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ACE: Easy Deployment of Field Optimization Experiments
Chalmers Univ Technol, Dept Comp Sci & Engn, Horselgangen 11, S-41296 Gothenburg, Sweden..
Chalmers Univ Technol, Dept Comp Sci & Engn, Horselgangen 11, S-41296 Gothenburg, Sweden..ORCID iD: 0000-0003-2854-722X
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-7700-1816
2019 (English)In: SOFTWARE ARCHITECTURE, ECSA 2019 / [ed] Bures, T Duchien, L Inverardi, P, Springer, 2019, p. 264-279Conference paper, Published paper (Refereed)
Abstract [en]

Optimization of software parameters is a recurring activity in the life-cycle of many software products, from prototypes and simulations, test beds and hardware-in-the-loop scenarios, field calibrations to the evolution of continuous deployment cycles. To perform this activity, software companies require a combination of software developers and optimization experts with domain specific knowledge. Moreover, in each of life-cycle steps, companies utilize a plethora of different tools, tailored for specific domains or development stages. To most companies, this scenario leads to an excessive cost in the optimization of smaller features or in cases where it is not clear what the returned value will be. In this work we present a new optimization system based on field experiments, that is aimed to facilitate the adoption of optimization in all stages of development. We provide two main contributions. First, we present the architecture of a new optimization system that allows existing software systems to perform optimization procedures in different domains and in different development stages. This optimization system utilizes domain-agnostic interfaces to allow existing systems to perform optimization procedures with minimal invasiveness and optimization expertise. Second, we provide an overview of the deployments, discuss the advantages and limitations and evaluate the optimization system in three empirical scenarios: (1) offline optimization with simulations; (2) optimization of a communication system in a test bed in collaboration with Ericsson; (3) live optimization of a mobile application in collaboration with Sony Mobile. We aim to provide practitioners with a single optimization tool that can leverage their optimization activities from offline to live systems, with minimal invasiveness and optimization expertise.

Place, publisher, year, edition, pages
Springer, 2019. p. 264-279
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11681
Keywords [en]
Optimization, Black-box optimization, Field experiments, Software architecture
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:mau:diva-64422DOI: 10.1007/978-3-030-29983-5_18ISI: 000613130900018Scopus ID: 2-s2.0-85072826665ISBN: 978-3-030-29983-5 (print)ISBN: 978-3-030-29982-8 (print)OAI: oai:DiVA.org:mau-64422DiVA, id: diva2:1819484
Conference
13th European Conference on Software Architecture Engineering (ECSA), SEP 09-13, 2019, Paris, FRANCE
Available from: 2023-12-14 Created: 2023-12-14 Last updated: 2023-12-14Bibliographically approved

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Olsson, Helena Holmström

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