Error-Type—A Novel Set of Software Metrics for Software Fault Prediction

Abstract

In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing the characteristics of the buggy source codes from the past and predict the present ones based on the same characteristics using statistical or machine learning models. Many studies have been conducted to predict the fault proneness of software systems. However, most of them provide either inadequate or insufficient information and thus make the fault prediction task difficult. In this paper, we present a novel set of software metrics called Error-type software metrics, which provides prediction models with information about patterns of different types of Java runtime error. Particular, in this study, the ESM values consist of information of three common Java runtime errors which are Index Out Of Bounds Exception, Null Pointer Exception, and Class Cast Exception. Also, we proposed a methodology for modelling, extracting, and evaluating error patterns from software modules using Stream X-Machine (a formal modelling method) and machine learning techniques. The experimental results showed that the proposed Error-type software metrics could significantly improve the performances of machine learning models in fault-proneness prediction.

Insights of effectivity analysis of learning-based approaches towards software defect prediction

“…This form of network integrates developer, module dependency, and contribution of developer in order to investigated their joint influence towards software quality. The work carried out by Phung et al [59] have presented a unique scheme where software metric is formulated for error representation associated with java-based runtime. A formal modelling method is used along with machine learning in order to evaluate the patterns.…”

Comprehensive Evaluation of Static Analysis Tools for Their Performance in Finding Vulnerabilities in Java Code

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“…The presence of programming errors reduces the quality of the software and increases the cost of development life cycle [3]. Poor program quality is a leading cause of security vulnerabilities.…”