Multicriteria decision making taxonomy of code recommendation system challenges: a fuzzy-AHP analysis

Abstract The recommendation systems plays an important role in today’s life as it assist reliable selection of common utilities. code system is being used by the databases (GitHub, source frog etc.) aiming to recommend more appropriate users. There are several factors that could negatively impact performance (CRS). This study aims empirically explore challenges have critical on CRS. Using systematic literature review and questionnaire survey approaches, 19 were identified. Secondly, investigated further prioritized using fuzzy-AHP analysis. identification challenges, their categorization analysis provides prioritization-based taxonomy explored challenges. findings will real-world industry experts academic researchers improve develop new techniques for improvement