A Measurement Tool for Object Oriented Software and Measurement Experiments with It

Li, Xinke; Liu, Zongtian; Biao, Pan; Dahong, Xing

doi:10.1007/3-540-44704-0_4

Cited by 9 publications

(9 citation statements)

References 7 publications

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“…Other examples of such values can be found in [7][8][9]20]. We selected values from [2] for comparison purposes because measurements there were taken on relatively large amounts of CCC classes, which is similar to our study, and the same types of data were collected as in our study.…”

Section: Quality Aspectsmentioning

confidence: 97%

“…The mean coupling values reported in [2,[7][8][9]20] are usually between 5 and 7. The distribution of coupling values in the project classes is presented in Fig.…”

Section: Quality Aspectsmentioning

confidence: 98%

“…We selected values from [2] for comparison purposes because measurements there were taken on relatively large amounts of CCC classes, which is similar to our study, and the same types of data were collected as in our study. Values from other studies mentioned [7][8][9]20] will be used when discussing the findings.…”

Section: Quality Aspectsmentioning

confidence: 99%

See 2 more Smart Citations

Software development productivity on a new platform: an industrial case study

Tomaszewski

Lundberg

2005

Information and Software Technology

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Section: Quality Aspectsmentioning

confidence: 97%

“…The mean coupling values reported in [2,[7][8][9]20] are usually between 5 and 7. The distribution of coupling values in the project classes is presented in Fig.…”

Section: Quality Aspectsmentioning

confidence: 98%

See 1 more Smart Citation

Software development productivity on a new platform: an industrial case study

Tomaszewski

Lundberg

2005

Information and Software Technology

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“…[18] RLCOM [15] "Ratio of number of non-similar method pairs to total number of method pairs in the class".…”

Section: Traditional Coupling and Cohesion Metricsmentioning

confidence: 99%

“…[15] These cohesion metrics considered method similarity as an intransitive relation. LCOM3 and TCC incorporate indirect relationships between methods.…”

Section: Traditional Coupling and Cohesion Metricsmentioning

confidence: 99%

A Design of Cohesion and Coupling Metrics for Component based Software Systems

Rana¹,

Singh²

2016

IJCA

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Component based software engineering (CBSE) is based on the concept of reusability. CBSE is upcoming paradigm where emphasis is laid on reuse of existing component and rebuilds a new component. Software metrics are used to check the complexity of software. Many software metrics have been proposed for CBS to measure various attributes like complexity, cohesion, coupling etc. Many different cohesion and coupling metrics have been developed. For quality software the cohesion should be high and coupling should be low. The aim of this paper is to develop adequate coupling, cohesion and interface metrics. Graph notation and concept of weights have been used to illustrate proposed metrics and evaluate the results accordingly.

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Cohesion measurements between variables and methods using component-based software systems

Shipra

2024

Int J Syst Assur Eng Manag

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The practice of leveraging previously created software components to progress new software is identified as component-based software engineering (CBSE). Good software engineering design is the foundation of CBSE principles. The black box approach that underpins CBSE hides the execution of components in nature, and the components communicate with one another using strictly delineated interfaces. Component platforms are shared, which lowers the price of creation. To ascertain a system's complexity, various software metrics are employed. For superiority in software intricacy, coupling would be minimal, and cohesiveness must be high. It is predetermined that coupling should be low and cohesion should be increased for refinement in software complexity. We are identifying the combination of different software systems and improving the methods for doing so with our approach. Proposed: Cohm (cohesion of methods) and Cohv (cohesion of variables) are two cohesion metrics that have been proposed. The cohesiveness metrics in this study have been analytically and empirically evaluated, and a comparison has been made between them. Additionally, an effort was made to give the outcomes of an empirical estimation based on the case study. The T-test is used to determine the consequences of the metrics, and Python is used to validate the metrics. Python or R programming and the Matlab tool are used to determine the relationship between various variables and metrics. Findings: The consequence of the current investigation is very encouraging and might be used to estimate the involvedness of the parts. The proportional analysis of the proposed metrics and various cohesion metrics reveals that the suggested metrics are more cohesive than the present metrics, increasing the likelihood that they can be reused when creating new applications.

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A Measurement Tool for Object Oriented Software and Measurement Experiments with It

Cited by 9 publications

References 7 publications

Software development productivity on a new platform: an industrial case study

Software development productivity on a new platform: an industrial case study

A Design of Cohesion and Coupling Metrics for Component based Software Systems

Cohesion measurements between variables and methods using component-based software systems

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