An association rule mining-oriented approach for prioritizing functional requirements

Software requirements play a vital role in ensuring a software product’s success. However, it remains a challenging task to implement all of the user requirements, especially in a resource-constrained development environment. To deal with this situation, a requirements prioritization (RP) process can help determine the sequence for the user requirements to be implemented. However, existing RP techniques are suffered from some major challenges such as lack of automation, excessive effort, and reliance on stakeholders’ involvement to initiate the process. This study intends to propose an automated requirements prioritization approach called association rule mining-oriented (ARMO) to address these challenges. The automation process of the ARMO approach incorporates activities to first pre-process the requirements description and extract features. The features are then examined and analyzed through the applied rule mining technique to prioritize the requirements automatically and efficiently without the involvement of stakeholders. In this work, an evaluation model was further developed to assess the effectiveness of the proposed ARMO approach. To validate the efficacy of ARMO approach, a case study was conducted on real-world software projects grounded on the accuracy, precision, recall, and f1-score measures. The promising experimental results demonstrate the ability of the proposed approach to prioritize user requirements. The proposed approach can successfully prioritize user requirements automatically without requiring a significant amount of effort and stakeholders’ involvement to initiate the RP process.