The software testing process is an essential phase in the software life cycle. However, the vast size of code and the ambiguity present in defect reports often pose challenges in identifying defects within the source code. This paper aims to propose a method that automatically identifies defect-causing modules in faulty source code. Software developers can utilize this tool in product testing to enhance performance and save time. In our proposed approach, we focus on analyzing the similarity metrics among keywords sourced from Defect Descriptions, commonly found in feedback reports, and the specific Module or Function names embedded within the software's source code. Employing the Cosine similarity technique, we generate precise similarity constants between these linguistic elements. This innovative tool emerges as a potential time-saving asset for software developers, offering the capability to significantly reduce debugging timelines. With its implementation, we anticipate the potential for saving weeks of laborious debugging efforts, empowering developers to tackle defects efficiently and effectively within the source code.