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Indexed by:期刊论文

Date of Publication:2012-09-01

Journal:IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Included Journals:SCIE、EI、Scopus

Volume:38

Issue:5

Page Number:1195-1212

ISSN No.:0098-5589

Key Words:The next release problem; backbone; soft backbone; multilevel algorithm; requirements instance generation; search-based requirements engineering

Abstract:The Next Release Problem (NRP) aims to optimize customer profits and requirements selection for the software releases. The research on the NRP is restricted by the growing scale of requirements. In this paper, we propose a Backbone-based Multilevel Algorithm (BMA) to address the large scale NRP. In contrast to direct solving approaches, the BMA employs multilevel reductions to downgrade the problem scale and multilevel refinements to construct the final optimal set of customers. In both reductions and refinements, the backbone is built to fix the common part of the optimal customers. Since it is intractable to extract the backbone in practice, the approximate backbone is employed for the instance reduction while the soft backbone is proposed to augment the backbone application. In the experiments, to cope with the lack of open large requirements databases, we propose a method to extract instances from open bug repositories. Experimental results on 15 classic instances and 24 realistic instances demonstrate that the BMA can achieve better solutions on the large scale NRP instances than direct solving approaches. Our work provides a reduction approach for solving large scale problems in search-based requirements engineering.