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research-article

Model level design pattern instance detection using answer set programming

Authors:

Matthew Stephan,

Daniela InclezanAuthors Info & Claims

MiSE '16: Proceedings of the 8th International Workshop on Modeling in Software Engineering

Pages 13 - 19

https://doi.org/10.1145/2896982.2896991

Published: 14 May 2016 Publication History

Abstract

Software engineering is becoming increasingly model-centric. Engineers are using models more within projects and their models are growing in complexity. A challenge facing the modeling community is evaluation of these models. One technique for software evaluation is detecting instances of established "good" or "bad" solutions in a system, often termed design patterns or antipatterns, respectively. Most approaches require implemented code for detection. However, this precludes early-stage analysis, and the evaluation of purely or mostly model-centric systems. In this position paper, we introduce a detection technique that uses answer set programming to find occurrences of patterns within sets of structural and behavioral models. We represent the patterns as rules and the structural and behavioral system models as facts, requiring both model types since some patterns specify both. We provide an overview of our proposed approach, contrast existing work, and present discussion points on its impact on model evaluation and anticipated challenges.

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Cited By

Houichime TEl Amrani Y(2025)Context Is All You Need: A Hybrid Attention-Based Method for Detecting Code Design PatternsIEEE Access10.1109/ACCESS.2025.352584913(9689-9707)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3525849
Wang LSong TSong HZhang S(2022)Research on Design Pattern Detection Method Based on UML Model with Extended Image Information and Deep LearningApplied Sciences10.3390/app1217871812:17(8718)Online publication date: 30-Aug-2022
https://doi.org/10.3390/app12178718
Yarahmadi HHasheminejad S(2020)Design pattern detection approaches: a systematic review of the literatureArtificial Intelligence Review10.1007/s10462-020-09834-5Online publication date: 20-Apr-2020
https://doi.org/10.1007/s10462-020-09834-5
Show More Cited By

Index Terms

Model level design pattern instance detection using answer set programming
1. Social and professional topics
  1. Computing / technology policy
    1. Intellectual property
      1. Software reverse engineering
2. Software and its engineering

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cover image ACM Conferences

MiSE '16: Proceedings of the 8th International Workshop on Modeling in Software Engineering

May 2016

93 pages

ISBN:9781450341646

DOI:10.1145/2896982

Copyright © 2016 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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ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS\DATC: IEEE Computer Society
TCSE: IEEE Computer Society's Tech. Council on Software Engin.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 May 2016

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ICSE '16

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IEEE-CS\DATC
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ICSE '16: 38th International Conference on Software Engineering

May 14 - 22, 2016

Texas, Austin

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Overall Acceptance Rate 13 of 30 submissions, 43%

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Cited By

Houichime TEl Amrani Y(2025)Context Is All You Need: A Hybrid Attention-Based Method for Detecting Code Design PatternsIEEE Access10.1109/ACCESS.2025.352584913(9689-9707)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3525849
Wang LSong TSong HZhang S(2022)Research on Design Pattern Detection Method Based on UML Model with Extended Image Information and Deep LearningApplied Sciences10.3390/app1217871812:17(8718)Online publication date: 30-Aug-2022
https://doi.org/10.3390/app12178718
Yarahmadi HHasheminejad S(2020)Design pattern detection approaches: a systematic review of the literatureArtificial Intelligence Review10.1007/s10462-020-09834-5Online publication date: 20-Apr-2020
https://doi.org/10.1007/s10462-020-09834-5
Stephan MCordy J(2016)Model-Driven Evaluation of Software Architecture Quality Using Model Clone Detection2016 IEEE International Conference on Software Quality, Reliability and Security (QRS)10.1109/QRS.2016.21(92-99)Online publication date: Aug-2016
https://doi.org/10.1109/QRS.2016.21

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