Search Budget in Multi-Objective Refactoring optimization: a Model-Based Empirical Study
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10456431" target="_blank" >RIV/00216208:11320/22:10456431 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/SEAA56994.2022.00070" target="_blank" >https://doi.org/10.1109/SEAA56994.2022.00070</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SEAA56994.2022.00070" target="_blank" >10.1109/SEAA56994.2022.00070</a>
Alternative languages
Result language
angličtina
Original language name
Search Budget in Multi-Objective Refactoring optimization: a Model-Based Empirical Study
Original language description
Software model optimization is the task of automatically generate design alternatives, usually to improve quality aspects of software that are quantifiable, like performance and reliability. In this context, multi-objective optimization techniques have been applied to help the designer find suitable tradeoffs among several non-functional properties. In this process, design alternatives can be generated through automated model refactoring, and evaluated on non-functional models. Due to their complexity, this type of optimization tasks require considerable time and resources, often limiting their application in software engineering processes.In this paper, we investigate the effects of using a search budget, specifically a time limit, to the search for new solutions. We performed experiments to quantify the impact that a change in the search budget may have on the quality of solutions. Furthermore, we analyzed how different genetic algorithms (i.e., NSGh-II, SPEh2, and PESA2) perform when imposing different budgets. We experimented on two case studies of different size, complexity, and domain.We observed that imposing a search budget considerably deteriorates the quality of the generated solutions, but the specific algorithm we choose seems to play a crucial role. From our experiments, NSGh-II is the fastest algorithm, while PESA2 generates solutions with the highest quality. Differently, SPEh2 is the slowest algorithm, and produces the solutions with the lowest quality.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF18_053%2F0016976" target="_blank" >EF18_053/0016976: International mobility of research, technical and administrative staff at the Charles University</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022
ISBN
978-1-66546-152-8
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
406-413
Publisher name
IEEE COMPUTER SOC
Place of publication
LOS ALAMITOS
Event location
Gran Canaria, Spain
Event date
Aug 31, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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