research-article

Feature location benchmark with argoUML SPL

Authors:

Jabier Martinez,

Nicolas Ordoñez,

Xhevahire Tërnava,

Eduardo Figueiredo,

Marco Tulio ValenteAuthors Info & Claims

SPLC '18: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1

Pages 257 - 263

https://doi.org/10.1145/3233027.3236402

Published: 10 September 2018 Publication History

Abstract

Feature location is a traceability recovery activity to identify the implementation elements associated to a characteristic of a system. Besides its relevance for software maintenance of a single system, feature location in a collection of systems received a lot of attention as a first step to re-engineer system variants (created through clone-and-own) into a Software Product Line (SPL). In this context, the objective is to unambiguously identify the boundaries of a feature inside a family of systems to later create reusable assets from these implementation elements. Among all the case studies in the SPL literature, variants derived from ArgoUML SPL stands out as the most used one. However, the use of different settings, or the omission of relevant information (e.g., the exact configurations of the variants or the way the metrics are calculated), makes it difficult to reproduce or benchmark the different feature location techniques even if the same ArgoUML SPL is used. With the objective to foster the research area on feature location, we provide a set of common scenarios using ArgoUML SPL and a set of utils to obtain metrics based on the results of existing and novel feature location techniques.

References

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Cited By

Stummer AHager ARabiser R(2024)Towards a Flexible Approach for Variability MiningProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3676543(75-81)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3676543
Greiner SSchultheiß ABittner PThüm TKehrer T(2024)Give an Inch and Take a Mile? Effects of Adding Reliable Knowledge to Heuristic Feature TracingProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3672593(84-95)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3672593
Eisenecker UMüller R(2024)Software product lines and features from the perspective of set theory with an application to feature locationJournal of Systems and Software10.1016/j.jss.2023.111938210:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.jss.2023.111938
Show More Cited By

Index Terms

Feature location benchmark with argoUML SPL
1. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Reusability
        Software product lines
    2. Software post-development issues
      1. Software reverse engineering

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Published In

cover image ACM Other conferences

SPLC '18: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1

September 2018

324 pages

ISBN:9781450364645

DOI:10.1145/3233027

Editors:
Thorsten Berger
Chalmers | University of Gothenburg, Sweden
,
Paulo Borba
Federal University of Pernambuco, Brazil
,
Goetz Botterweck
University of Limerick, Ireland
,
Tomi Männistö
University of Helsinki, Finland
,
David Benavides
University of Seville, Spain
,
Sarah Nadi
University of Alberta, Canada
,
Timo Kehrer
Humboldt-Universität zu Berlin, Germany
,
Rick Rabiser
Johannes Kepler University Linz, Austria
,
Christoph Elsner
Siemens Corporate Technology, Germany
,
Mukelabai Mukelabai
Chalmers | University of Gothenburg, Sweden

Copyright © 2018 ACM.

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]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 September 2018

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ITEA3

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SPLC '18

SPLC '18: 22nd International Systems and Software Product Line Conference

September 10 - 14, 2018

Gothenburg, Sweden

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Overall Acceptance Rate 167 of 463 submissions, 36%

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Cited By

Stummer AHager ARabiser R(2024)Towards a Flexible Approach for Variability MiningProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3676543(75-81)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3676543
Greiner SSchultheiß ABittner PThüm TKehrer T(2024)Give an Inch and Take a Mile? Effects of Adding Reliable Knowledge to Heuristic Feature TracingProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3672593(84-95)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3672593
Eisenecker UMüller R(2024)Software product lines and features from the perspective of set theory with an application to feature locationJournal of Systems and Software10.1016/j.jss.2023.111938210:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.jss.2023.111938
Eyal Salman H(2024)Leveraging a combination of machine learning and formal concept analysis to locate the implementation of features in software variantsInformation and Software Technology10.1016/j.infsof.2023.107320164:COnline publication date: 10-Jan-2024
https://dl.acm.org/doi/10.1016/j.infsof.2023.107320
Acher MMartinez J(2023)Generative AI for Reengineering Variants into Software Product LinesProceedings of the 27th ACM International Systems and Software Product Line Conference - Volume B10.1145/3579028.3609016(57-66)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1145/3579028.3609016
Schultheiß ABittner PGreiner SKehrer T(2023)Benchmark Generation with VEVOS: A Coverage Analysis of Evolution Scenarios in Variant-Rich SystemsProceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3571788.3571793(13-22)Online publication date: 25-Jan-2023
https://dl.acm.org/doi/10.1145/3571788.3571793
Mori AHashimoto M(2023)Phylogenetic Analysis of Reticulate Software Evolution2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR)10.1109/MSR59073.2023.00074(498-510)Online publication date: May-2023
https://doi.org/10.1109/MSR59073.2023.00074
Ghallab KZiadi TChalal Z(2023)Migrating Individual Applications into Software Product Lines Using the Mobioos Forge Platform2023 30th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC60848.2023.00060(483-492)Online publication date: 4-Dec-2023
https://doi.org/10.1109/APSEC60848.2023.00060
Michelon GMartinez JSotto-Mayor BArrieta AAssunção WAbreu REgyed A(2023)Spectrum-based feature localization for families of systemsJournal of Systems and Software10.1016/j.jss.2022.111532195:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.jss.2022.111532
Bertolotti FCazzola WFavalli LFelfernig AFuentes L(2022)Features, believe it or not!Proceedings of the 26th ACM International Systems and Software Product Line Conference - Volume A10.1145/3546932.3546989(32-42)Online publication date: 12-Sep-2022
https://dl.acm.org/doi/10.1145/3546932.3546989
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