Enhancing Agile Development Cycles with AI-Powered Code Generation: A Framework for Automated Feature Implementation and Error Detection

Authors: Nagaraj Parvatha

DOI: https://doi.org/10.37082/IJIRMPS.v11.i6.232520

Short DOI: https://doi.org/g9mnc8

Country: India

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Abstract: Agile software devcreated elopment serves as the essential foundation for creating adjustable efficient software products. Traditional Agile workflows encounter various difficulties including slow-moving feature shipment durations and delayed faultfinding processes. Researchers have a new AI framework which detects errors during Agile development stages while automatically executing user specifications and producing code. Through integration with modern AI tools the framework creates a smooth code development system which also performs immediate issue detection. The framework demonstrates substantial benefits by accelerating development speed together with higher code quality and improved team operational efficiency using conceptual design alongside an imagined test case. The framework agrees with Agile principles by supporting collaborative work and rapid project delivery through iterative development cycles despite the present challenges with AI implementation and accuracy dependence. Future study should enhance the framework through AI monitoring features which would enable both automatic testing and deployment procedures leading to breakthroughs in software advancement methods.

Keywords: Agile development, AI-powered tools, code generation, error detection, software quality, iterative workflows, team productivity.

Paper Id: 232520

Published On: 2023-12-19

Published In: Volume 11, Issue 6, November-December 2023

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