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Data in DevOps and Its Importance in Code Analytics

Data in DevOps and Its Importance in Code Analytics

Girish Babu, Charitra Kamalaksh Patil
Copyright: © 2020 |Pages: 27
ISBN13: 9781799818632|ISBN10: 1799818632|ISBN13 Softcover: 9781799818649|EISBN13: 9781799818656
DOI: 10.4018/978-1-7998-1863-2.ch007
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MLA

Babu, Girish, and Charitra Kamalaksh Patil. "Data in DevOps and Its Importance in Code Analytics." Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities, edited by Vishnu Pendyala, IGI Global, 2020, pp. 182-208. https://doi.org/10.4018/978-1-7998-1863-2.ch007

APA

Babu, G. & Patil, C. K. (2020). Data in DevOps and Its Importance in Code Analytics. In V. Pendyala (Ed.), Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities (pp. 182-208). IGI Global. https://doi.org/10.4018/978-1-7998-1863-2.ch007

Chicago

Babu, Girish, and Charitra Kamalaksh Patil. "Data in DevOps and Its Importance in Code Analytics." In Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities, edited by Vishnu Pendyala, 182-208. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-1863-2.ch007

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Abstract

Robust DevOps plays a huge role in the health and sanity of software. The metadata generated during DevOps need to be harnessed for deriving useful insights on the health of the software. This area of work can be classified as code analytics and comprises of the following (but not limited to): 1. commit history from the source code management system (SCM); 2. the engineers that worked on the commit; 3. the reviewers on the commit; 4. the extent of build (if applicable) and test validation prior to the commit, the types of failures found in iterative processes, and the fixes done; 5. test extent of test coverage on the commit; 6. any static profiling on the code in the commit; 7. the size and complexity of the commit; 8. many more. This chapter articulates many ways the above information can be used for effective software development.

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