Exploring the relationships between design measures and software quality in object-oriented systems

By Lionel Claude Briand, Jürgen Wüst, John William Daly, D. Victor Porter. Journal of Systems and Software, 2000

640 citations recorded by the source corpus.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/cfedc22796516742de3437b50505311bd6b19e90

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Citations in the corpus

Empirical validation of object-oriented metrics on open source software for fault prediction (2005, result): “[3] [4], [5] for this purpose and similar results were also”
Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities (2011, methodology): “[7] also used OO design metrics to predict defects and their logistic regression model classified fault-prone classes at over 80% of precision and found over 90% of faulty classes.”
The prediction of faulty classes using object-oriented design metrics (2001, methodology): “Briand et al., 1998a; Briand et al., 1998b; Briand et al., 2000; El-Emam et al., 2000; Tang et al., 1999).”
Software fault prediction metrics: A systematic literature review (2013, methodology): “The performance difference be-tween modeling techniques appears to be moderate [38,30,60] and the choice of a modeling technique seems to have lesser impact on classiﬁcation accuracy of a model than the choice of a metrics set [60].”
Application of neural networks for software quality prediction using object-oriented metrics (2003, background): “Briand et al. (2000) performed an empirical study on the relationships between existing object-oriented coupling, cohesion, and inheritance measures and the probability of fault detection in system classes during testing.”
The Qualitas Corpus: A Curated Collection of Java Code for Empirical Studies (2010, background): “Another example of research infrastructure is the New Zealand Digital Library project, which aims is to develop the technology for the creation of digital libraries and make it available publicly so that others can use it [19].”
Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults (2006, methodology): “As stated in [ 9 ], this is due to suppressor relationships between the variables, which are commonly observed in multivariate regression analysis.”