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review-article

Definition, approaches, and analysis of code duplication detection (2006–2020): a critical review

Published: 01 December 2022 Publication History

Abstract

Code duplication detection is the act of finding similar code in software development. It is important for software engineer to address the issues of code duplication detection. In this paper, a critical review of previous works on code duplication for code clone and plagiarism detection is performed. The review involves five main parts. Firstly, a systematic literature review is conducted to confirm the selected articles. Secondly, a critical review of different code duplication approaches is conducted based on three phases; processing, detection, and decision. Thirdly, statistical analysis of the number of review articles is performed to show the trends and hots of code duplication research. Moreover, quantitative analysis of different code duplication approaches is presented to show the effectiveness of different approaches. Fourthly, the advantages and disadvantages of different approaches and techniques are summarized and discussed. Finally, the conclusion of the review is summarized and future research direction of code duplication is described.

References

[1]
Zhenzhou T et al (2016) Software plagiarism detection: a survey. J Cyber Secur. 1(3). [Online]. Available: https://faculty.ist.psu.edu/wu/papers/spd-survey-16.pdf
[2]
Tian Z, Liu T, Zheng Q, Fan M, Zhuang E, and Yang Z Exploiting thread-related system calls for plagiarism detection of multithreaded programs J Syst Softw 2016 119 136-148
[3]
Cosma G and Joy M Towards a Definition of source-code plagiarism IEEE Trans Educ 2008 51 2 195-200
[4]
Kamiya T, Kusumoto S, and Inoue K CCFinder: a multilinguistic token-based code clone detection system for large scale source code IEEE Trans Softw Eng 2002 28 7 654-670
[5]
Kalinowsky LB Indications and management of various somatic treatment in present day psychiatry Proc Rudolf Virchow Med Soc City NY 1972 28 172-174
[6]
Parker A and Hamblen JO Computer algorithms for plagiarism detection IEEE Trans Educ 1989 32 2 94-99
[7]
Yamamoto T, Matsushita M, Kamiya T, and Inoue K Measuring similarity of large software systems based on source code correspondence Lect Notes Comput Sci 2005 3547 530-544
[8]
Ain QU, Butt WH, Anwar MW, Azam F, and Maqbool B A Systematic review on code clone detection IEEE Access 2019 7 86121-86144
[9]
Hua W, Sui Y, Wan Y, Liu G, and Xu G FCCA: hybrid code representation for functional clone detection using attention networks IEEE Trans Reliab 2021 70 1 304-318
[10]
Reinhartz-Berger I and Zamansky A Reuse of similarly behaving software through polymorphism-inspired variability mechanisms IEEE Trans Softw Eng 2022 48 3 773-785
[11]
Sheneamer AM An automatic advisor for refactoring software clones based on machine learning IEEE Access 2020 8 124978-124988
[12]
Wu M, Wang P, Yin K, Cheng H, Xu Y, and Roy CK LVMapper: a large-variance clone detector using sequencing alignment approach IEEE Access 2020 8 27986-27997
[13]
Karnalim O IR-based technique for linearizing abstract method invocation in plagiarism-suspected source code pair J King Saud Univ Comput Inf Sci 2019 31 3 327-334
[14]
Ragkhitwetsagul C, Krinke J (2017) Using compilation/decompilation to enhance clone detection. In: 11th international workshop on software clone, pp 8–14
[15]
Kim S and Lee H Software systems at risk: an empirical study of cloned vulnerabilities in practice Comput Secur 2018 77 720-736
[16]
Yu D et al. Detecting Java code clones with multi-granularities based on bytecode Proc Int Comput Softw Appl Conf 2017 1 317-326
[17]
Kim S, Woo S, Lee H, Oh H (2017) VUDDY: a scalable approach for vulnerable code clone discovery. In: proceedings - IEEE symposium on security and privacy, pp 595–614,
[18]
Lyu F, Lin Y, Yang J, Zhou J (2016) SUIDroid: an efficient hardening-resilient approach to android app clone detection. Proceedings - 15th IEEE international conference on trust security and privacy comput communication 10th IEEE international conference big data science engineering 14th IEEE international symposium on parallel distribution proce, pp 511–518.
