Prioritizing Software Requirements by Combining the Usage Monitoring and User Feedback Data

The elicitation of requirements for systems in use is known as continuous requirements elicitation. Monitoring and feedback data have been used in the literature for the continuous elicitation and prioritization of requirements. Frameworks and techniques are available for gathering usage monitoring and user feedback data but the existing work does not correlate the user feedback and usage monitoring data for continuous requirements elicitation and prioritization, the scope of monitoring is limited and the elicitation and prioritization process involves manual intervention resulting in lower user satisfaction level. To overcome these limitations and achieve higher user satisfaction, our goal is to provide a mechanism to prioritize requirements through a recommender system in a semi-automated manner by correlating usage monitoring and user feedback data granular to the use case level. For this, we introduce a four-step method in which the first step deals with acquiring granular usage monitoring and user feedback data to the use-case level, and the second step performs the correlation of user feedback and usage monitoring data. Based on the correlation found, the requirements priorities are recommended in the third step. In this step, default priority is assigned using a matrix similar to the Eisenhower Decision Matrix. In the fourth step, this default priority is given a priority score according to the frequency of the feedback messages. We performed an evaluation by comparing the requirements prioritization list received from our proposed technique to the requirements prioritized by the requirements engineer. A comparison with existing works also shows the superiority of our approach. These comparisons indicate that requirements prioritization using correlated user feedback and usage monitoring data has resulted in achieving higher user satisfaction level towards requirements prioritization.