Knowledge sharing factors for modern code review to minimize software engineering waste

Software engineering activities, for instance, Modern Code Review (MCR) produce quality software by identifying the defects from the code. It involves social coding and provides ample opportunities to share knowledge among MCR team members. However, the MCR team is confronted with the issue of waiti...

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Bibliographic Details
Main Authors: Fatima, N. (Author), Nazir, S. (Author), Chuprat, S. (Author)
Format: Article
Language:English
Published: Science and Information Organization, 2020.
Subjects:
Online Access:Get fulltext
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001 87641
042 |a dc 
100 1 0 |a Fatima, N.  |e author 
700 1 0 |a Nazir, S.  |e author 
700 1 0 |a Chuprat, S.  |e author 
245 0 0 |a Knowledge sharing factors for modern code review to minimize software engineering waste 
260 |b Science and Information Organization,   |c 2020. 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/87641/1/NargisFatima_2020KnowledgeSharingFactorsforModernCode.pdf 
520 |a Software engineering activities, for instance, Modern Code Review (MCR) produce quality software by identifying the defects from the code. It involves social coding and provides ample opportunities to share knowledge among MCR team members. However, the MCR team is confronted with the issue of waiting waste due to poor knowledge sharing among MCR team members. As a result, it delays the project delays and increases mental distress. To minimize the waiting waste, this study aims to identify knowledge sharing factors that impact knowledge sharing in MCR. The methodology employed for this study is a systematic literature review to identify knowledge sharing factors, data coding with continual comparison and memoing techniques of grounded theory to produce a unique and categorized list of factors influencing knowledge sharing. The identified factors were then assessed through expert panel for its naming, expressions, and categorization. The study finding reported 22 factors grouped into 5 broad categories i.e. Individual, Team, Social, Facility conditions, and Artifact. The study is useful for researchers to extend the research and for the MCR team to consider these factors to enhance knowledge sharing and to minimize waiting waste. 
546 |a en 
650 0 4 |a T Technology (General)