Software Fault-Proneness Analysis based on Composite Developer-Module Networks

Existing software fault-proneness analysis and prediction models can be categorized into software metrics and visualized approaches. However, the studies of the software metrics solely rely on the quantified data, while the latter fails to reflect the human aspect, which is proven to be a main cause...

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Bibliographic Details
Published in:IEEE access 2021, Vol.9, p.155314-155334
Main Authors: Lee, Shou-Yu, Wong, W. Eric, Li, Yihao, Chu, William Cheng-Chung
Format: Article
Language:English
Subjects:
Analytical models
Computer bugs
developer-module networks
fault-proneness prediction
Graphs
human aspects
Measurement
Modules
Networks
Prediction models
Predictive models
Software
Software development
Software metrics
Software networks
Training
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Summary:Existing software fault-proneness analysis and prediction models can be categorized into software metrics and visualized approaches. However, the studies of the software metrics solely rely on the quantified data, while the latter fails to reflect the human aspect, which is proven to be a main cause of many failures in various domains. In this paper, we proposed a new analysis model with an improved software network called Composite Developer-Module Network. The network is composed of the linkage of both developers to software modules and software modules to modules to reflect the characteristics and interaction between developers. After the networks of the research objects are built, several different sub-graphs in the networks are derived from analyzing the structures of the sub-graphs that are more fault-prone and further determine whether the software development is in a bad structure, thus predicting the fault-proneness. Our research shows that the different sub-structures are not only a factor in fault-proneness, but also that the complexity of the sub-structure can affect the production of bugs.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3128438