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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Autores principales:	Shou-Yu Lee, W. Eric Wong, Yihao Li, William Cheng-Chung Chu
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Software networks developer-module networks fault-proneness prediction human aspects software metrics Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/eb773661955a48bea35ef0b16adc77ad
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spelling	oai:doaj.org-article:eb773661955a48bea35ef0b16adc77ad2021-11-26T00:00:26ZSoftware Fault-Proneness Analysis based on Composite Developer-Module Networks2169-353610.1109/ACCESS.2021.3128438https://doaj.org/article/eb773661955a48bea35ef0b16adc77ad2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9615229/https://doaj.org/toc/2169-3536Existing 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.Shou-Yu LeeW. Eric WongYihao LiWilliam Cheng-Chung ChuIEEEarticleSoftware networksdeveloper-module networksfault-proneness predictionhuman aspectssoftware metricsElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 155314-155334 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Software networks developer-module networks fault-proneness prediction human aspects software metrics Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Software networks developer-module networks fault-proneness prediction human aspects software metrics Electrical engineering. Electronics. Nuclear engineering TK1-9971 Shou-Yu Lee W. Eric Wong Yihao Li William Cheng-Chung Chu Software Fault-Proneness Analysis based on Composite Developer-Module Networks
description	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.
format	article
author	Shou-Yu Lee W. Eric Wong Yihao Li William Cheng-Chung Chu
author_facet	Shou-Yu Lee W. Eric Wong Yihao Li William Cheng-Chung Chu
author_sort	Shou-Yu Lee
title	Software Fault-Proneness Analysis based on Composite Developer-Module Networks
title_short	Software Fault-Proneness Analysis based on Composite Developer-Module Networks
title_full	Software Fault-Proneness Analysis based on Composite Developer-Module Networks
title_fullStr	Software Fault-Proneness Analysis based on Composite Developer-Module Networks
title_full_unstemmed	Software Fault-Proneness Analysis based on Composite Developer-Module Networks
title_sort	software fault-proneness analysis based on composite developer-module networks
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/eb773661955a48bea35ef0b16adc77ad
work_keys_str_mv	AT shouyulee softwarefaultpronenessanalysisbasedoncompositedevelopermodulenetworks AT wericwong softwarefaultpronenessanalysisbasedoncompositedevelopermodulenetworks AT yihaoli softwarefaultpronenessanalysisbasedoncompositedevelopermodulenetworks AT williamchengchungchu softwarefaultpronenessanalysisbasedoncompositedevelopermodulenetworks
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Software Fault-Proneness Analysis based on Composite Developer-Module Networks

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