Project Abstract

Abstract
The emergence of artificial intelligence (AI) has revolutionized various industries, including software development. One critical aspect of software development is bug detection, which can be time-consuming and error-prone when done manually. This research project focuses on leveraging AI techniques to automate bug detection in software development processes. The primary objective is to develop an intelligent system that can automatically identify and classify bugs in software code, thereby enhancing the efficiency and accuracy of bug detection processes. Chapter 1 provides an introduction to the research topic, followed by a background study that explores the current state of bug detection in software development. The problem statement highlights the challenges associated with manual bug detection methods, leading to the formulation of research objectives aimed at improving bug detection efficiency. The limitations and scope of the study are also discussed, along with the significance of the research in advancing the field of software development. Finally, the chapter concludes with the structure of the research and definitions of key terms used throughout the study. Chapter 2 presents a comprehensive literature review that examines existing research and technologies related to bug detection and artificial intelligence in software development. The review covers various AI techniques, such as machine learning and natural language processing, that have been applied to bug detection tasks. Additionally, the chapter discusses the challenges and opportunities associated with automating bug detection using AI technologies. Chapter 3 outlines the research methodology employed in this study, including the data collection process, feature selection techniques, and model development strategies. The chapter also discusses the evaluation metrics used to assess the performance of the AI system in bug detection tasks. Furthermore, the research methodology includes a detailed description of the experimental setup and validation procedures to ensure the reliability and validity of the results. In Chapter 4, the findings of the research are presented and discussed in detail. The chapter highlights the performance of the AI system in detecting bugs in software code compared to traditional manual methods. The results of the experiments conducted indicate the effectiveness of the AI system in improving bug detection accuracy and efficiency. Additionally, the chapter discusses the implications of the findings and their potential impact on software development practices. Chapter 5 concludes the research project with a summary of the key findings and contributions of the study. The chapter also discusses the limitations of the research and provides recommendations for future work in this area. Overall, this research project demonstrates the potential of AI technologies in automating bug detection processes and enhancing the quality of software development practices. Keywords Artificial intelligence, bug detection, software development, machine learning, automated systems, software code, data analysis, research methodology, experimental evaluation, performance metrics.

Project Overview