Special Issue of the Automated Software Engineering Journal
Next Generation Search-Based Software Engineering: Insights from Search and Data Mining


Guest Editors: Marouane Kessentini, University of Michigan, Dearborn, MI, USA marouane@umich.edu
Tim Menzies, North Carolina State University, NC, USA


The concept of search has been explored in many fields such as Search-Based Software Engineering and Data Mining (e.g. one way to characterize data mining is a heuristic search though a large space of possible generalizations). That is, there is a strong theoretical connection between the goals of Search-Based SE and data mining. Hence, many papers have explored combinations of data mining and SBSE, using a range of techniques. For example:



The goal of this special issue is to understand the cost/benefit trade offs in combining Search-based SE and data mining. There are many questions in this field including (but not restricted to) the following:




This special issue encourages high quality submissions on all aspects of combing data mining and search-based software engineering. Note that the evaluation section of all such submissions must use at least some software engineering case studies such as (but are not limited to) :



Submission of a manuscript implies that the work described has not been published before. A submission extended from a previous conference version has to contain at least 30% new material. Authors are requested to attach to the submitted paper their previously published articles and an explanation of the novel contributions made in the journal version. Papers should be submitted to the special issue through the Editorial Manager https://www.editorialmanager.com/ause/, selecting the article type "Special Issue: Search-based Software Engineering and Predictive Modelling". Formatting templates can be found in the following link: http://www.springer.com/computer/ai/journal/10515?detailsPage=pltci_1060168