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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Proceedings ArticleDOI
An empirical study on predicting defect numbers
Mingming Chen,Yutao Ma +1 more
TL;DR: The experiments on six open-source software projects in PROMISE repository show that the prediction model built with Decision Tree Regression seems to be the best estimator in both of the scenarios, and that for all the prediction models, the results yielded in the cross-project scenario can be comparable to (or sometimes better than) those in the within- project scenario when choosing suitable training data.
Journal ArticleDOI
Deriving thresholds of software metrics to predict faults on open source software
Ömer Faruk Arar,Kürşat Ayan +1 more
TL;DR: The objective of this paper is to empirically examine whether or not there are effective threshold values for source code metrics to derive generalized thresholds that can be used in different software systems.
Journal ArticleDOI
Iterative software fault prediction with a hybrid approach
Ezgi Erturk,Ebru Akcapinar Sezer +1 more
TL;DR: The results indicate that the iterative software fault prediction is successful and can be transformed into a tool that can automatically locate fault-prone modules due to its well-organized information flow.
Journal ArticleDOI
A study of subgroup discovery approaches for defect prediction
TL;DR: This paper represents an engineering approach to defect prediction, i.e., an approach which is useful in practice, easily understandable and can be applied by practitioners and deliver a practical (or engineering) approach rather than a highly accurate result.
Proceedings ArticleDOI
Empirical Evaluation of Cross-Release Effort-Aware Defect Prediction Models
TL;DR: Cross-release evaluation of 11 fault density prediction models using data sets collected from 2 releases of 25 open source software projects with an effort-aware performance measure known as Norm(Popt) produced an overall average performance of more than 50% across all the selected models clearly indicating the importance of considering testing efforts in building fault-prone prediction models.
References
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TL;DR: This research addresses the needs for software measures in object-orientation design through the development and implementation of a new suite of metrics for OO design, and suggests ways in which managers may use these metrics for process improvement.
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A complexity measure
TL;DR: In this paper, a graph-theoretic complexity measure for managing and controlling program complexity is presented. But the complexity is independent of physical size, and complexity depends only on the decision structure of a program.
Journal ArticleDOI
A Complexity Measure
TL;DR: Several properties of the graph-theoretic complexity are proved which show, for example, that complexity is independent of physical size and complexity depends only on the decision structure of a program.