Recommending Improvements to Web Applications Using Quality-Driven Heuristic Search

Planning out maintenance tasks to increase the quality of Web applications can be difficult for a manager. First, it is hard to evaluate the precise effect of a task on quality. Second, quality improvement will generally be the result of applying a combination of available tasks; identifying the best combination can be complicated. We present a general approach to recommend improvements to Web applications. The approach uses a meta-heuristic algorithm to find the best sequence of changes given a quality model responsible to evaluate the fitness of candidate sequences. This approach was tested using a navigability model on 15 different Web pages. The meta-heuristic recommended the best possible sequence for every tested configuration, while being much more efficient than an exhaustive search with respect to execution time.