Distinguishing Similar Design Pattern Instances through Temporal Behavior Analysis

Xiong, Renhao; Lo, David; Li, Bixin

doi:10.1109/saner48275.2020.9054804

Cited by 3 publications

(3 citation statements)

References 47 publications

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“…In order to calculate precision and recall of each tool, we identified the true instances of each pattern in the projects used for benchmarking. We established the ground truth through manual inspection and validated with other results [15,17]. We compared unique instances of patterns retrieved by Pat-ternScout with Finder [18] and DPD [12].…”

Section: Comparing Patternscout With Existing Toolsmentioning

confidence: 99%

“…We compared unique instances of patterns retrieved by Pat-ternScout with Finder [18] and DPD [12]. While SparT [17] was also evaluated, we excluded it from the analysis as the off-the-shelf implementation did not include specifications for creational and structural patterns. We excluded Tools that are unavailable for download (e.g., [19,20]) or those for which a core dependency is deprecated (e.g., [21,15]) from the comparison.…”

Section: Comparing Patternscout With Existing Toolsmentioning

confidence: 99%

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Towards Lightweight Detection of Design Patterns in Source Code

Poozhithara¹,

Asuncion²,

Lagesse³

2022

Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering

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Identifying which design patterns exist in source code helps maintenance engineers better understand source code and determine if new requirements can be satisfied. Automated techniques for finding design patterns generally require much time to label training datasets or to specify rules/queries for each pattern, and is difficult to extend support to secure design patterns (SDPs) and combination patterns. To address these challenges, we introduce PatternScout, a technique for automatic generation of SPARQL queries from UML Class diagrams and Sequence diagrams. These queries are used to detect patterns in the source code. Our results indicate that PatternScout can detect object-oriented design patterns (OODP) with accuracy that is comparable or better than existing techniques. It can also generate queries for SDPs that can be represented as UML Class diagrams.

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Section: Comparing Patternscout With Existing Toolsmentioning

confidence: 99%

Section: Comparing Patternscout With Existing Toolsmentioning

confidence: 99%

Towards Lightweight Detection of Design Patterns in Source Code

Poozhithara¹,

Asuncion²,

Lagesse³

2022

Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering

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show abstract

“…Design pattern detection using structural analysis: This approach depends on transforming both the system under study and the design patterns into intermediate structures such as graphs and matrices. After that, the detection algorithm looks within the system structure for structures that represent specific design patterns [9,13,[21][22][23][24][25][26][27][28][29]. Methods that depend on structural analysis have high accuracy [10,11].…”

Section: Detection Approachesmentioning

confidence: 99%

A Feature-Based Method for Detecting Design Patterns in Source Code

Kouli

Rasoolzadegan

2022

Symmetry

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Design patterns are common solutions to existing issues in software engineering. In recent decades, design patterns have been researched intensively because they increase the quality factors of software systems such as flexibility, maintainability, and reusability. Design pattern detection refers to the determination of the symmetry between a code fragment and the definition of a design pattern. One of the major challenges in design pattern detection is how to obtain accurate information about the design patterns used in the software system due to the existence of different design pattern variants. Increasing the number of design pattern variants covered by a detection method is one of the main factors that increase its accuracy. In this paper, a step toward solving this challenge was taken by proposing a new feature-based method that builds on concrete definitions of existing design pattern variants and supports the definition and detection of new variants. In this proposed method, the needed features are extracted from the signatures of the design patterns. This method was applied to the 23 Gang of Four (GoF) design patterns and evaluated using four open-source Java projects. Afterward, it was compared with some previous methods using automatically generated testbeds. The experimental results demonstrated that the proposed method has better performance in terms of precision and recall compared to the other methods.

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Towards More Precise Descriptions of Design Patterns

Doorn

Stuurman

2022

Lecture Notes in Networks and Systems

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Distinguishing Similar Design Pattern Instances through Temporal Behavior Analysis

Cited by 3 publications

References 47 publications

Towards Lightweight Detection of Design Patterns in Source Code

Towards Lightweight Detection of Design Patterns in Source Code

A Feature-Based Method for Detecting Design Patterns in Source Code

Towards More Precise Descriptions of Design Patterns

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