Application of Data Mining Techniques for Improving Continuous Integration

Authors

  • Meenakshi Kathayat Assistant Professor, Department of Computer Science & Engineering, Birla Institute of Applied Sciences Bhimtal, Uttarakhand, INDIA

DOI:

https://doi.org/10.31033/ijemr.8.5.4

Keywords:

Continuous integration, Agile development, Software development, Data mining techniques

Abstract

Continuous integration is a software development process where members of a team frequently integrate the work done by them. Generally each person integrates at least daily - leading to multiple integrations per day. Integration done by each developer is verified by an automated build (including test) to detect integration errors as quickly as possible. Many teams find that this approach reduces integration problems and allows a team to develop cohesive software rapidly. Continuous Integration doesn’t remove bugs, but it does make them dramatically easier to find and remove. This paper provides an overview of various issues regarding Continuous Integration and how various data mining techniques can be applied in continuous integration data for extracting useful knowledge and solving continuous integration problems.

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Published

2018-10-31

How to Cite

Meenakshi Kathayat. (2018). Application of Data Mining Techniques for Improving Continuous Integration. International Journal of Engineering and Management Research, 8(5), 20–23. https://doi.org/10.31033/ijemr.8.5.4