Validation of the coupling dependency metric as a predictor of run-time failures and maintenance measures

Binkley, Aaron B.; Schach, Stephen R.

doi:10.1109/icse.1998.671604

Cited by 77 publications

(58 citation statements)

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“…bytes.high = j->m_DAAShadowRegs.COP_REGS.COP.THFilterCoeff_1 [4]; bytes.low = j->m_DAAShadowRegs.COP_REGS.COP.THFilterCoeff_1 [3]; if (!daa_load(&bytes, j)) return 0;…”

Section: Discussionmentioning

confidence: 99%

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High-MCC Functions in the Linux Kernel

2013

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Abstract-McCabe's Cyclomatic Complexity (MCC) is a widely used metric for the complexity of control flow. Common usage decrees that functions should not have an MCC above 50, and preferably much less. However, the Linux kernel includes more than 800 functions with MCC values above 50, and over the years 369 functions have had an MCC of 100 or more. Moreover, some of these functions undergo extensive evolution, indicating that developers are successful in coping with the supposed high complexity. We attempt to explain this by analyzing the structure of such functions and showing that in many cases they are in fact well-structured. At the same time, we observe cases where developers indeed refactor the code in order to reduce complexity. These observations highlight the need to define more holistic notions of complexity, rather than using simple syntactic code metrics.

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“…bytes.high = j->m_DAAShadowRegs.COP_REGS.COP.THFilterCoeff_1 [4]; bytes.low = j->m_DAAShadowRegs.COP_REGS.COP.THFilterCoeff_1 [3]; if (!daa_load(&bytes, j)) return 0;…”

Section: Discussionmentioning

confidence: 99%

“…Complex code is hard to write correctly and hard to maintain, leading to more faults [12], [3]. As a result, significant research effort has been expended on defining code complexity metrics and on methods to combine them into effective predictors of code quality [20], [5], [21].…”

Section: Introductionmentioning

confidence: 99%

High-MCC Functions in the Linux Kernel

2013

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“…Generally, accepted rules state that modules should have high cohesion and low coupling [1], [2], [3]. In fact, several empirical studies provided evidence that high levels of coupling and/or lack of cohesion are generally associated with lower productivity, greater rework, and more significant design efforts by developers (e.g., [4], [5]). In addition, classes with low cohesion and/or high coupling have been shown to correlate with high defect rates [6].…”

Section: Introductionmentioning

confidence: 99%

Methodbook: Recommending Move Method Refactorings via Relational Topic Models

Bavota

Oliveto

Gethers

et al. 2014

IIEEE Trans. Software Eng.

130

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Abstract-During software maintenance and evolution the internal structure of the software system undergoes continuous changes. These modifications drift the source code away from its original design, thus deteriorating its quality, including cohesion and coupling of classes. Several refactoring methods have been proposed to overcome this problem. In this paper we propose a novel technique to identify Move Method refactoring opportunities and remove the Feature Envy bad smell from source code. Our approach, coined as Methodbook, is based on Relational Topic Models (RTM), a probabilistic technique for representing and modeling topics, documents (in our case methods) and known relationships among these. Methodbook uses RTM to analyze both structural and textual information gleaned from software to better support move method refactoring. We evaluated Methodbook in two case studies. The first study has been executed on six software systems to analyze if the move method operations suggested by Methodbook help to improve the design quality of the systems as captured by quality metrics. The second study has been conducted with eighty developers that evaluated the refactoring recommendations produced by Methodbook. The achieved results indicate that Methodbook provides accurate and meaningful recommendations for move method refactoring operations.

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“…Binkley and Schach [6] propose a Coupling Dependency Metric which mea sures change and fault-proneness at a finer grain compared to other metrics that restrict their scope to the class level. Briand et al [7] introduce a software metric suite which accounts for class-attribute, class-method, and method-method rela tionships and show that there is correlation between these coupling measurements with fault-proneness.…”

Section: Established Coupling Metricsmentioning

confidence: 99%

“…There have been several proposals [6,7,12,17,28,27,19,9] and validations [4,21,39,40,34,20] in order to provide accurate predictions of class quality. As of now there is no oracle, however the seminal metrics have been tried and true compared to other more recent additions.…”

Section: Chaptermentioning

confidence: 99%

A Coupling-Complexity Metric Suite for Predicting Software Quality

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Validation of the coupling dependency metric as a predictor of run-time failures and maintenance measures

Cited by 77 publications

References 1 publication

High-MCC Functions in the Linux Kernel

High-MCC Functions in the Linux Kernel

Methodbook: Recommending Move Method Refactorings via Relational Topic Models

A Coupling-Complexity Metric Suite for Predicting Software Quality

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