A Hierarchical Model for Object-Oriented Design Quality Assessment

By J. Bansiya, C. Davis. IEEE Trans. Software Eng., 2002

1,103 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Industrial and Manufacturing Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/37a1b6b861d042dbacf6c7eaa2927d3dfed2043c

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Citations in the corpus

Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems (2008, background): “…the literature (see Section 2) as software cohesion metrics proved to be useful in different tasks [24], including the assessment of design quality [5], [13], productivity, design, and reuse effort [18], prediction of software quality, fault prediction [30], [39], [69], modularization of software…”
Identification of Move Method Refactoring Opportunities (2009, background): “The entity set of a method m contains the following entities: . the directly accessed attributes that belong to the same class with m; . the accessed attributes that belong to other classes of the system; . the directly accessed methods that belong to the same class with m; . the accessed methods…”
Towards identifying software project clusters with regard to defect prediction (2010, methodology): “The metrics suite suggested by Bansiy and Davis [1]:”
A systematic review of software fault prediction studies (2009, methodology): “QMOOD (quality metrics for object-oriented design) was proposed by Bansiya and Davis (2002). However, CK metrics suite is much more popular than other suites and they are mostly used if class-level metrics are applied.”
Software fault prediction metrics: A systematic literature review (2013, methodology): “…frequently used ones are those of Abreu and Carapuca (MOOD metrics suite) [1,51], Bansiya and Davis (QMOOD metrics suite) [3], Bieman and Kang [5], Briand et al. [70], Cart-wright and Shepperd [74], Chidamber and Kemerer (CK metrics suite) [12,13], Etzkorn et al. [17], Halstead [24],…”
Comparing and experimenting machine learning techniques for code smell detection (2015, methodology): “We chose well-known metrics that are widely used in the literature (Bansiya and Davis, 2002; Dubey et al., 2012; Chidamber and Kemerer, 1994; Lorenz and Kidd, 1994; Aggarwal et al, 2006).”
Empirical Validation of Three Software Metrics Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Processes (2007, background): “M ANY OO metrics have been developed by researchers to help assess design quality [1], [2], [3], [4], [5].”