[19]
Xue H, Sun S, Venkataramani G, and Lan T Machine learning-based analysis of program binaries: a comprehensive study IEEE Access 2019 7 65889-65912
[20]
Jadon S Code clones detection using machine learning technique: support vector machine Proc IEEE Int Conf Comput Commun Autom ICCCA 2017 2016 303-309
[21]
Nakamura Y, Choi E, YoshidaN, Haruna S, Inoue K (2016) Towards detection and analysis of interlanguage clones for multilingual web applications. In: 2016 IEEE 23rd International conference on software Anal. Evol. Reengineering, SANER 2016, pp 17–18.
[22]
Li B, Ye C, Guan S, Zhou H (2020) Semantic code clone detection via event embedding tree and GAT network. In: Proc - 2020 IEEE 20th international conference software quality, reliability and security QRS 2020, vol 3. pp 382–393.
[23]
Svajlenko J, Islam JF, Keivanloo I, Roy CK, Mia MM (2014) Towards a big data curated benchmark of inter-project code clones. In: Proceedings - 30th international conference software maintenance and evolution ICSME 2014, vol 476. pp 476–480.
[24]
Saini V, Farmahinifarahani F, Lu Y, Baldi P, Lopes CV (2018) Oreo: detection of clones in the twilight zone. In: ESEC/FSE 2018 - proceedings of the 2018 26th ACM joint meeting on European software engineering conference and symposium on the foundations of software engineering. pp 354–365.
[25]
Zeng J, Ben K, Li X, and Zhang X Fast code clone detection based on weighted recursive autoencoders IEEE Access 2019 7 125062-125078
[26]
Roy CK and Cordy JR NICAD: accurate detection of near-miss intentional clones using flexible pretty-printing and code normalization IEEE Int Conf Progr Compr 2008
[27]
Zhang PY, Chen CM, and Huang B “Texts similarity algorithm based on subtrees matching”, Moshi Shibie yu Rengong Zhineng/Pattern Recognit Artif Intell 2014 27 3 226-234
[28]
Kodhai E, Kanmani S, Kamatchi A, Radhika R, Vijaya Saranya B (2010) Detection of type-1 and type-2 code clones using textual analysis and metrics. In: ITC 2010 - 2010 international conference recent trends information, telecommunication comput, pp 241–243.
[29]
Chen J, Alalfi MH, Dean TR, and Zou Y Detecting android malware using clone detection J Comput Sci Technol 2015 30 5 942-956
[30]
Ji JH, Woo G, Cho HG (2007) A source code linearization technique for detecting plagiarized programs. In: ITiCSE 2007 12th annual SIGCSE conference on Innovation and technology in computer science education. pp 73–77.
[31]
Kustanto C, Liem I (2009) Automatic source code plagiarism detection. In: 10th ACIS International conference on software engineering, artificial intelligences, networking and parallel/distributed computing. SNPD 2009, conjunction with IWEA 2009 WEACR 2009. pp 481–486.
[32]
Han L, Cui B, Zhang R, Li Z, Wang J, Hao Y. Type redefinition plagiarism detection of token-based comparison. In: 2010 international conference on multimedia information networking and security. pp 351–355.
[33]
Toomey W (2012) Ctcompare: code clone detection using hashed token sequences. In: 2012 6th international workshop software clones, IWSC 2012 - proceedings, pp 92–93.
[34]
Yuan Y, Guo Y (2012) Boreas: an accurate and scalable token-based approach to code clone detection. In: 2012 27th IEEE/ACM international conference on automation software engineering ASE 2012 - proceedings, pp 286–289.
[35]
Farhadi MR, Fung BCM, Fung YB, Charland P, Preda S, and Debbabi M Scalable code clone search for malware analysis Digit Investig 2015 15 46-60
[36]
Sajnani H, Saini V, Svajlenko J, Roy CK, and Lopes CV SourcererCC 2016 1 1157-1168
[37]
Li L, Feng H, Zhuang W, Meng N, Ryder B (2017) CCLearner: a deep learning-based clone detection approach. In: Proceedings - 2017 IEEE international conference software maintenance evolution ICSME 2017, pp 249–260.
[38]
Semura Y, Yoshida N, Choi E, and Inoue K CCFinderSW: clone detection tool with flexible multilingual tokenization Proc Asia-Pacific SoftwEng Conf APSEC 2018 2017 654-659
[39]
Wang P, Svajlenko J, Wu Y, Xu Y, Roy CK (2018) CCAligner: a token based large-gap clone detector. In: Proceedings international conference software angering, pp 1066–1077.
[40]
