A general framework to detect behavioral design patterns

Cong Liu; Boudewijn van Dongen; Nour Assy; Wil M.P. van der Aalst

doi:10.1145/3183440.3194947

A general framework to detect behavioral design patterns

Cong Liu, Boudewijn van Dongen, Nour Assy, Wil M.P. van der Aalst

Process Analytics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

7 Citations (Scopus)

2 Downloads (Pure)

Abstract

This paper presents a general framework to detect behavioral design patterns by combining source code and execution data. The framework has been instantiated for the observer, state and strategy patterns to demonstrate its applicability. By experimental evaluation, we show that our combined approach can guarantee a higher precision and recall than purely static approaches. In addition, our approach can discover all missing roles and return complete pattern instances that cannot be supported by existing approaches.

Original language	English
Title of host publication	Proceedings - International Conference on Software Engineering
Publisher	IEEE Computer Society
Pages	234-235
Number of pages	2
ISBN (Electronic)	9781450356633
DOIs	https://doi.org/10.1145/3183440.3194947
Publication status	Published - 27 May 2018
Event	40th International Conference on Software Engineering (ICSE 2018) - Gothenburg, Sweden Duration: 27 May 2018 → 3 Jun 2018 Conference number: 40 https://www.icse2018.org/home

Conference

Conference	40th International Conference on Software Engineering (ICSE 2018)
Abbreviated title	ICSE 2018
Country/Territory	Sweden
City	Gothenburg
Period	27/05/18 → 3/06/18
Internet address	https://www.icse2018.org/home

Keywords

behavioral design pattern
discovery and detection
general framework
pattern instance invocation
Behavioral Design Pattern
General Framework
Pattern Instance Invocation
Discovery and Detection

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10.1145/3183440.3194947

Cite this

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title = "A general framework to detect behavioral design patterns",

abstract = "This paper presents a general framework to detect behavioral design patterns by combining source code and execution data. The framework has been instantiated for the observer, state and strategy patterns to demonstrate its applicability. By experimental evaluation, we show that our combined approach can guarantee a higher precision and recall than purely static approaches. In addition, our approach can discover all missing roles and return complete pattern instances that cannot be supported by existing approaches.",

keywords = "behavioral design pattern, discovery and detection, general framework, pattern instance invocation, Behavioral Design Pattern, General Framework, Pattern Instance Invocation, Discovery and Detection",

author = "Cong Liu and {van Dongen}, Boudewijn and Nour Assy and {van der Aalst}, {Wil M.P.}",

year = "2018",

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language = "English",

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booktitle = "Proceedings - International Conference on Software Engineering",

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AU - Assy, Nour

AU - van der Aalst, Wil M.P.

N1 - Conference code: 40

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AB - This paper presents a general framework to detect behavioral design patterns by combining source code and execution data. The framework has been instantiated for the observer, state and strategy patterns to demonstrate its applicability. By experimental evaluation, we show that our combined approach can guarantee a higher precision and recall than purely static approaches. In addition, our approach can discover all missing roles and return complete pattern instances that cannot be supported by existing approaches.

KW - behavioral design pattern

KW - discovery and detection

KW - general framework

KW - pattern instance invocation

KW - Behavioral Design Pattern

KW - General Framework

KW - Pattern Instance Invocation

KW - Discovery and Detection

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DO - 10.1145/3183440.3194947

M3 - Conference contribution

AN - SCOPUS:85049676389

SP - 234

EP - 235

BT - Proceedings - International Conference on Software Engineering

PB - IEEE Computer Society

T2 - 40th International Conference on Software Engineering (ICSE 2018)

Y2 - 27 May 2018 through 3 June 2018

ER -

A general framework to detect behavioral design patterns

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Keywords

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