Scalable detection of semantic clones

By Mark Gabel, Lingxiao Jiang, Zhendong Su. 2008 ACM/IEEE 30th International Conference on Software Engineering, 2008

384 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/a325f5c196ba7ca8dd240e441a3981d69fe4714d

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Citations in the corpus

Comparison and evaluation of code clone detection techniques and tools: A qualitative approach (2009, methodology): “Another recent study by Gabel et al. [46] maps PDG subgraphs to related structured syntax and then ﬁnds clones using Deckard .”
Achieving accuracy and scalability simultaneously in detecting application clones on Android markets (2014, methodology): “The time complexity of this reduction is O ( n 3 ) ( n is the number of nodes in a PDG).”
Juxtapp: A Scalable System for Detecting Code Reuse among Android Applications (2012, background): “A variety of approaches for static code clone detection have been proposed in the programming language literature for refactoring, finding bugs, and better understanding of the code [21, 27, 29, 25].”
Using web corpus statistics for program analysis (2014, methodology): “Existing plagiarism detection algorithms can be categorized into one of the following types: string-based, token-based [7, 11, 22, 25], abstract-syntax-tree-based [4, 10], and program-dependence-graph-based [6, 13, 16].”
Do code clones matter? (2009, background): “• Tree [3,8,12] and graph [9,19,22] based approaches require the availability of suitable context free grammars for AST or PDG construction.”
Semantic code search via equational reasoning (2020, methodology): “PDGs abstract away the exact ordering of statements in favor of identifying when one statement uses the result of another (data dependence) or is guarded by a condition (control dependence).”
A Large-Scale Study on Repetitiveness, Containment, and Composability of Routines in Open-Source Projects (2016, methodology): “Prior research has used program dependence graph (PDG) [17] to model the semantics of source code for comparison [20, 36, 30].”
DeepSim: deep learning code functional similarity (2018, background): “However, they either do not scale due to the complexity of graph isomorphism [13], or are imprecise due to the approximations made for improving scalability (e.g., mapping the subgraphs in PDG back to AST forest and comparing syntactical feature vectors extracted from AST [17]).”