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On the compressibility of large-scale source code datasets

JOURNAL OF SYSTEMS AND SOFTWARE 2025年 227卷

作者： Boffa, Antonio Di Cosmo, Roberto Ferragina, Paolo Guerra, Andrea Manzini, Giovanni Vinciguerra, Giorgio Zacchiroli, Stefano Ecole Polytech Fed Lausanne EPFL Lausanne Switzerland Inria Paris France Univ Paris Cite Paris France St Anna Sch Adv Studies Dept EMbeDS Pisa Italy Univ Pisa Dept Comp Sci Pisa Italy Inst Polytech Paris LTCI Telecom Paris Palaiseau France

Storing ultra-large amounts of unstructured data (often called objects or blobs) is a fundamental task for several object-based storage engines, data warehouses, data-lake systems, and key-value stores. These systems cannot currently leverage similarities between objects, which could be vital in improving their space and time performance. An important use case in which we can expect the objects to be highly similar is the storage of large-scale versioned source code datasets, such as the Software Heritage Archive (Di Cosmo and Zacchiroli, 2017). This use case is particularly interesting given the extraordinary size (1.5 PiB), the variegated nature, and the high repetitiveness of the at-issue corpus. In this paper we discuss and experiment with content-and context-based compression techniques for source-code collections that tailor known and novel tools to this setting in combination with state-of-the-art general-purpose compressors and the information coming from the Software Heritage Graph. We experiment with our compressors over a random sample of the entire corpus, and four large samples of source code files written in different popular languages: C/C++, Java, JavaScript, and Python. We also consider two scenarios of usage for our compressors, called Backup and File-Access scenario, where the latter adds to the former the support for single file retrieval. As a net result, our experiments show (i) how much "compressible" each language is, (ii) which content-or context-based techniques compress better and are faster to (de)compress by possibly supporting individual file access, and (iii) the ultimate compressed size that, according to our estimate, our best solution could achieve in storing all the source code written in these languages and available in the Software Heritage Archive: namely, in 3 TiB (down from their original 78 TiB total size, with an average compression ratio of 4%).

关键词： Data compression source code Storage systems Locality-sensitive hashing Software Heritage Version control systems

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Employing Blockchain, NFTs, and Digital Certificates for Unparalleled Authenticity and Data Protection in source code: A Systematic Review

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COMPUTERS 2025年第4期14卷 131-131页

作者： Lopez, Leonardo Juan Ramirez Ledezma, Genesis Gabriela Morillo Univ El Bosque Engn Fac Osiris & Bioaxis Res Grp Bogota 111321 Colombia

In higher education, especially in programming-intensive fields like computer science, safeguarding students' source code is crucial to prevent theft that could impact learning and future careers. Traditional storage solutions like Google Drive are vulnerable to hacking and alterations, highlighting the need for stronger protection. This work explores digital technologies that enhance source code security, with a focus on Blockchain and NFTs. Due to Blockchain's decentralized and immutable nature, NFTs can be used to control code ownership, improving security, traceability, and preventing unauthorized access. This approach effectively addresses existing gaps in protecting academic intellectual property. However, as Bennett et al. highlight, while these technologies have significant potential, challenges remain in large-scale implementation and user acceptance. Despite these hurdles, integrating Blockchain and NFTs presents a promising opportunity to enhance academic integrity. Successful adoption in educational settings may require a more inclusive and innovative strategy.

关键词： blockchain data protection digital certificates non-fungible tokens (NFTs) source code

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source code Plagiarism-A Student Perspective

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IEEE TRANSACTIONS ON EDUCATION 2011年第1期54卷 125-132页

作者： Joy, Mike Cosma, Georgina Yau, Jane Yin-Kim Sinclair, Jane Univ Warwick Dept Comp Sci Coventry CV4 7AL W Midlands England PA Coll Larnax Cyprus

This paper considers the problem of source code plagiarism by students within the computing disciplines and reports the results of a survey of students in Computing departments in 18 institutions in the U. K. This survey was designed to investigate how well students understand the concept of source code plagiarism and to discover what, if any, specific aspects might cause particular confusion. An analysis of the results was carried out to assess understanding by topic and to discover whether various demographic factors may have an influence on that understanding. Within the survey sample, it appeared that the demographic factors tested did not generally affect students' understanding of source code plagiarism. However, analysis of the data for specific topics revealed that there are several areas of activity where the boundary between acceptable and unacceptable behavior is not clearly understood. These findings have implications for plagiarism education programs.

