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Title:
Analyzing and predicting software integration bugs using network analysis on requirements dependency network
Author: Wang, Junjie (1) ; Wang, Qing (1)
Corresponding Author: Wang, Junjie
Source: Requirements Engineering
Issued Date: 2014
Indexed Type: EI
Department: (1) Laboratory for Internet Software Technologies, Institute of Software Chinese Academy of Sciences, Beijing, China; (2) University of Chinese Academy of Sciences, Beijing, China; (3) State Key Laboratory of Computer Science, Institute of Software Chinese Academy of Sciences, Beijing, China
Abstract: Complexity, cohesion and coupling have been recognized as prominent indicators of software quality. One characterization of software complexity is the existence of dependency relationships. Moreover, the degree of dependency reflects the cohesion and coupling between software elements. Dependencies in the design and implementation phase have been proven to be important predictors of software bugs. We empirically investigated how requirements dependencies correlate with and predict software integration bugs, which can provide early estimates regarding software quality and thus facilitate decision making early in the software lifecycle. We conducted network analysis on the requirements dependency networks of three commercial software projects. Significant correlation is observed between most of our network measures and the number of bugs. Furthermore, many network measures demonstrate significantly greater values for higher severity (or a higher fixing workload). Afterward, we built bug prediction models using these network measures and found that bugs can be predicted with high accuracy and sensitivity, even in cross-project and cross-company contexts. We further identified the dependency type that contributes most to bug correlation, as well as the network measures that contribute more to bug prediction. These observations show that the requirements dependency network can be used as an early indicator and predictor of software integration bugs.
English Abstract: Complexity, cohesion and coupling have been recognized as prominent indicators of software quality. One characterization of software complexity is the existence of dependency relationships. Moreover, the degree of dependency reflects the cohesion and coupling between software elements. Dependencies in the design and implementation phase have been proven to be important predictors of software bugs. We empirically investigated how requirements dependencies correlate with and predict software integration bugs, which can provide early estimates regarding software quality and thus facilitate decision making early in the software lifecycle. We conducted network analysis on the requirements dependency networks of three commercial software projects. Significant correlation is observed between most of our network measures and the number of bugs. Furthermore, many network measures demonstrate significantly greater values for higher severity (or a higher fixing workload). Afterward, we built bug prediction models using these network measures and found that bugs can be predicted with high accuracy and sensitivity, even in cross-project and cross-company contexts. We further identified the dependency type that contributes most to bug correlation, as well as the network measures that contribute more to bug prediction. These observations show that the requirements dependency network can be used as an early indicator and predictor of software integration bugs.
Language: 英语
WOS ID: WOS:000376412200001
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/17009
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Wang, Junjie ,Wang, Qing . Analyzing and predicting software integration bugs using network analysis on requirements dependency network[J]. Requirements Engineering,2014-01-01.
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