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The Impact of Service Cohesion on the Analyzability of Service-Oriented Software

Published: 01 April 2010 Publication History

Abstract

Service-Oriented Computing (SOC) is intended to improve software maintainability as businesses become more agile and underlying processes and rules change more frequently. However, to date, the impact of service cohesion on the analyzability subcharacteristic of maintainability has not been rigorously studied. Consequently, this paper extends existing notions of cohesion in the Procedural and OO paradigms in order to account for the unique characteristics of SOC, thereby supporting the derivation of design-level software metrics for objectively quantifying the degree of service cohesion. The metrics are theoretically validated, and an initial empirical evaluation using a small-scale controlled study suggests that the proposed metrics could help predict analyzability early in the Software Development Life Cycle. If future industrial studies confirm these findings, the practical applicability of such metrics is to support the development of service-oriented systems that can be analyzed, and thus maintained, more easily. In addition, such metrics could help identify design problems in existing systems.

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  • (2022)Analysis of Microservice Evolution using Cohesion MetricsProceedings of the 16th Brazilian Symposium on Software Components, Architectures, and Reuse10.1145/3559712.3559716(40-49)Online publication date: 3-Oct-2022
  • (2021)Multi-criteria Web Services Selection: Balancing the Quality of Design and Quality of ServiceACM Transactions on Internet Technology10.1145/344638822:1(1-31)Online publication date: 28-Sep-2021
  • (2020)Web Service API Anti-patterns Detection as a Multi-label Learning ProblemWeb Services – ICWS 202010.1007/978-3-030-59618-7_8(114-132)Online publication date: 18-Sep-2020
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cover image IEEE Transactions on Services Computing
IEEE Transactions on Services Computing  Volume 3, Issue 2
April 2010
75 pages

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IEEE Computer Society

United States

Publication History

Published: 01 April 2010

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  1. Services systems, design concepts, maintainability, product metrics.

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Cited By

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  • (2022)Analysis of Microservice Evolution using Cohesion MetricsProceedings of the 16th Brazilian Symposium on Software Components, Architectures, and Reuse10.1145/3559712.3559716(40-49)Online publication date: 3-Oct-2022
  • (2021)Multi-criteria Web Services Selection: Balancing the Quality of Design and Quality of ServiceACM Transactions on Internet Technology10.1145/344638822:1(1-31)Online publication date: 28-Sep-2021
  • (2020)Web Service API Anti-patterns Detection as a Multi-label Learning ProblemWeb Services – ICWS 202010.1007/978-3-030-59618-7_8(114-132)Online publication date: 18-Sep-2020
  • (2019)UniDoSA: The Unified Specification and Detection of Service AntipatternsIEEE Transactions on Software Engineering10.1109/TSE.2018.281918045:10(1024-1053)Online publication date: 1-Oct-2019
  • (2018)API library-based identification and documentation of usage patternsInternational Journal of Computer Applications in Technology10.1504/IJCAT.2018.09406558:1(63-79)Online publication date: 1-Jan-2018
  • (2018)A Hybrid Approach for Improving the Design Quality of Web Service InterfacesACM Transactions on Internet Technology10.1145/322659319:1(1-24)Online publication date: 22-Dec-2018
  • (2017)Identification multi-level frequent usage patterns from APIsJournal of Systems and Software10.1016/j.jss.2017.05.039130:C(42-56)Online publication date: 1-Aug-2017
  • (2017)The impact of feature selection on maintainability prediction of service-oriented applicationsService Oriented Computing and Applications10.1007/s11761-016-0202-911:2(137-161)Online publication date: 1-Jun-2017
  • (2017)Automating identification of services and their variability for product lines using NSGA-IIFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-016-5121-611:3(444-464)Online publication date: 1-Jun-2017
  • (2015)Web Service Antipatterns Detection Using Genetic ProgrammingProceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739480.2754724(1351-1358)Online publication date: 11-Jul-2015
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