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Kemerer, Chris F.; Slaughter, Sandra A.

doi:10.1023/a:1009741031615

Cited by 14 publications

(2 citation statements)

References 13 publications

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“…First, design patterns are commonly used in both open-source and proprietary software and are seen as an exemplar of sound software engineering practice; knowledge of their change trends and fault-proneness is valuable information for the developer and could also inform future maintenance activity, resource prioritization, and QA planning. While we agree that in theory use of design patterns should be condoned, we see the study presented as an exploration of actual design pattern usage and evolution in an industrial setting (Kemerer & Slaughter, 1999); the purpose of any empirical software study is to support (or refute) hypoth-eses (possibly using metrics) about the way we develop and use software in all its aspects (Basili, Briand, & Melo, 1996;Chidamber & Kemerer, 1994). Second, detailed studies of fault data in large scale commercial software systems are rare and this study reports, not only on fault occurrence, but also documents corrective maintenance measurements, in terms of lines of code, which may add valuable information for the prediction of future maintenance effort.…”

Section: Motivation and Related Workmentioning

confidence: 66%

Faults and Their Relationship to Implemented Patterns, Coupling and Cohesion in Commercial C# Software

Counsell

Gatrell

2012

International Journal of Information System Modeling and Design

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This paper documents a study of fault proneness in commercial, proprietary software and attempts to determine whether a relationship exists between class faults and the design context of a class, namely the coupling and cohesion of a class, and whether the class is a participant of common design patterns. The authors studied a commercial software system for a 24 month period and identified design pattern participants by inspecting the design documentation and source code; coupling and cohesion metrics were measured by inspecting the source code with a tool; we also extracted fault data for the same period to determine whether a relationship existed between the design context and the fault propensity of a class. Results showed that design pattern participant classes were marginally more fault-prone than non-participant classes, The Adaptor, Method and Singleton patterns were found to be the most fault-prone of thirteen patterns explored. Coupling was found to have a significant relationship with the fault proneness of classes in the system; efferent coupling was a stronger indicator of fault propensity than afferent coupling. Cohesion, when measured using the LCOM(HS) metric, was not found to have a strong relationship with fault proneness.

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Section: Motivation and Related Workmentioning

confidence: 66%

Faults and Their Relationship to Implemented Patterns, Coupling and Cohesion in Commercial C# Software

Counsell

Gatrell

2012

International Journal of Information System Modeling and Design

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“…Finally, this study contributes to an empirical body of knowledge on coupling and longitudinal analysis of which more studies have been urged (Kemerer et al, 1999a(Kemerer et al, , 1999b. The basis of the research presented in this paper is that of a previous study by the same authors (Mubarak et al, 2010) in a line of research on coupling.…”

Section: Motivation and Related Workmentioning

confidence: 79%

A Longitudinal Study of Fan-In and Fan-Out Coupling in Open-Source Systems

Counsell

Mubarak

Hierons

2011

International Journal of Information System Modeling and Design

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Excessive coupling between object-oriented classes is widely acknowledged as a maintenance problem that can result in a higher propensity for faults in systems and a ‘stored up’ future problem. This paper explores the relationship between ‘fan-in’ and ‘fan-out’ coupling metrics over multiple versions of open-source software. More specifically, the relationship between the two metrics is explored to determine patterns of growth in each over the course of time. The JHawk tool was used to extract the two metrics from five open-source systems. Results show a wide range of traits in the classes to explain both high and low levels of fan-in and fan-out. Evidence was also found of certain ‘key’ classes (with both high fan-in and fan-out) and ‘client’ and ‘server’-type classes with high fan-out and fan-in, respectively. This paper provides an explanation of the composition and existence of such classes as well as for disproportionate increases in each of the two metrics over time. Finally, it was found that high fan-in class values tended to be associated with small classes; classes with high fan-out on the other hand tended to be relatively large classes.

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