Recommender System for Software Engineering using SQL Semantic Search
Astrit Desku1, Bujar Raufi2, Artan Luma3, Besnik Selimi4
1Astrit Desku*, Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia.
2Bujar Raufi, Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia.
3Artan Luma, Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia.
4Besnik Selimi, Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia.
Manuscript received on 31 March 2022. | Revised Manuscript received on 06 April 2022. | Manuscript published on 30 April 2022. | PP: 119-122 | Volume-11 Issue-4, April 2022. | Retrieval Number: 100.1/ijeat.D34940411422 | DOI: 10.35940/ijeat.D3494.0411422
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Recommender Systems, Semantic Search, Software Engineering.
Scope of the Article: Software Engineering & Its Applications