Wan H, Liu K, Gao X (2019) Token-based approach for real-time plagiarism detection in digital designs. In: Proceedings frontiers education confference FIE. vol 2018-Octob, pp 1–5.
[41]
Sulistiani L and Karnalim O ES-Plag: efficient and sensitive source code plagiarism detection tool for academic environment Comput Appl Eng Educ 2019 27 1 166-182
[42]
Koschke R, Falke R, Frenzel P (2006) Clone detection using abstract syntax suffix trees. In: Proceedings - workshop conference reverse engineering. WCRE, pp 253–262.
[43]
Jiang L, Misherghi G, Su Z, and Glondu S DECKARD: scalable and accurate tree-based detection of code clones Proc - Int Conf Softw Eng 2007 0520320 96-105
[44]
Xiong H, Yan H, Li Z, Li H (2009) BUAA-AntiPlagiarism: a system to detect plagiarism for C source code. In: Proceedings - 2009 international conference computational intelligence software engineering CiSE 2009, pp 1–5.
[45]
Zhang L, Liu D, Li Y, and Zhong M AST-based plagiarism detection method Commun Comput Inf Sci 2012 312 611-618
[46]
Son JW, Noh TG, Song HJ, and Park SB An application for plagiarized source code detection based on a parse tree kernel Eng Appl Artif Intell 2013 26 8 1911-1918
[47]
Tao G, Guowei D, Hu Q, Baojiang C (2013) Improved plagiarism detection algorithm based on abstract syntax tree. In: Proceeding - 4th international conference emerging intelligent data web technol. EIDWT 2013, pp 714–719.
[48]
Kikuchi H, Goto T, Wakatsuki M, Nishino T (2014) A source code plagiarism detecting method using alignment with abstract syntax tree elements. In: 2014 IEEE/ACIS 15th International Conference Software Engineering Artificial Intelligence Network Parallel/Distributed Comput SNPD 2014 – Proceeding.
[49]
Resmi NG and Soman KP Abstract syntax tree generation using modified grammar for source code plagiarism detection IJCAT Int J Comput Technol 2014 1 6 319-326
[50]
Nan LIU, Li-fang HAN, Kun-feng XIA, Tong QU (2014) An improved algorithm based on abstract syntax tree for source code plagiarism detection.
[51]
Song HJ, Park SB, and Park SY Computation of program source code similarity by composition of parse tree and call graph” Math Probl Eng 2015
[52]
Chodarev S, Pietriková E, and Kollár J “Haskell clone detection using pattern comparing algorithm Int Conf Eng Mod Electr Syst EMES 2015 2015 1-4
[53]
Gan ST, Qin XJ, Chen ZN, and Wang LZ Software vulnerability code clone detection method based on characteristic metrics Ruan Jian Xue Bao/Journal Softw 2015 26 2 348-363
[54]
Fu D, Xu Y, Yu H, and Yang B WASTK: a weighted abstract syntax tree kernel method for source code plagiarism detection Sci Program 2017
[55]
Zou D et al. (2017) SCVD: a new semantics-based approach for cloned vulnerable code detection Lect Notes Comput Sci 2017 10327 LNCS 325-344
[56]
Yang Y, Ren Z, Chen X, Jiang H (2018) Structural function based code clone detection using a new hybrid technique. In: proceedings - international computational software applied conference. vol 1, pp 286–291.
[57]
Shen VRL Novel code plagiarism detection based on abstract syntax tree and fuzzy petri nets Int J Eng Educ 2019 1 1 46-56
[58]
Duracik M, Hrkut P, Krsak E, and Toth S Abstract syntax tree based source code antiplagiarism system for large projects set IEEE Access 2020 8 175347-175359
[59]
Wang W, Li G, Ma B, Xia X, Jin Z (2020) Detecting code clones with graph neural network and flow-augmented abstract syntax tree. In: SANER 2020 - Proceedings 2020 IEEE 27th international conference software anal evolution reengineering, pp 261–271.
[60]
Son J, Park S, Park S (2006) Program plagiarism detection using parse tree kernels. In: Pacific Rim international conference on artificial intelligence, pp 1000–1004
[61]
Merlo E Detection of plagiarism in University projects using metrics-based spectral similarity Duplic Redundancy Similarity Softw 2007 06301 1-10
[62]
Fukushima Y, Kula R, Kawaguchi S, Fushida K, Nagura M, Iida H (2009) Code clone graph metrics for detecting diffused code clones. In: Proceedings - Asia-Pacific software engineering conference APSEC, pp 373–380.
[63]
Perumal A, Kanmani S, Kodhai E (2010) Extracting the similarity in detected software clones using metrics. In: 2010 international conference comput. communication technol. ICCCT-2010, pp 575–579.
