scholarly journals Python Source Code Plagiarism Attacks in Object-Oriented Environment

2017 ◽  
Vol 6 (3) ◽  
pp. 87-84
Author(s):  
Oscar Karnalim ◽  
Aldi Aldiansyah
Keyword(s):  
Data Structure ◽  
Computer Science ◽  
Prior Knowledge ◽  
Programming Language ◽  
Detection System ◽  
Source Code ◽  
Object Oriented ◽  
Plagiarism Detection ◽  
Science Major

Since source code plagiarism is an emerging issue on Computer Science major and Python is a new popular programming language, this paper aims to empirically enlist plagiarism attacks that might be occurred on Python source code. As our case study, our work will be focused on source code plagiarism in object-oriented environment. The result of this work is expected to become either an evaluation baseline or a prior knowledge for developing Python-targeted plagiarism detection system. Based on 280 plagiarism-suspected pairs that were extracted from four Basic Data Structure classes, four findings can be deducted. First, there are 20 distinct Python plagiarism attacks that might be occurred in object-oriented environment. Second, plagiarism attack trend on both object-oriented and procedural environment are considerably similar to each other. Third, there is no need to handle plagiarism attacks in both object-oriented and procedural environment separately. Last, plagiarism attacks in object-oriented environment is more monotonous than such attacks in procedural environment.

Source Code Plagiarism Detection Using Biological String Similarity Algorithms

2014 ◽  
Vol 13 (03) ◽  
pp. 1450028 ◽  
Author(s):  
Imad Rahal ◽  
Colin Wielga
Keyword(s):  
Programming Languages ◽  
Source Code ◽  
Visual Basic ◽  
Biological Sequence ◽  
Large Collection ◽  
Plagiarism Detection ◽  
String Similarity ◽  
What Works ◽  
String Comparison

Source code plagiarism is easy to commit but difficult to catch. Many approaches have been proposed in the literature to automate its detection; however there is little consensus on what works best. In this paper, we propose two new measures for determining the accuracy of a given technique and describe an approach to convert code files into strings which can then be compared for similarity in order to detect plagiarism. We then compare several string comparison techniques, heavily utilised in the area of biological sequence alignment, and compare their performance on a large collection of student source code containing various types of plagiarism. Experimental results show that the compared techniques succeed in matching a plagiarised file to its original files upwards of 90% of the time. Finally, we propose a modification for these algorithms that drastically improves their runtimes with little or no effect on accuracy. Even though the ideas presented herein are applicable to most programming languages, we focus on a case study pertaining to an introductory-level Visual Basic programming course offered at our institution.

REDESIGNING LEGACY SYSTEMS INTO THE OBJECT-ORIENTED PARADIGM

2004 ◽  
Vol 14 (03) ◽  
pp. 255-276
Author(s):  
W. ERIC WONG ◽  
JENNY LI
Keyword(s):  
Inventory Management ◽  
Source Code ◽  
Object Oriented ◽  
Original System ◽  
Software Systems ◽  
Legacy Systems ◽  
Dynamic Binding ◽  
Legacy Software ◽  
Original Program

Object-oriented languages support many modern programming concepts such as information hiding, inheritance, polymorphism, and dynamic binding. As a result, software systems implemented in OO languages are in general more reusable and reliable than others. Many legacy software systems, created before OO programming became popular, need to be redesigned and updated to OO programs. The process of abstracting OO designs from the procedural source code has often been done with limited assistance from program structural diagrams. Most reengineering focuses on the functionality of the original program, and the OO redesign often results in a completely new design based on the designers' understanding of the original program. Such an approach is not sufficient because it may take a significant amount of time and effort for designers to comprehend the original program. This paper presents a computer-aided semi-automatic method that abstracts OO designs from the original procedural source code. More specifically, it is a method for OO redesign based on program structural diagrams, visualization, and execution slices. We conducted a case study by applying this method to an inventory management software system. Results indicate that our method can effectively and efficiently abstract an appropriate OO design out of the original C code. In addition, some of the code from the original system can be automatically identified and reused in the new OO system.

scholarly journals Pembangunan Perangkat Lunak PuniEdit (Perangkat Lunak Editor untuk Multi Language Programming)

2019 ◽  
Author(s):  
Budiman
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Source Code ◽  
Computer Software ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Text Editor ◽  
Development Environment ◽  
Integrated Development ◽  
High Level

During this period continued to develop computer software, programming language was no exception. At the start of the era of low level programming languages, then developed a high level programming language. It is characterized by the appearance of a method of programming offered by a programming language, that is, object-oriented programming (OOP). IDE (Integrated Development Environment) is a computer program that has some facilities that are required in the development of the software. The purpose of the IDEA is to provide all the necessary utilities in building software. As for the type of software text editor that can be used to manipulate the source code hereinafter referred to as the source code of programming languages such as Ultraedit, JediEdit, ClearEdit, cEdit, the Golden Pen, and so on. PuniEdit software is a text-based editor software that can simplify the user through correction, insertion, and modification of the source code. PuniEdit software is built using Borland Delphi 7.0 and SynEdit component. This software can be used for the Pascal programming language, C++ and HTML. In addition, the software PuniEdit can perform management of the token. This PuniEdit software, the user can clearly see every occurrence of the type of token as keywords (reserved word), identifier, operator, and so on.Keywords: Source code, programming language, source code is scanned.

