Approaches to Detection of Source Code Plagiarism amongst Students
Date 28.12.2016 Size 17.07 Kb. #4661
Mike Joy 23 November 2010 Process for detecting plagiarism Technologies Establishing the facts Four Stages Collection Detection Confirmation Investigation From Culwin and Lancaster (2002) Get all documents together online so they can be processed formats? security? BOSS (Warwick) Coursemaster (Nottingham) Managed Learning Environment Compare with other submissions Compare with external documents We’ll come back to this later Software tool says “A and B similar” Never rely on a computer program! Requires expert human judgement Evidence must be compelling Might go to court A from B, or B from A, or joint work? If A from B, did B know? open networked file / printer output Did the culprit/s understand? Was code written externally? University processes must be followed Establishing the facts How do you compare two programs? This is an algorithm question Stages 2 and 3: detection and confirmation How do you use the results (of a comparison) to educate students? This is a pedagogic question Stage 4, and before stage 1! Plagiarism in essays is easier to detect Lots of “tricks” a lecturer can use! Software tools Collection Detection Confirmation Investigation It won’t work! String matching algorithm inappropriate Database does not contain code Commercial involvement /* Program A */ public class Sun { static final double latitude=52.4; static final double longitude=-1.5; static final double tpi = 2.0*pi; /* ... */ public static void main(String[] args) { calculate(); } public static double FNrange(double x) { double b = x / tpi; double a = tpi * (b - (long)(b)); if (a < 0) a = tpi + a; return a; }; public static void calculate() { /* ... */ } /* ... */ /* Program B */ public class SunsetCalculator { static float latitude=52.4; static float longitude=-1.5; /* ... */ public static void main(String[] args) { findSunsetTime(); } public static double rangeCalc(float arg) { float x = arg / tpi; float y = 2*3.14159 * (x - (int)(x)); if (y < 0) y = 2*3.14159 + y; return y; }; public static void findSunsetTime() { /* ... */ } /* ... */ Is Program B derived from Program A in a manner which is “plagiarism”? Maybe Structure is similar – cosmetic changes But the algorithm Maybe 6 derived from 5, maybe the other way round Attribute counting systems (Halstead, 1972; Ottenstein, 1976): Numbers of unique operators Numbers of unique operands Total numbers of operator occurrences Total numbers of operand occurrences Structure-based systems : Each program is converted into token strings (or something similar) Token streams are compared for determining similar source-code fragments Tools: YAP3, JPlag, Plague, MOSS, and Sherlock Example (tokenwise equivalent) int calculate(String arg) { int ans=0; for (int j=1; j<=100; j++) { ans *= j; } return ans; } Integer doit(String v) { float result=0.0; for (float f=100.0; f > 0.0; f--) result *= f; return result; } type name(type name) start type name=number loop (type name=number name compare number operation name) start name operation name end return name end MOSS (Alex Aiken: Berkeley/Stanford, USA, 1994) JPlag (Guido Malpohl: Karlsruhe, Germany) Java only Programs must compile? Sherlock (Warwick, UK) (Joy and Luck, 1999) MOSS determines the similarity of C, C++, Java, Pascal, Ada, ML, Lisp, or Scheme program Web-based: theory.stanford.edu/~aiken/moss/ “Winnowing” (Schleimer et al. , 2003) Local document fingerprinting algorithm Efficiency proven (33% of lower bound) Guarantees detection of matches longer than a certain threshold JPlag currently supports Java, C#, C, C++, Scheme, and natural language text Web-based: www.ipd.uni-karlsruhe.de/jplag Algorithm: Parse programs and tokenise then pairwise compare using “Greedy String Tiling” (Prechelt et al., 2002) maximises percentage of common token strings worst case θ(n3), average case linear Developed at the University of Warwick Department of Computer Science Open-Source application coded in Java Sherlock detects plagiarism on source-code and natural language assignments BOSS home page: www.boss.org.uk Preprocesses code (not a full parse!) then simple string comparison Commercial product www.safe-corp.biz exact algorithm not publishedpatent pending? Free academic use for small data sets Remove comments , whitespace and lines containing only keywords/syntax; compare sequences of instructions Extract comments, and compare Extract