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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Book
Agile Software Development
TL;DR: Agile Software Development as discussed by the authors compares software development to a game, where team members play the game knowing that the ultimate goal is to win, always remembering what they have learned along the way, and always keeping in mind that they will never play the same way twice.
Journal ArticleDOI
Lessons from applying the systematic literature review process within the software engineering domain
TL;DR: In this article, the authors report experiences with applying one such approach, the practice of systematic literature review, to the published studies relevant to topics within the software engineering domain, and some lessons about the applicability of this practice to software engineering are extracted.
Journal ArticleDOI
A validation of object-oriented design metrics as quality indicators
TL;DR: Several of Chidamber and Kemerer's OO metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle and are better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.
Book
Agile Software Development, Principles, Patterns, and Practices
TL;DR: This comprehensive, pragmatic tutorial on Agile Development and eXtreme programming, written by one of the founding father of Agile development, teaches software developers and project managers how to get projects done on time, and on budget using the power ofAgile Development.