Abstract
In the current era, the auto and reliable recommendation system plays a significant role in human life. The code recommender systems are being used in various source code databases to recommend the most suitable source code to the user. While code recommendation, the code analysis concerning 'code quality' and 'code implementation' is important to recommend the most reliable code by considering the objective of the user. The ultimate aim of this research work is to propose a code recommendation and implementation model using the characteristics of DevOps that assist in extracting, analyzing, implementing, and updating the recommender system continuously. The current study presents an initial framework of the proposed code recommender model. The design of the model is based on the data collected through literature review and by conducting an empirical study with experts. We believe that the proposed model will assist the researchers and practitioners to recommend the most secure and suitable source code according to their requirement.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