identifiers, and count similar; x, xxx, xx12345 are “similar” Combine (1), (2) and (3) to give correlation score Example of Identical “Instruction Sequences” /* File 1*/ for (int i=1; i<10; i++) { if (a==10) print(“done”); else a++; } /* File 2*/ for (int x=100; x > 0; x--) { if (z99 > -10) print(“ans is ” + z99); else { abc += 65; } } Documents as “bags of words” Known technique in IR Handles synonymy and polysemy Maths is nasty Results reported in (Cosma and Joy, 2010) Comments Spelling mistakes Unusual English (Thai, German, …) Use of Search Engines Unusual style Code errors Data protection (e.g. MOSS is in USA) Accuracy Faulty code may not be accepted Results returned by different tools are similar (but not identical) User interface Availability of sets of test data Part 3 – Establishing the Facts Collection Detection Confirmation Investigation What do we actually This is where the problems start … Evidence … ? We carried out a survey in order to: gather the perceptions of academics on what constitutes source-code plagiarism (Cosma and Joy, 2006), and create a structured description of what constitutes source-code plagiarism from a UK academic perspective (Cosma and Joy, 2008) On-line questionnaire distributed to 120 academics Questions were in the form of small scenarios Mostly multiple-choice responses Comments box below each question Anonymous – option for providing details Received 59 responses, from more that 34 different institutions Responses were analysed and collated to create a universally acceptable source-code plagiarism description. Plagiaristic activities: Source-code reuse and self-plagiarism Use of (O-O) templates Converting source to another language Inappropriate collusion/collaboration Using code-generator software Obtaining source-code written by other authors False and “pretend” references Copying with adaptation: minimal, moderate, extreme We carried out a survey (Joy et al. , 2010) in order to: gather the perceptions of students on what (source code) plagiarism means identify types of plagiarism which are poorly understood identify categories of student who perceive the issue differently to others Online questionnaire answered by 770 students from computing departments across the UK Anonymised, but brief demographic information included Used 15 “scenarios”, each of which may describe a plagiaristic activity No significant difference in perspectives in terms of university degree programme level of study (BS, MS, PhD) Issues which students misunderstood: open source code translating between languages re-use of code from previous assignments placing references within technical documentation Making policy clear to students Identifying external contributors web sites with code to download enthusiasts forums, Wikis, etc. Cheat sites F. Culwin and T.Lancaster, “Plagiarism, prevention, deterrence and detection”, [online] available from: www.heacademy.ac.uk/assets/York/documents /resources/resourcedatabase/ id426_plagiarism_prevention_deterrence_detection.pdf (2002) G. Cosma and M.S. Joy, “An Approach to Source-Code Plagiarism Detection and Investigation using Latent Semantic Analysis” IEEE Transactions on Computers, to appear (2010) G. Cosma and M.S. Joy, “Towards a Definition on Source-Code Plagiarism”, IEEE Transactions on Education 51(2) pp. 195-200 (2008) G. Cosma and M.S. Joy, “Source-code Plagiarism: a UK Academic Perspective”, Proceedings of the 7th Annual Conference of the HEA Network for Information and Computer Sciences (2006) M. Halstead, “Natural Laws Controlling Algorithm Structure, ACM SIGPLAN Notices 7(2) pp. 19-26 (1972) M.S. Joy, G. Cosma, J.Y-K. Yau and J.E. Sinclair, “Source Code Plagiarism – a Student Perspective”, IEEE Transactions on Education (to appear) (2010) M.S. Joy and M. Luck, “Plagiarism in Programming Assignments”, IEEE Transactions on Education 42(2), pp. 129-133 (1999) K. Ottenstein, “An Algorithmic Approach to the Detection and Prevention of Plagiarism”, ACM SIGCSE Bulletin 8 (4) pp. 30-41 (1976) L. Prechelt, G. Malpohl and M. Philippsen, “Finding “Plagiarisms among a Set of Programs with JPlag”. Journal of Universal Computer Science 8(11) pp. 1016-1038 (2002) S. Schleimer, D.S. Wilkerson and A. Aitken, “Winnowing: Local Algorithms for Document Fingerprinting”, Proceedings of the ACM SIGMOD International Conference on Management of Data , pp. 76-85 (2003) Share with your friends:
The database is protected by copyright ©sckool.org 2023
send message
