle.net/11675/10924 http://www.scopus.com/inward/record.url?scp=85147747850&partnerID=8YFLogxK
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Classification framework for faulty-software using enhanced exploratory whale optimizer-based feature selection scheme and random forest ensemble learning

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