Proceedings IEEE Joint International Conference on Requirements Engineering (2002)
Sept. 9, 2002 to Sept. 13, 2002
Martin S. Feather , California Institute of Technology
Tim Menzies , West Virginia University
<p>Planning for the optimal attainment of requirements is an important early lifecycle activity. However, such planning is difficult when dealing with competing requirements, limited resources, and the incompleteness of information available at requirements time.</p> <p>A novel approach to requirements optimization is described. A requirements interaction model is executed to randomly sample the space of options. This produces a large amount of data, which is then condensed by a summarization tool. Theresult isasmall list ofcritical decisions (i.e., those most influential in leading towards the desired optimum). This focuses human experts? attention on a relatively few decisions and makes them aware of major alternatives.</p> <p>This approach is iterative. Each iteration allows experts to select from among the major alternatives. In successive iterations the execution and summarization modules are run again, but each time further constrained by the decisions made in previous iteration. In the case study shown here, out of 99 yes/no decisions (approximately 10 30 possibilities), five iterations were sufficient to find and make the 30 key ones.</p>
T. Menzies and M. S. Feather, "Converging on the Optimal Attainment of Requirements," Proceedings IEEE Joint International Conference on Requirements Engineering(RE), Essen, Germany, 2002, pp. 263.