Methods and Techniques for Recommender Systems in Secure Software Engineering: A Literature Review


Authors : Astrit Desku

Volume/Issue : Volume 7 - 2022, Issue 3 - March

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3KkSMB1

DOI : https://doi.org/10.5281/zenodo.6496507

Recommender Systems are software tools that can assist developers with a wide range of activities, from reusing codes to suggest developers what to do during development of these systems. All recommender systems should exert one or three of future functionalities: Gathering Data and Creating Dataset, Static Analysis and Recommendation to user-by-user interface. In this paper, we have presented a literature review in the field of recommender systems. Papers are aggregating by their context in three main groups: Mechanism to Collect Data, Recommendation Engine to Analyze Data and Generate Recommendations and User Interface to Deliver Recommendations. In the conclusion are presented number of reviewed paper for each category

Keywords : Recommender Systems, Machine Learning, Software Engineering, Data Mining Techniques, Control Flow Graphs.

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