Application of Java Relationship Graphs (JRG) to plagiarism detection in Java Projects: A Neo4j Graph Database Approach

Arora, Ritu; Maurya, Arun Motilal; Sharma, Yashvardhan

doi:10.1145/3451471.3451479

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…The Class Collaboration Network (CCN) is particularly interesting to analyze [10], [32], [37], [38] because classes are the main building blocks in OOP. Arora and Goel [24], [27] proposed JavaRelationshipGraphs (JRG) -a software network model specialized for the Java language. JRG is a directed graph that captures various relations between different code elements in Java programs.…”

Section: A Code Dependency Representationsmentioning

confidence: 99%

“…In this section, we conduct a comparative analysis of various models as outlined in Section II, contrasting them with the SCG model within the context of software comprehension. We consider nine different code graph models in addition to the Semantic Code Graph (SCG): Control Flow Graph (CFG) [39], Program Dependence Graph (PDG) [41], Code Property Graph (CPG) [49], System Dependence Graph (SDG) [52], Java System Dependency Graph (JSysDG) [55], Call Graph (CG) [34], Class Collaboration Network (CCN) [32], Java Relationship Graphs (JRG) [24], and General Dependency Network (GDN) [29].…”

Section: Software Comprehension Capabilities: Comparison Of Scg and O...mentioning

confidence: 99%

“…• retrofit 23 -a type-safe HTTP client for Android and Java, • commons-io 24 -the Apache Commons IO library containing utility classes, stream implementations, file filters, file comparators, endian transformation classes, • playframework 25 -high velocity web framework for building web applications with Java & Scala, • metals 26 -Scala language server with rich IDE features, • glide 27 -media management and image loading framework for Android that wraps media decoding, memory and disk caching, and resource pooling into a simple and easy to use interface, • vert.x 28 -toolkit to build reactive applications on JVM;…”

Section: Empirical Software Comprehension With Semantic Code Graphmentioning

confidence: 99%

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Semantic Code Graph—An Information Model to Facilitate Software Comprehension

Borowski,

Balis,

Orzechowski

2024

IEEE Access

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Software comprehension can be extremely time-consuming due to the ever-growing size of codebases. Consequently, there is an increasing need to accelerate the code comprehension process to facilitate maintenance and reduce associated costs. A crucial aspect of this process is understanding and preserving the high quality of the code dependency structure. While a variety of code structure models already exist, there is a surprising lack of models that closely represent the source code and focus on software comprehension. As a result, there are no readily available and easy-to-use tools to assist with dependency comprehension, refactoring, and quality monitoring of code. To address this gap, we propose the Semantic Code Graph (SCG), an information model that offers a detailed abstract representation of code dependencies with a close relationship to the source code. We establish the critical properties of the SCG model and demonstrate its implementation for Java and Scala languages. To validate the SCG model's usefulness in software comprehension, we compare it to nine other source code representation models. Additionally, we select 11 well-known and widelyused open-source projects developed in Java and Scala and perform a range of software comprehension activities on them using three different code representation models: the proposed SCG, the Call Graph, and the Class Collaboration Network. We then qualitatively analyze the results to compare the performance of these models in terms of software comprehension capabilities. These activities encompass project structure comprehension, identifying critical project entities, interactive visualization of code dependencies, and uncovering code similarities through software mining. Our findings demonstrate that the SCG enhances software comprehension capabilities compared to the prevailing Class Collaboration Network and Call Graph models. Moreover, the SCG-based data analysis yields actionable software comprehension insights. We also release an open-source tool, scg-cli, to assist with result reproduction and further research. We believe that the work described is a step towards the next generation of tools that streamline code dependency comprehension and management.

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