Winnowing: local algorithms for document fingerprinting

By Saul Schleimer, Daniel Shawcross Wilkerson, A. Aiken. 2003

1,378 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Information Retrieval & Search, Algorithms & Complexity

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Citations in the corpus

Foundation Models and Fair Use (2023, methodology): “We thank Alex Aiken for generously providing us with access to MossPlus—the commercial version of Moss.”
CP-Miner: finding copy-paste and related bugs in large-scale software code (2006, background): “Index Terms—Software analysis, code reuse, code duplication, debugging aids, data mining.”
Attack of the Clones: Detecting Cloned Applications on Android Markets (2012, methodology): “Winnowing [40] attempts to find plagiarism with modifications using k-grams, by finding common token substrings of length k.”
Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods (2012, neutral): “Fingerprint [115], [116] and hash-based [117], [118] are com-”
A study of the uniqueness of source code (2010, methodology): “Schleimer et al. s MOSS [19] uses a form of document .ngerprinting to scalably characterize likely-plagiarized software.”
BitShred: feature hashing malware for scalable triage and semantic analysis (2011, methodology): “Here we discuss another called Winnowing.”
GPLAG: detection of software plagiarism by program dependence graph analysis (2006, methodology): “We spent two hours plagiarizing it such that both Moss and JPlag were confused.”
Using web corpus statistics for program analysis (2014, methodology): “In this section we analyze the effectiveness of our corpusdriven filters in improving the accuracy of plagiarism reports fromMOSS [25], a widely-used modern plagiarism detector that can process JavaScript programs.”
Learning to Fuzz: Application-Independent Fuzz Testing with Probabilistic, Generative Models of Input Data (2016, background): “, to find anomalies that correspond to bugs [36], for code completion [12], to recommend API usages [50], for plagiarism detection [31, 46], and to find copy-paste bugs [29].”
The Algorithm Design Manual (2020, methodology): “See [SWA03] for the interesting details of how to implement a plagiarism detector for computer programs.”
CP-Miner: A Tool for Finding Copy-paste and Related Bugs in Operating System Code (2004, background): “JPlag [33], Moss [35], and sif [30] are tools to find similar programs among a given set.”
DECKARD: Scalable and Accurate Tree-Based Detection of Code Clones (2007, methodology): “Example tools include Moss [20] and JPlag ( http://www.jplag.de ).”