Differential evolution with Pareto tournament for the multi-objective next release problem

摘要

Software requirements selection is the engineering process in which the set of new requirements which will be included in the next release of a software product are chosen. This NP-hard problem is an important issue involving several contradictory objectives that have to be tackled by software companies when developing new releases of software packages. Software projects have to stick to a budget, but they also have to cover the highest number of customer requirements. Furthermore, in real instances of the problem, the requirements tackled suffer interactions and other restrictions which complicate the problem. In this paper, we use an adapted multi-objective version of the differential evolution (DE) evolutionary algorithm which has been successfully applied to several real instances of the problem. For doing this, the software requirements selection problem has been formulated as a multiobjective optimization problem with two objectives: the total software development cost and the overall customer’s satisfaction, and with three interaction constraints. On the other hand, the original DE algorithm has been adapted to solve real instances of the problem generated from data provided by experts. Numerical experiments with case studies on software requirements selection have been carried out to demonstrate the effectiveness of the multiobjective proposal and the obtained results show that the developed algorithm performs better than other relevant algorithms previously published in the literature under a set of public datasets.