Co-changing code volume prediction through association rule mining and linear regression model

Lee, Shin-Jie; Lo, Li Hsiang; Chen, Yu Cheng; Shen, Shi-Min

doi:10.1016/j.eswa.2015.09.023

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Cited by 10 publications

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“…However, the evaluated results were based on several assumptions. Lee et al (2016) worked on co-change, i.e. if one class is changed it affects the other classes also.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Behavioral Dependency for Effective Computing in Software

Bura

Choudhary

2021

International Journal of System Dynamics Applications

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Software plays an important role in effective computing and communication of any services. It become crucial to identify some critical parts of the software that can lead to enhanced computing and increases efficiency of the software. Dependency plays a significant role in finding relationship amongst classes and predicting change prone classes. This paper aims to enhance Behavioral Dependency by defining 6 types of dependencies amongst classes. These are (i) direct behavioral dependency (ii) indirect behavioral dependency (iii) internal behavioral dependency (iv) external behavioral dependency (v) indirect internal behavioral dependency and (vi) Indirect External Behavioral Dependency. Evaluating these dependencies, gives accurate results for the prediction of change prone classes. Further, paper compares proposed approach with existing methods.

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“…However, the evaluated results were based on several assumptions. Lee et al (2016) worked on co-change, i.e. if one class is changed it affects the other classes also.…”

Section: Related Workmentioning

confidence: 99%