Journal ArticleDOI
Software fault prediction metrics
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TLDR
Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics and seem to be better at predicting post-release faults than any static code metrics.Abstract:
ContextSoftware metrics may be used in fault prediction models to improve software quality by predicting fault location. ObjectiveThis paper aims to identify software metrics and to assess their applicability in software fault prediction. We investigated the influence of context on metrics' selection and performance. MethodThis systematic literature review includes 106 papers published between 1991 and 2011. The selected papers are classified according to metrics and context properties. ResultsObject-oriented metrics (49%) were used nearly twice as often compared to traditional source code metrics (27%) or process metrics (24%). Chidamber and Kemerer's (CK) object-oriented metrics were most frequently used. According to the selected studies there are significant differences between the metrics used in fault prediction performance. Object-oriented and process metrics have been reported to be more successful in finding faults compared to traditional size and complexity metrics. Process metrics seem to be better at predicting post-release faults compared to any static code metrics. ConclusionMore studies should be performed on large industrial software systems to find metrics more relevant for the industry and to answer the question as to which metrics should be used in a given context.read more
Citations
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Journal ArticleDOI
A systematic review of machine learning techniques for software fault prediction
TL;DR: The machine learning techniques have the ability for predicting software fault proneness and can be used by software practitioners and researchers, however, the application of theMachine learning techniques in software fault prediction is still limited and more number of studies should be carried out in order to obtain well formed and generalizable results.
Journal ArticleDOI
An empirical study on software defect prediction with a simplified metric set
TL;DR: The experimental results indicate that the choice of training data for defect prediction should depend on the specific requirement of accuracy and the minimum metric subset can be identified to facilitate the procedure of general defect prediction with acceptable loss of prediction precision in practice.
Journal ArticleDOI
A Systematic Literature Review and Meta-Analysis on Cross Project Defect Prediction
TL;DR: CPDP is still a challenge and requires more research before trustworthy applications can take place and this work synthesises literature to understand the state-of-the-art in CPDP with respect to metrics, models, data approaches, datasets and associated performances.
Journal ArticleDOI
A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction
TL;DR: Imbalanced learning should only be considered for moderate or highly imbalanced SDP data sets and the appropriate combination of imbalanced method and classifier needs to be carefully chosen to ameliorate the imbalanced learning problem for SDP.
References
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Journal ArticleDOI
Empirical evaluation of reuse sensitiveness of complexity metrics
TL;DR: A revision of the Chidamber and Kemerer’s metrics which can be applied to software which had been constructed by reusing software components is proposed and an analysis of data collected from the development of an object-oriented software using a GUI framework is given.
Book ChapterDOI
Empirical Investigation of Metrics for Fault Prediction on Object-Oriented Software
Bindu Goel,Yogesh Singh +1 more
TL;DR: In the present study, the relationship between OO metrics and the detection of the faults in the object-oriented software is investigated.
Proceedings ArticleDOI
Evolution and Search Based Metrics to Improve Defects Prediction
TL;DR: Search based techniques are used to define software metrics accounting for the role a class plays in the class diagram and for its evolution over time and preliminary results show that the new metrics favorably compare with traditional object oriented metrics.
Proceedings ArticleDOI
An empirical approach for software fault prediction
TL;DR: The results show that combination metric model is found to be the best prediction model among three and this approach is compared with others in the literature and is proved to be more accurate.
Proceedings ArticleDOI
Ineffectiveness of Use of Software Science Metrics as Predictors of Defects in Object Oriented Software
TL;DR: The results show that the removal of SSM from the set of independent variables does not significantly affect the classification of modules as defect prone and the prediction of number of defects, highlighting the ineffectiveness of use ofSSM in defect prediction in OO software.