Improving Software Development Using AI Enabled Predictive Analytics
Srija Saha · Journal of Artificial Intelligence Machine Learning and Data Science · 2024
The incorporation of Artificial intelligence into software development is moving rapidly with predictive analytics playing a crucial role in better decision making, maximising resources, and increasing product quality.The use of AI powered predictive analytics, and several phases of the software development life cycle has gained considerable traction.However, there is still a lack of exploration in implementing a comprehensive strategy to its application.This paper provides a thorough investigation of the incorporation of Artificial intelligence (AI) across the whole software development process, including requirement analysis, design, coding, testing and maintenance.Using predictive models, artificial intelligence allows for the anticipation of the changes in requirements, discovery of design fault, detection of code defects, optimization of test coverage, prediction of maintenance needs.This paper discusses the comprehensive integration of AI across the whole project lifetime, leading to improved results by enhancing individual stages and creating synergetic benefits.The proposed solution aims to tackle key challenges such as data quality, model interpretability, and tool integration.These solutions include implementation of explainable AI approaches, adoption and strong governance practices.Concrete examples from real world scenarios showcase the practical advantages of using AI driven predictive analytics.These examples highlight the ability to reduce project timelines, enhance code quality, and raise fault detection rates.The importance of AI in software development is anticipated to increase as it continues to improve, presenting enhanced prospects for innovation and efficiency.This paper offers a roadmap for enterprises aiming to use AI to revolutionise the software development processes and achieve exceptional results.