关键词： Computing disciplines plagiarism source code student survey university education

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PDetect: A clustering approach for detecting plagiarism in source code datasets

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COMPUTER JOURNAL 2005年第6期48卷 651-661页

作者： Moussiades, L Vakali, A Inst Educ Technol Dept Ind Informat Div Comp Syst GR-65404 Kavala Greece Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece

Efficient detection of plagiarism in programming assignments of students is of a great importance to the educational procedure. This paper presents a clustering oriented approach for facing the problem of source code plagiarism. The implemented software, called PDetect, accepts as input a set of program sources and extracts subsets (the clusters of plagiarism) such that each program within a particular subset has been derived from the same original. PDetect proposes the use of an appropriate measure for evaluating plagiarism detection performance and supports the idea of combining different plagiarism detection schemes. Furthermore, a cluster analysis is performed in order to provide information beneficial to the plagiarism detection process. PDetect is designed such that it may be easily adapted over any keyword-based programming language and it is quite beneficial when compared with earlier (state-of-the-art) plagiarism detection approaches.

关键词： Plagiarism source code Cluster Analysis

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source code Representations for Plagiarism Detection 7th

Source Code Representations for Plagiarism Detection

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7th International Workshop on Learning Technology for Education Challenges (LTEC)

作者： Duracik, Michal Krsak, Emil Hrkut, Patrik Univ Zilina Fac Management Sci & Informat Univ 8215-1 Zilina 01026 Slovakia

ISBN: (纸本)9783319955223;9783319955216

At the present time the plagiarism is a growing problem due to a lot of easily accessible resources, and many papers deal with this topic. New algorithms are constantly being created, but there are not currently manny of systems, that we could use for plagiarism detection. Our aim is to explore plagiarism on a large scale. This paper focuses on selecting the appropriate representation of the source code, that is very important when searching for plagiarism. There is an overview of the current representation possibilities. We focus on representation source code using AST. Comparison of the tree structures is time-consuming operation. We will try to find how effectively represent AST in order to facilitate comparison. There are two ways to represent AST. Representation by hashing or using characteristic vectors. We present the experiment and results on which we choose the appropriate form of the representation.

关键词： source code Representations Hash Characteristic vector

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Detection of source code Similitude in Academic Environments

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2015年第1期23卷 13-22页

作者： Bejarano, Andres M. Garcia, Lucy E. Zurek, Eduardo E. Univ Norte Dept Syst Engn Barranquilla Atlantico Colombia

This article presents a proposal for the detection of programming source code similitude in academic environments. The objective of this proposal is to provide support to professors in detecting plagiarism in student homework assignments in introductory computer programming courses. The developed tool, codeSIGHT, is based on a modification of the Greedy String Tiling algorithm. The tool was tested in one theoretical and three real scenarios, obtaining similitude detections for assignments ranging from those that contained code without modifications to assignments containing insertions of procedural instructions inside the main code. The results verified the efficiency of the tool at the first five levels of the plagiarism spectrum for programming code, in addition to supporting suspicions of plagiarism in real scenarios. (c) 2013 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:13-22, 2015;View this article online at;DOI

关键词： plagiarism computer programming source code

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Viewing functions as token sequences to highlight similarities in source code

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SCIENCE OF COMPUTER PROGRAMMING 2013年第10期78卷 1871-1891页

作者： Chilowicz, Michel Duris, Etienne Roussel, Gilles Univ Paris Est Lab Informat Gaspard Monge CNRS UMR 8049 F-77454 Marne La Vallee 2 France

The detection of similarities in source code has applications not only in software re-engineering (to eliminate redundancies) but also in software plagiarism detection. This later can be a challenging problem since more or less extensive edits may have been performed on the original copy: insertion or removal of useless chunks of code, rewriting of expressions, transposition of code, inlining and outlining of functions, etc. In this paper, we propose a new similarity detection technique not only based on token sequence matching but also on the factorization of the function call graphs. The factorization process merges shared chunks (factors) of codes to cope, in particular, with inlining and outlining. The resulting call graph offers a view of the similarities with their nesting relations. It is useful to infer metrics quantifying similarity at a function level. (C) 2012 Elsevier B.V. All rights reserved.

