% % GENERATED FROM http://acme.able.cs.cmu.edu % by : anonymous % IP : ec2-18-116-51-117.us-east-2.compute.amazonaws.com % at : Fri, 26 Apr 2024 16:09:47 -0400 GMT % % Selection : Publication #393 %
@InProceedings{Barnes:2013/EvolutionPlanning, AUTHOR = {Barnes, Jeffrey M. and Pandey, Ashutosh and Garlan, David}, TITLE = {Automated Planning for Software Architecture Evolution}, YEAR = {2013}, MONTH = {11-15 November}, BOOKTITLE = {The 28th IEEE/ACM International Conference on Automated Software Engineering}, ADDRESS = {Silicon Valley, CA}, PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/ASE2013-final.pdf}, ABSTRACT = {In previous research, we have developed a theoretical framework to help software architects make better decisions when planning software evolution. Our approach is based on representation and analysis of candidate evolution paths—sequences of transitional architectures leading from the current system to a desired target architecture. One problem with this kind of approach is that it imposes a heavy burden on the software architect, who must explicitly define and model these candidate paths. In this paper, we show how automated planning techniques can be used to support automatic generation of evolution paths, relieving this burden on the architect. We illustrate our approach by applying it to a data migration scenario, showing how this architecture evolution problem can be translated into a planning problem and solved using existing automated planning tools.}, KEYWORDS = {Architecture Evolution} } |