Towards the Validation of Plagiarism Detection Tools by Means of Grammar Evolution

Cebrián, Manuel; Alfonseca, Manuel; Ortega, Alfonso

doi:10.1109/tevc.2008.2008797

Cited by 16 publications

(9 citation statements)

References 20 publications

(13 reference statements)

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“…-For the activities done in Mooshak, we use a plagiarism detection system developed by Cebrian et al [8]. Thanks to Mooshak, all the submissions are available in judge's server, so the plagiarism detector can be easily applied.…”

Section: Instantiation Of the Methodsmentioning

confidence: 99%

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Make Learning Fun with Programming Contests

Garcı́a-Mateos

Fernández-Alemán

2009

Transactions on Edutainment II

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Abstract. Usually, higher education teachers have to deal with highly populated classes and low levels of motivation. Making more entertaining courses is a good way to overcome these limitations. But, how can fun and entertainment be introduced in a course which is mainly based on a final exam evaluation? We propose a new methodology based on two key ideas: (i) replacing the final exam with a series of activities in a continuous evaluation context; and (ii) making those activities more appealing to the students. We describe an e-learning experience carried out in a second-year programming course for computing majors. The activities are designed as on-line programming competitions, where all students participate and are able to see their global ranking. Experimental results show the effectiveness of this approach. On average, the dropout rate decreased from 72% to 45% while the pass rate doubled.

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Section: Instantiation Of the Methodsmentioning

confidence: 99%

“…To ensure the authorship of the programs, a source code plagiarism detection environment [8] is used. To appraise the quality of the code, the human factor remains to be prominent.…”

Section: Related Workmentioning

confidence: 99%

Make Learning Fun with Programming Contests

Garcı́a-Mateos

Fernández-Alemán

2009

Transactions on Edutainment II

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“…Similarly, the system by Zhang et al [95] employs a measurement of shared information and clustering to look for plagiarism. A recent paper by Cebrián et al [96] discusses an approach to the validation of plagiarism detection systems employing shared information to compare programmatically generated code variants. What all of these references have in common is the use of information theory -specifically Kolmogorov complexity based information distance -for looking at similarity between coding artefacts.…”

Section: Similarity Not Differencementioning

confidence: 99%

Studying software evolution using artefacts’ shared information content

Arbuckle¹

2011

Science of Computer Programming

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a b s t r a c tIn order to study software evolution, it is necessary to measure artefacts representative of project releases. If we consider the process of software evolution to be copying with subsequent modification, then, by analogy, placing emphasis on what remains the same between releases will lead to focusing on similarity between artefacts. At the same time, software artefacts -stored digitally as binary strings -are all information. This paper introduces a new method for measuring software evolution in terms of artefacts' shared information content. A similarity value representing the quantity of information shared between artefact pairs is produced using a calculation based on Kolmogorov complexity. Similarity values for releases are then collated over the software's evolution to form a map quantifying change through lack of similarity. The method has general applicability: it can disregard otherwise salient software features such as programming paradigm, language or application domain because it considers software artefacts purely in terms of the mathematically justified concept of information content. Three open-source projects are analysed to show the method's utility. Preliminary experiments on udev and git verify the measurement of the projects' evolutions. An experiment on ArgoUML validates the measured evolution against experimental data from other studies.

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“…-For the activities done in Mooshak, we use a plagiarism detection system developed by Cebrian et al [13]. Thanks to Mooshak, all the submissions are available in judge's server, so the plagiarism detector can be easily applied.…”

Section: Comprehensionmentioning

confidence: 99%

An Experience on Ada Programming Using On-Line Judging

Montoya-Dato

Fernández-Alemán

Garcı́a-Mateos

2009

Reliable Software Technologies – Ada-Europe 2009

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Abstract. Ada has proved to be one of the best languages to learn computer programming. Nevertheless, learning to program is difficult and when it is combined with lack of motivation by the students, dropout rates can reach up to 70%. In order to face up to this problem, we have developed a first-year course for computing majors on programming based on two key ideas: supplementing the final exam with a series of activities in a continuous evaluation context; and making those activities more appealing to the students. In particular, some of the activities are designed as on-line Ada programming competitions; they are carried out by using a web-based automatic evaluation system, the on-line judge. Human instructors remain essential to assess the quality of the code. To ensure the authorship of the programs, a source-code plagiarism detection environment is used. Experimental results show the effectiveness of the proposed approach. The dropout rate decreased from 61% in the autumn semester 2007 to 48% in the autumn semester 2008.

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Towards the Validation of Plagiarism Detection Tools by Means of Grammar Evolution

Cited by 16 publications

References 20 publications

Make Learning Fun with Programming Contests

Make Learning Fun with Programming Contests

Studying software evolution using artefacts’ shared information content

An Experience on Ada Programming Using On-Line Judging

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