[64]
Choi E, Yoshida N, Ishio T (2011) Finding Code clones for refactoring with clone metrics: a case study of open source software. In: Proceedings. pp 1–5
[65]
Bansal G, Tekchandani R (2014) Selecting a set of appropriate metrics for detecting code clones. In: 2014 7th international conference contemp comput. IC3 2014, pp 484–488.
[66]
Aktas MS and Kapdan M Structural code clone detection methodology using software metrics Int J Softw Eng Knowl Eng 2016 26 2 307-332
[67]
Tsunoda M, Kamei Y, Sawada A (2016) Assessing the differences of clone detection methods used in the fault-prone module prediction. In: 2016 IEEE 23rd international conference software anal evolution reengineering, SANER 2016, pp 15–16.
[68]
Takahashi M, Anang Y, Nanba R, Watanabe Y (2018) An Efficient merging method for code clones and gapped code clones using software metrics. 5(1):1–11
[69]
Okutan A (2018) Use of source code similarity metrics in software defect prediction, pp 1–14. [Online]. Available: http://arxiv.org/abs/1808.10033
[70]
Kaur G and Sharma ES Metric level based code clone detection using optimized code manager Int J Eng Technol 2018 7 2.27 Special Issue 27 144-149
[71]
Choi E, Yoshida N, Ishio T, Inoue K, and Sano T Extracting code clones for refactoring using combinations of clone metrics Proc Int Conf Softw Eng 2011
[72]
Liu C, Chen C, Han J, Yu PS (2006) GPLAG: detection of software plagiarism by program dependence graph analysis ∗ categories and subject descriptors. In: KDD ’06 Proc. 12th ACM SIGKDD Int. Conf. Knowl. Discov. data minning, pp 872–881
[73]
Pham NH, Nguyen HA, Nguyen TT, Al-Kofahi JM, and Nguyen TN Complete and accurate clone detection in graph-based models Proc Int Conf Softw Eng 2009 January 276-286
[74]
Li J, Ernst MD (2012) CBCD: cloned buggy code detector. In: Proceeding - International Conference Software Engineering. pp 310–320.
[75]
Chae DK, Ha J, Kim SW, Kang BJ, Im EG (2013) Software plagiarism detection: a graph-based approach. In: Int. Conf. Inf. Knowl. Manag. Proc., pp 1577–1580.
[76]
Qu W, Jia Y, and Jiang M Pattern mining of cloned codes in software systems Inf Sci 2014 259 544-554
[77]
Wang B, Yang X, and Wang G Detecting copy directions among programs using extreme learning machines Math Prob Eng 2015 2015 1-15
[78]
Obaido GR (2017) Structural analysis of source code plagiarism using graphs. May
[79]
Kamalpriya CM, Singh P (2017) Enhancing program dependency graph based clone detection using approximate subgraph matching. In: IWSC 2017 - 11th IEEE international workshop on software clones, co-located with SANER 2017, pp 61–67.
[80]
Liu Z, Wei Q, Cao Y (2017) VFDETECT: a vulnerable code clone detection system based on vulnerability fingerprint. In: Proceedings 2017 IEEE 3rd Inf. technol. mechatronics engineering conference ITOEC 2017, vol 2017-Janua, pp 548–553.
[81]
Wang M, Wang P, Xu Y (2018) CCSharp: an efficient three-phase code clone detector using modified PDGs. In: Proc. - Asia-Pacific Softw. Eng. Conf. APSEC, vol 2017-Decem, pp 100–109.
[82]
Ullah F, Wang J, Jabbar S, Al-Turjman F, and Alazab M Source code authorship attribution using hybrid approach of program dependence graph and deep learning model IEEE Access 2019 7 141987-141999
[83]
Zou Yue XY and Ming Wu Design and implementation of high level code cloning detection method Comput Eng Sci 2020 42 07 1191-1196
[84]
Xinghao C Research on key technologies of clone code detection based on LLVM 2018 Nanjing Nanjing University of Posts and Telecommunications
[85]
Jhi YC, Jia X, Wang X, Zhu S, Liu P, and Wu D Program characterization using runtime values and its application to software plagiarism detection IEEE Trans Softw Eng 2015 41 9 925-943
[86]
Luo L, Ming J, Wu D, Liu P, and Zhu S Semantics-based obfuscation-resilient binary code similarity comparison with applications to software and algorithm plagiarism detection IEEE Trans Softw Eng 2017 43 12 1157-1177
[87]
Maryono D, Yuana RA, and Hatta P The analysis of source code plagiarism in basic programming course J Phys Conf Ser 2019 1193 012027
[88]
Martínez S, Wimmer M, and Cabot J Efficient plagiarism detection for software modeling assignments Comput Sci Educ 2020 30 2 187-215
[89]
