A Case Study of Automated Feature Location Techniques for Industrial Cost Estimation
Ameer Armaly, John Klaczynski, Collin McMillan · 2016
We present a case study of feature location in industry. We study two off-the-shelf feature location algorithms for use as input to a software cost estimator. The feature location algorithms that we studied map program requirements to one or more function points. The cost estimator product, which is the industrial context in which we study feature location, transforms the list of function points into an estimate of the resources necessary to implement that requirement. We chose the feature location algorithms because they are simple to explain, deploy and maintain as a project evolves and personnel rotate on and off. We tested both feature location algorithms against a large software system with a development lifespan of over 20 years. We compared both algorithms by surveying our industrial partner about the accuracy of the list of function points produced by each algorithm. To provide further evidence, we compared both algorithms against an open source benchmarking dataset. Finally, we discuss the requirements of the industrial environment and the ways in which it differs from the academic environment. Our industrial partner elected to use Lucene combined with the PageRank algorithm as their feature location algorithm because it balanced accuracy with simplicity.