Automated Framework to Extract Software Requirements from Source Code

Cameron Miskell, Richard Diaz, Parth Ganeriwala, Khaled Slhoub, Fitzroy Nembhard

Abstract: Software maintenance and innovation are constant challenges across industries, especially as programming languages evolve with technology. Similarly, poor lexicon quality degrades program comprehension, increasing the effort required by developers to improve existing software products. To address these challenges, we propose a novel automated framework that extracts software requirements directly from source code using a baseline AI language model applied to a Java code base. Leveraging natural language processing techniques, the framework validates programs and generates easily readable requirements by analyzing file contents. The framework enhances agility and flexibility by providing comprehensive documentation for existing software systems. It caters to both experienced and less-experienced developers, offering an intuitive graphical user interface and enabling efficient identification and resolution of errors. The resulting output facilitates natural interaction through language processing. By automating the extraction process, the framework allows developers to better understand software systems, make informed decisions, and adapt to evolving needs.