@inbook{9bd19e2c5d8f4dfab468d0e5533af859,
title = "Pareto Optimal Search Based Refactoring at the Design Level",
abstract = "Refactoring aims to improve the quality of a software system's structure. which tends to degrade as the system evolves. While manually, determining useful refactorings can be challenging search based techniques can automatically discover useful refactorings. Current search based refactoring approaches require metrics to be combined in a complex fashion, and produce a single sequence of refactorings. In this paper we show how Pareto optimality can improve search based refactoring, making the combination of metrics easier, and aiding the presentation of multiple sequences of optimal refactorings to users.",
author = "Mark Harman and Laurence Tratt",
year = "2007",
language = "English",
isbn = "978-1-59593-697-4",
series = "GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2",
publisher = "ASSOC COMPUTING MACHINERY",
pages = "1106 -- 1113",
booktitle = "Unknown",
note = "Annual Conference of Genetic and Evolutionary Computation Conference ; Conference date: 07-07-2007 Through 11-07-2007",
}