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Modelling Software Tasks for Supporting Resource-Driven Adaptation

  • Notre Dame University-Louaize
  • Open University Milton Keynes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Software systems execute tasks that depend on different types of resources. The variability of resources hinders the ability of software systems to execute important tasks. For example, in automated warehouses, malfunctioning robots could delay product deliveries and cause financial losses due to customer dissatisfaction. Resource-driven adaptation addresses the negative implications of resource variability. Hence, this paper presents a task modelling notation called SERIES, which is used for representing task models that support resource-driven adaptation in software systems. SERIES is complemented by a tool that enables software practitioners to create and modify task models. SERIES was evaluated through a study with software practitioners. The participants of this study were asked to explain and create task models and then provide their feedback on the usability of SERIES and the clarity of its semantic constructs. The results showed a very good user performance in explaining and creating task models using SERIES. These results were reflected in the feedback of the participants and the activities that they performed using SERIES.

Original languageEnglish
Title of host publicationEnterprise Information Systems - 24th International Conference, ICEIS 2022, Revised Selected Papers
EditorsJoaquim Filipe, Michał Śmiałek, Alexander Brodsky, Slimane Hammoudi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages249-272
Number of pages24
ISBN (Print)9783031393853
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event24th International Conference on Enterprise Information Systems, ICEIS 2022 - Virtual, Online
Duration: 25 Apr 202227 Apr 2022

Publication series

NameLecture Notes in Business Information Processing
Volume487 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Conference

Conference24th International Conference on Enterprise Information Systems, ICEIS 2022
CityVirtual, Online
Period25/04/2227/04/22

Keywords

  • Resource-driven adaptation
  • Task modelling notation

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