Policy and Issues in Deploying Automated Plagiarism Detection Systems in Academic Communities

2011 ◽  
pp. 172-195
Author(s):  
Chi Hong Cheong ◽  
Tak Pang Lau ◽  
Irwin King
Keyword(s):  
Ethical Issues ◽  
Detection System ◽  
Educational Institution ◽  
Background Information ◽  
Plagiarism Detection ◽  
Academic Quality ◽  
Policy Issues ◽  
Detection Systems ◽  
Use Of The Internet

Plagiarism is becoming prevalent through the use of the Internet. Educational institutions are seeking technology to combat plagiarism. This chapter describes policy and issues encountered by an educational institution that deploys an automated plagiarism detection system. Background information of plagiarism and the benefits of using automated plagiarism detection systems are presented as motivation. A detailed account on the benefits of using automated plagiarism detection system in the academic setting is given. Associated policy issues (administrative issues, submission policy issues, disciplinary issues, copyright issues, security and privacy issues, and ethical issues) and resources needed to deploy such a system are discussed in details. VeriGuide, an automated plagiarism detection system designed and implemented at the Chinese University of Hong Kong, is presented as a case study on how the technology can be used to alleviate workload for the teachers and also provide a fair academic environment for the students. It is hoped that the case study would be helpful for those who are interested in using such a system to promote academic quality and integrity.

scholarly journals Flowchart-Based Cross-Language Source Code Similarity Detection

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Feng Zhang ◽  
Guofan Li ◽  
Cong Liu ◽  
Qian Song
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Computer Programming ◽  
Source Code ◽  
Common Source ◽  
Intermediate Structure ◽  
Plagiarism Detection ◽  
Code Obfuscation ◽  
Similarity Detection ◽  
Cross Language

Source code similarity detection has various applications in code plagiarism detection and software intellectual property protection. In computer programming teaching, students may convert the source code written in one programming language into another language for their code assignment submission. Existing similarity measures of source code written in the same language are not applicable for the cross-language code similarity detection because of syntactic differences among different programming languages. Meanwhile, existing cross-language source similarity detection approaches are susceptible to complex code obfuscation techniques, such as replacing equivalent control structure and adding redundant statements. To solve this problem, we propose a cross-language code similarity detection (CLCSD) approach based on code flowcharts. In general, two source code fragments written in different programming languages are transformed into standardized code flowcharts (SCFC), and their similarity is obtained by measuring their corresponding SCFC. More specifically, we first introduce the standardized code flowchart (SCFC) model to be the uniform flowcharts representation of source code written in different languages. SCFC is language-independent, and therefore, it can be used as the intermediate structure for source code similarity detection. Meanwhile, transformation techniques are given to transform source code written in a specific programming language into an SCFC. Second, we propose the SCFC-SPGK algorithm based on the shortest path graph kernel to measure the similarity between two SCFCs. Thus, the similarity between two pieces of source code in different programming languages is given by the similarity between SCFCs. Experimental results show that compared with existing approaches, CLCSD has higher accuracy in cross-language source code similarity detection. Furthermore, CLCSD cannot only handle common source code obfuscation techniques used by students in computer programming teaching but also obtain nearly 90% accuracy in dealing with some complex obfuscation techniques.

scholarly journals Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment

2017 ◽  
Vol 41 (1) ◽  
pp. 105-123 ◽  
Author(s):  
Faqih Salban Rabbani ◽  
Oscar Karnalim
Keyword(s):  
Programming Languages ◽  
State Of The Art ◽  
Source Code ◽  
Point Of View ◽  
Local Alignment ◽  
Plagiarism Detection ◽  
Low Level ◽  
Intermediate Language ◽  
Token Sequence

Even though there are various source code plagiarism detection approaches, only a few works which are focused on low-level representation for deducting similarity. Most of them are only focused on lexical token sequence extracted from source code. In our point of view, low-level representation is more beneficial than lexical token since its form is more compact than the source code itself. It only considers semantic-preserving instructions and ignores many source code delimiter tokens. This paper proposes a source code plagiarism detection which rely on low-level representation. For a case study, we focus our work on .NET programming languages with Common Intermediate Language as its low-level representation. In addition, we also incorporate Adaptive Local Alignment for detecting similarity. According to Lim et al, this algorithm outperforms code similarity state-of-the-art algorithm (i.e. Greedy String Tiling) in term of effectiveness. According to our evaluation which involves various plagiarism attacks, our approach is more effective and efficient when compared with standard lexical-token approach. 

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