When simplicity meets effectiveness: Detecting code comments coherence with word embeddings and LSTM
Michael Dubem Igbomezie, Phuong T. Nguyen, Davide Di Ruscio · 2024
Code comments play a crucial role in software development, as they provide programmers with practical information, allowing them to understand better the intent and semantics of the underpinning code. Nevertheless, developers tend to leave comments unchanged after updating the code, resulting in a discrepancy between the two artifacts. Such a discrepancy may trigger misunderstanding and confusion among developers, impeding various activities, including code comprehension and maintenance. Thus, it is crucial to identify if, given a code snippet, its corresponding comment is coherent and reflects well the intent behind the code. Unfortunately, existing approaches to this problem, while obtaining an encouraging performance, either rely on heavily pre-trained models, or treat input data as text, neglecting the intrinsic features contained in comments and code, including word order and synonyms.