Application for Automated Collection of Test Files for CSS Class via HTTP and for Local Plagiarism Check

Abstract

This thesis focuses on analysing and automating the examination process for the 'Computer Support for Study' course taught at Faculty of Mechanical Engineering, Czech Technical University in Prague; and running the plagiarism check on answers from the test takers. An application called Testrek is built as a part for this thesis which should streamline much of the examination process for the CSS course. The application is written using Python programming language with support from external libraries which are discussed in the thesis. Testrek essentially checks and downloads the files from a publicly accessible network location (public_html folder), where answer files are uploaded by the test takers. The Plagiarism check is run using a library called fuzzywuzzy which in turn uses the Levenshtein distance to calculate the similarity between two strings. At the end, a technical walkthrough of the application is also provided for understanding of the use case. In conclusion, the required automation of examination process has been achieved. Consequently, the analysis in this thesis open opportunity for further scope of automation and making the application even more dynamic to cover more courses.This thesis focuses on analysing and automating the examination process for the 'Computer Support for Study' course taught at Faculty of Mechanical Engineering, Czech Technical University in Prague; and running the plagiarism check on answers from the test takers. An application called Testrek is built as a part for this thesis which should streamline much of the examination process for the CSS course. The application is written using Python programming language with support from external libraries which are discussed in the thesis. Testrek essentially checks and downloads the files from a publicly accessible network location (public_html folder), where answer files are uploaded by the test takers. The Plagiarism check is run using a library called fuzzywuzzy which in turn uses the Levenshtein distance to calculate the similarity between two strings. At the end, a technical walkthrough of the application is also provided for understanding of the use case. In conclusion, the required automation of examination process has been achieved. Consequently, the analysis in this thesis open opportunity for further scope of automation and making the application even more dynamic to cover more courses.