International Journal of Innovative Research in Computer Science and Technology (IJIRCST) ISSN (Online): 2347-5552, Volume-13, Issue-1, January 2025 https://doi.org/10.55524/ijircst.2025.13.1.1 Article ID IRP-1576, Pages 1-11 http://www.ijircst.org Innovative Research Publication 1 Development of an AI-Driven Model for Advancing Software Engineering Practices Aylin Güzel 1 , and Ahmet Egesoy 2 1 Research Scholar, Department of Computer Engineering, Ege University, Izmir, Turkiye 2 Assistant Professor, Department of Computer Engineering, Ege University, Izmir, Turkiye Correspondence should be addressed to Ahmet Egesoy; Received 11 November 2024; Revised 26 November 2024; Accepted 11 December 2024 Copyright © 2024 Made Ahmet Egesoy et al. This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT- This work introduces the Fuzzy Specification Tree Model (FST), a general-purpose framework designed to enhance AI-assisted software engineering. The paper begins by examining the intricate interplay between software engineering and artificial intelligence (AI), emphasizing how AI technologies are reshaping software development methodologies. Building on a foundation of requirements-driven approaches, the study presents a novel adaptation of classical feature modelling to create a versatile, fuzzy logic-based requirements specification model. This model not only facilitates the definition of functionalities for partially completed software but also supports formal methods for project management, version control, and reuse. By employing separate Fuzzy Specification Trees for requirements and the current state of a project, developers gain a dynamic perspective on project completeness and can leverage AI assistance to prioritize tasks, ensuring efficient progression toward project completion with minimal effort. KEYWORDS- AI, Software Engineering, Requirements Management, Fuzzy Logic. I. INTRODUCTION As software systems grow increasingly complex, traditional methodologies encounter significant limitations in terms of scalability and adaptability. The term "software crisis" is commonly used as an umbrella phrase to describe the persistent and ill-structured challenges associated with software development processes. This crisis is often characterized by the ongoing difficulty in meeting the ever- growing demands for software. Addressing these demands is the overarching goal of software engineering. Artificial intelligence (AI) and formal methods are revolutionizing software engineering by addressing many of the challenges posed by the software crisis. AI techniques, such as machine learning and natural language processing, enable smarter automation of tasks like requirements analysis, code generation, testing, and debugging, reducing human error and increasing efficiency. Meanwhile, formal methods bring mathematical rigor to software development, allowing for precise specification, verification, and validation of software systems. Together, these approaches enhance the scalability and reliability of software engineering processes, enabling the creation of more complex and adaptive systems while maintaining high levels of quality. The Feature-Oriented Domain Analysis (FODA) method was created by Dr. Kyo C. Kang and his colleagues at the Software Engineering Institute (SEI) of Carnegie Mellon University in 1990. They documented their work in the report titled "Feature-Oriented Domain Analysis (FODA) Feasibility Study”, [1] which introduced a systematic approach to domain analysis by identifying common and variable features within a software domain. It is our view that a feature-driven point of view fostered by the use of AI can provide a solution for the problems of software engineering. Our proposal employs a fuzzy version of the FODA tree that is more in line with project management challenges. The remainder of this paper is organized as follows: Section II provides an overview of the role of AI in software engineering. Section III discusses the advantages of a requirements-based approach. Section IV presents the proposed model which is an innovative diagram type (and data structure) called Fuzzy Specification Tree Model. Finally, Section V concludes the paper. II. AI IN SOFTWARE ENGINEERING Artificial intelligence (AI) is a branch of computer science focused on creating intelligent systems capable of acting and communicating in ways that resemble human behavior. AI enables computer systems to explore and perform tasks in domains traditionally driven by human labor. These systems operate with high accuracy, reduce operational costs, and enhance production processes, making them more efficient and manageable. Consequently, it is expected that AI technologies will bring comparable advancements and efficiencies to the field of software engineering. Determining what qualifies as intelligence is inherently challenging, particularly in a domain already regarded as ill-structured, even for humans. Any technique that demonstrably aids in managing the inherent complexity of software systems by offering developers valuable insights or assistance can justifiably be classified as AI. AI has a wide range of applications in software engineering. The following sub-sections will explore several key areas where AI can be utilized, including cost estimation, fault prediction, test estimation, testing, software maintenance, reuse, quality prediction, source code summarization, and the detection of design and code bad smells.