Moussiades L and Vakali A PDetect: a clustering approach for detecting plagiarism in source code datasets Comput J 2005 48 6 651-661
[90]
Zhang L, Zhuang YT, and Yuvan ZM A program plagiarism detection model based on information distance and clustering Proc Int Conf Intell Pervasive Comput 2007 2 431-436
[91]
Abd-El-Hafiz SK A metrics-based data mining approach for software clone detection Proc Int Comput Softw Appl Conf 2012
[92]
Acampora G, Cosma G (2015) A fuzzy-based approach to programming language independent source-code plagiarism detection. In: IEEE international conference fuzzy system. vol 2015-Novem.
[93]
Mostafizer Rahman Md, Watanobe Y, and Nakamura K Source code assessment and classification based on estimated error probability using attentive lstm language model and its application in programming education Appl Sci 2020 10 8 2973
[94]
Harer JA et al (2018) Automated software vulnerability detection with machine learning. [Online]. Available: http://arxiv.org/abs/1803.04497
[95]
Phan AV, Chau PN, Le Nguyen M, and Bui LT Automatically classifying source code using tree-based approaches Data Knowl Eng 2018 114 July 2019 12-25
[96]
Kiyak EO, Cengiz AB, Birant KU, and Birant D Comparison of image-based and text-based source code classification using deep learning SN Comput Sci 2020
[97]
Liu Y, Wang J, and Ben-Tzvi P A cable length invariant robotic tail using a circular shape universal joint mechanism J Mech Robot 2019
[98]
Kim DK A deep neural network-based approach to finding similar code segments IEICE Trans Inf Syst 2020 E103D 4 874-878
[99]
Mou L, Li G, Zhang L, Wang T, and Jin Z Convolutional neural networks over tree structures for programming language processing AAAI Conf Artif Intell AAAI 2016 2016 1287-1293
[100]
Yan J, Xu C, Li N, Gao M, and Zhou A Optimizing model parameter for entity summarization across knowledge graphs J Comb Optim 2019 37 1 293-318
[101]
Engels S, Lakshmanan V, Craig M (2007) Plagiarism detection using feature-based neural networks. In: SIGCSE 2007 38th SIGCSE Tech. Symp. Comput. Sci. Educ, pp 34–38.
[102]
Wei HH and Li M Supervised deep features for software functional clone detection by exploiting lexical and syntactical information in source code IJCAI Int Jt Conf Artif Intell 2017
[103]
Yu Z, Zheng W, Wang J, Tang Q, Nie S, and Wu S CodeCMR : cross-modal retrieval For function-level binary source code matching Adv Neural Inf Process Syst 2020 33 1-12
[104]
Allyson FB, Danilo ML, Jose SM, and Giovanni BC Sherlock N-overlap: invasive normalization and overlap coefficient for the similarity analysis between source code IEEE Trans Comput 2019 68 5 740-751
[105]
Göde N, Koschke R (2009) Incremental clone detection. In: Proceedings Eur conference software maintenance reengineering, CSMR, pp 219–228.
[106]
Quoc D, Bui N, Bui NDQ (2018) Institutional knowledge at Singapore Management University Cross-language learning for program classification using bilateral tree-based convolutional neural networks cross-language learning for program classification using bilateral tree-based Convolutio
[107]
Schneider J, Bernstein A, Vom Brocke J, Damevski K, and Shepherd DC Detecting plagiarism based on the creation process IEEE Trans Learn Technol 2018 11 3 348-361
[108]
Svajlenko J, Roy CK (2017) CloneWorks: a fast and flexible large-scale near-miss clone detection tool. In: Proceedings - 2017 IEEE/ACM 39th international conference software engineering companion, ICSE-C 2017, pp 177–179.
[109]
Zhang J, Wang X, Zhang X, Sun H, Wang K, Liu X (2019) A novel neural source code representation based on abstract syntax tree. In: Proceeding - international conference software engineering, vol 2019-May, pp 783–794.
[110]
Ragkhitwetsagul C and Krinke J Siamese: scalable and incremental code clone search via multiple code representations Empir Softw Eng 2019 24 4 2236-2284
[111]
Falleri J, Morandat F, Blanc X, Martinez M, Monperrus M (2014) Fine-grained and accurate source code differencing to cite this version: fine-grained and accurate source code differencing, Ase
[112]
Saini N, Singh S, and Suman S Code clones: detection and management Proc Comput Sci 2018 132 718-727
[113]
