A Study on Identification of Documentation and Requirement Technical Debt through Code Comment Analysis

Context: The TD concept reflects the challenging decisions that developers and managers need to take to achieve short-term benefits to keep the customers satisfied and to survive in a competitive market. The identification of technical debt (TD) is an important step to effectively manage TD items and make TD manageable and explicit to keep the amount of TD under control. Researchers have developed automated approaches to identify TD items using indicators derived from source code metrics. However, those indicators do not always point to TD that developer teams consider real problems and cannot identify many types of relevant TD. Objective: This work seeks to identify comment patterns and their relationships which can support the identification process of documentation and requirement debts. Method: We performed a qualitative and quantitative analysis to investigate acceptable patterns of comments which indicate the existence of documentation and requirement debts. Results: We classify factors which can impact on the detection automated of documentation and requirement debts. Besides, the performed study provided a set of new patterns to detect documentation and requirement debts. Conclusion: This research contributes to bridge the gap between the TD identification area and code comment analysis, successfully using code comments to detect documentation and requirement debts.