Open AccessRecommender System for Software Engineering using SQL Semantic Search
Author(s) -
Astrit Desku,
Bujar Raufi,
Artan Luma,
Besnik Selimi
Publication year - 2022
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d3494.0411422
Subject(s) - computer science , recommender system , reuse , sql , software engineering , software , information retrieval , measure (data warehouse) , world wide web , database , programming language , ecology , biology
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. This paper outlines an approach to generating recommendation using SQL Semantic Search. Performance measurement of this recommender system is conducted by calculating precision, recall and F1-measure. Subjective evaluations consisted of 10 experienced developers for validating the recommendation. A statistical test t-Test is used to compare the means of two approaches of evaluations.