White M, Tufano M, Vendome C, Poshyvanyk D (2016) Deep learning code fragments for code clone detection. In: ASE 2016 - Proc. 31st IEEE/ACM Int. Conf. Autom. Softw. Eng., pp 87–98.
[114]
Higo Y, Yasushi U, Nishino M, Kusumoto S (2011) Incremental code clone detection: a PDG-based approach. In: Proceedings - workshop conference reverse engineering WCRE, pp 3–12.
[115]
Guo H et al. A lightweight cross-version binary code similarity detection based on similarity and correlation coefficient features IEEE Access 2020 8 120501-120512
[116]
Liu B et al (2018) ΑDiff: cross-version binary code similarity detection with DNN. In: ASE 2018 - proceeding 33rd ACM/IEEE international conference on automation software engineering, pp 667–678.
[117]
Ullah F et al. Cyber security threats detection in internet of things using deep learning approach IEEE Access 2019 7 124379-124389
[118]
Ljubovic V and Pajic E Plagiarism detection in computer programming using feature extraction from ultra-fine-grained repositories IEEE Access 2020 8 96505-96514
[119]
Mozgovoy M, Kakkonen T, Sutinen E (2007) Using natural language parsers in plagiarism detection. In: Proceeding. SLaTE, pp 77–79 [Online]. Available: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.144.320&rep=rep1&type=pdf
[120]
Sun W, Wang X, Wu H, Duan D, Sun Z, Chen Z (2019) MAF: method-anchored test fragmentation for test code plagiarism detection. In: Proceedings - 2019 IEEE/ACM 41st International conference software engineering education training, ICSE-SEET 2019, pp 110–120.
[121]
Xu X et al (2020) Revisiting the challenges and opportunities in software plagiarism detection. In: SANER 2020 - Proceeding 2020 IEEE 27th international conference on software anal evolution reengineering, pp 537–541.
[122]
Cosma G and Joy M An approach to source-code plagiarism detection and investigation using latent semantic analysis IEEE Trans Comput 2012 61 3 379-394
[123]
Budiman A and Karnalim O Automated hints generation for investigating source code plagiarism and identifying the culprits on in-class individual programming assessment Computers 2019 8 1 11
[124]
Koschke R Survey of research on software clones Duplic Redundancy Similarity Softw Dagstuhl Semin 2007 06301 4
[125]
Zhao G, Huang J (2018) DeepSim: deep learning code functional similarity. In: ESEC/FSE proceedings of the 2018 26th ACM joint meeting on European software engineering conference and symposium on the foundations of software engineering, pp 141–151.
[126]
Murakami H, Hotta K, Higo Y, Igaki H, Kusumoto S (2013) Gapped code clone detection with lightweight source code analysis. In: IEEE international conference on program comprehension. pp 93–102.

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  • (2025)Key-based data augmentation with curriculum learning for few-shot code searchNeural Computing and Applications10.1007/s00521-024-10670-937:3(1475-1490)Online publication date: 1-Jan-2025
  • (2023)A systematic literature review on source code similarity measurement and clone detectionJournal of Systems and Software10.1016/j.jss.2023.111796204:COnline publication date: 1-Oct-2023

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cover image Neural Computing and Applications
Neural Computing and Applications  Volume 34, Issue 23
Dec 2022
937 pages
ISSN:0941-0643
EISSN:1433-3058
Issue’s Table of Contents

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 December 2022
Accepted: 04 August 2022
Received: 30 December 2021

Author Tags

  1. Code duplication
  2. Code duplication detection
  3. System literature review

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  • Review-article

Funding Sources

  • National Natural Science Foundation of China
  • Research Foundation of Education Bureau of Hunan Province

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  • (2025)Key-based data augmentation with curriculum learning for few-shot code searchNeural Computing and Applications10.1007/s00521-024-10670-937:3(1475-1490)Online publication date: 1-Jan-2025
  • (2023)A systematic literature review on source code similarity measurement and clone detectionJournal of Systems and Software10.1016/j.jss.2023.111796204:COnline publication date: 1-Oct-2023

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