Important issues in software fault prediction: a road map

Golnoush Abaei, Ali Selamat

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

1 Citation (Scopus)


Quality assurance tasks such as testing, verification and validation, fault tolerance, and fault prediction play a major role in software engineering activities. Fault prediction approaches are used when a software company needs to deliver a finished product while it has limited time and budget for testing it. In such cases, identifying and testing parts of the system that are more defect prone is reasonable. In fact, prediction models are mainly used for improving software quality and exploiting available resources. Software fault prediction is studied in this chapter based on different criteria that matters in this research field. Usually, there are certain issues that need to be taken care of such as different machine-learning techniques, artificial intelligence classifiers, variety of software metrics, distinctive performance evaluation metrics, and some statistical analysis. In this chapter, the authors present a roadmap for those researchers who are interested in working in this area. They illustrate problems along with objectives related to each mentioned criterion, which could assist researchers to build the finest software fault prediction model.

Original languageEnglish
Title of host publicationHandbook of Research on Emerging Advancements and Technologies in Software Engineering
PublisherIGI Global
Number of pages30
ISBN (Electronic)9781466660281
ISBN (Print)9781466660274
Publication statusPublished - 30 Apr 2014
Externally publishedYes

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