KOMPARASI EFEKTIFITAS REKOMENDASI KODE GITHUB COPILOT VERSUS AMAZON CODEWHISPERER

Abstract

Advances in artificial intelligence (AI) technology have had a significant impact, particularly in the application development sector. GitHub Copilot and AWS Code Whisperer, which function as AI Code Generators, are examples of emerging solutions. This study aims to determine the effectiveness of using an AI code generator and the best results that can be generated between using GitHub Copilot and Amazon Code Whisperer. A systematic literature review was conducted by searching for and analyzing research journals related to the topic, applying inclusion and exclusion criteria. The study aims to identify differences in functionality, testing, and the influence of programming languages ​​on the accuracy and validity of the code recommendations provided. It also aims to compare the effectiveness of code recommendations by GitHub Copilot and Amazon Code Whisperer based on previous research.