关键词： source code Duplication Clones Similarity Factorization Inlining Outlining Call graph Suffix indexation

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Meta-Heuristic Guided Feature Optimization for Enhanced Authorship Attribution in Java source code

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IEEE ACCESS 2023年 11卷 141657-141673页

作者： Al-Ahmad, Bilal Al-Madi, Nailah Alzaqebah, Abdullah Alkhawaldeh, Rami S. Aldebei, Khaled Kabir, Md. Faisal Altaharwa, Ismail Abu-Faraj, Mua'ad Aljarah, Ibrahim Univ Jordan Aqaba 77110 Jordan St Cloud State Univ Dept Comp Sci & Informat Technol St Cloud MN 56301 USA Princess Sumaya Univ Technol Amman 11941 Jordan Al Ahliyya Amman Univ Fac Informat Technol Comp Sci Dept Amman 19628 Jordan Penn State Univ Harrisburg Sch Sci Engn & Technol Middletown PA 17057 USA Univ Jordan Amman 11942 Jordan

source code authorship attribution is the task of identifying who develops the code based on learning based on the programmer style. It is one of the critical activities which used extensively in different aspects such as computer security, computer law, and plagiarism. This paper attempts to investigate source code authorship attribution by capturing natural language aspects of the code rather than only using minimal set of syntactic and stylistic code features as explored in the previous literature. It proposes an evolutionary feature selection model to improve the accuracy of authorship attribution by implementing two language models (uni-gram and bi-gram). The proposed approach uses K-Nearest Neighbor as a classifier and Genetic Algorithm as a feature selection technique. Two experiments have been demonstrated on a public Authorship Attribution dataset on GitHub, the experiments include various evolutionary feature selection models. Notably, the obtained results in both experiments were compared with the related studies, and show a significant improvement in terms of accuracy.

关键词： source coding Feature extraction Genetic algorithms codes Task analysis Java Classification algorithms Evolutionary computation data mining feature selection java source code authorship attribution

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Examining the significance of high-level programming features in source code author classification

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JOURNAL OF SYSTEMS AND SOFTWARE 2008年第3期81卷 447-460页

作者： Frantzeskou, Georgia MacDonell, Stephen Stamatatos, Efstathios Gritzalis, Stefanos Univ Aegean Dept Informat & Commun Syst Engn Samos 83200 Greece Auckland Univ Technol Sch Comp & Math Sci Auckland 1020 New Zealand

The use of source code Author Profiles (SCAP) represents a new, highly accurate approach to source code authorship identification that is, unlike previous methods, language independent. While accuracy is clearly a crucial requirement of any author identification method, in cases of litigation regarding authorship, plagiarism, and so on, there is also a need to know why it is claimed that a piece of code is written by a particular author. What is it about that piece of code that suggests a particular author? What features in the code make one author more likely than another? In this study, we describe a means of identifying the high-level features that contribute to source code authorship identification using as a tool the SCAP method. A variety of features are considered for Java and Common Lisp and the importance of each feature in determining authorship is measured through a sequence of experiments in which we remove one feature at a time. The results show that, for these programs, comments, layout features and package-related naming influence classification accuracy whereas user-defined naming, an obvious programmer related feature, does not appear to influence accuracy. A comparison is also made between the relative feature contributions in programs written in the two languages. (C) 2007 Elsevier Inc. All rights reserved.

关键词： authorship source code program features fraud

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An analysis of programming language statement frequency in C, C plus plus , and Java source code

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SOFTWARE-PRACTICE & EXPERIENCE 2015年第11期45卷 1479-1495页

作者： Zhu, Xiaoyan Whitehead, E. James Sadowski, Caitlin Song, Qinbao Xi An Jiao Tong Univ Xian 710049 Shaanxi Peoples R China Univ Calif Santa Cruz Santa Cruz CA 95064 USA

Statement frequency data can inform programming language research and provide a solid basis for frequency-based code analysis. This paper presents an analysis of programming language statement frequency in a large corpus of C, C++, and Java source code, comprised of more than 54 million lines of code. Across these languages, the top four work-performing statement types are Method/Function Call, Assignment, If, and Return. As compared to studies of Formula Translating System, Common Business Oriented Language and Programming Language One in the 1970s, the main change is the prevalence of method/function calls. Statement use frequency across languages is remarkably similar, and within each individual language, most statement types have a frequency distribution that occupies a small range. A more detailed examination of assignment and looping statement types shows that many assignments simply involve copying of data and that C++/Java use for statements more than C. Copyright (C) 2014 John Wiley & Sons, Ltd.

关键词： statement frequency metrics source code

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