Ant Colony Optimization for the Next Release Problem: A Comparative Study

What is it about?

The selection of the enhancements to be included in the next software release is a complex task in every software development. Customers demand their own software enhancements, but all of them cannot be included in the software product, mainly due to the existence limited resources. In most of the cases, it is not feasible to develop all the new functionalities suggested by customers. Hence each new feature competes against each other to be included in the next release. This problem of minimizing development effort and maximizing customers' satisfaction is known as the next release problem (NRP). In this work we study the NRP problem as an optimisation problem. We use and describe three different meta-heuristic search techniques for solving NRP: simulated annealing, genetic algorithms and ant colony system (specifically, we show how to adapt the ant colony system to NRP). All of them obtain good but possibly sub optimal solution. Also we make a comparative study of these techniques on a case study. Furthermore, we have observed that the sub optimal solutions found applying these techniques include a high percentage of the requirements considered as most important by each individual customer.

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