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Family model mining for function block diagrams in automation software

Published: 15 September 2014 Publication History

Abstract

Automation systems are mostly individual highly customized system variants, consisting both of hardware and software. In order to reduce development effort, it is a common practice to use a clone-and-own approach by modifying an existing variant to fit the changed requirements of a new variant. The information about the commonalities and differences between those variants is usually not well documented and leads to problems in maintenance, testing and evolution. To alleviate these problems, in this paper, we present an improved version of a family mining approach for automatically discovering commonality and variability between related system variants. We apply this approach to function block diagrams used to develop automation software and show its feasibility by a manufacturing case study.

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cover image ACM Other conferences
SPLC '14: Proceedings of the 18th International Software Product Line Conference: Companion Volume for Workshops, Demonstrations and Tools - Volume 2
September 2014
151 pages
ISBN:9781450327398
DOI:10.1145/2647908
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • University of Florence: University of Florence
  • CNR: Istituto di Scienza e Tecnologie dell Informazione

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 September 2014

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Author Tags

  1. automation software
  2. family mining
  3. re-engineering
  4. software engineering

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  • Research-article

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SPLC '14
Sponsor:
  • University of Florence
  • CNR

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Overall Acceptance Rate 167 of 463 submissions, 36%

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  • (2023)True Variability Shining Through Taxonomy MiningProceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A10.1145/3579027.3608989(182-193)Online publication date: 28-Aug-2023
  • (2022)Synchronizing software variantsProceedings of the 26th ACM International Systems and Software Product Line Conference - Volume B10.1145/3503229.3547053(82-89)Online publication date: 12-Sep-2022
  • (2022)DSMCompare: domain-specific model differencing for graphical domain-specific languagesSoftware and Systems Modeling10.1007/s10270-021-00971-121:5(2067-2096)Online publication date: 7-Jan-2022
  • (2021)Custom-tailored clone detection for IEC 61131-3 programming languagesJournal of Systems and Software10.1016/j.jss.2021.111070182:COnline publication date: 1-Dec-2021
  • (2021)Learning by sampling: learning behavioral family models from software product linesEmpirical Software Engineering10.1007/s10664-020-09912-w26:1Online publication date: 1-Jan-2021
  • (2021)Enhancing software model encoding for feature location approaches based on machine learning techniquesSoftware and Systems Modeling10.1007/s10270-021-00920-yOnline publication date: 23-Aug-2021
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  • (2019)Automated N-way Program Merging for Facilitating Family-based Analyses of Variant-rich SoftwareACM Transactions on Software Engineering and Methodology10.1145/331378928:3(1-59)Online publication date: 18-Jul-2019
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