Assessing the Costs and Benefits of Proactively Adding Features in opensource system Bitcoin-Wallet: A Simulation study

Abstract: Objective: This paper builds on previous research and expands on the cost-benefit analysis of proactive feature annotation, with a focus on using Java to validate the findings from a real-world case study. Background: The significance of features within a system lies behind the need to locate them as they often necessitate identification for enhancement, and editing-related activities. However, the absence of readily available information regarding their locations can lead to prolonged recovery times and could potentially lead to inaccuracies in the location of features and inconsistencies in the superlative tasks such as feature enhancement. In contrast, incorporating this information about features directly into the codebase is advantageous. Method: While the eager strategy of annotating in the codebase may initially incur certain costs, the long-term benefits are likely to outweigh these added costs, resulting in a more efficient and easy-to-maintain system. This study investigates the case of an open source Bitcoin-Wallet system to establish traceability between features and assets in a clone-based product line through feature annotations. By employing nine evolution patterns, the study evaluates the costs and benefits of proactively adding annotations internally within the assets. Results: Results demonstrate the costeffectiveness of embedded annotations in reducing annotation costs and improving feature location, which consequently enhances developers’ efficiency and accuracy in performing feature-oriented tasks such as maintaining and reusing the code.