Sustav za otkrivanje sličnosti u tekstualnim dokumentima i izvornim tekstovima programa

master's thesis

• Title (english): A system for detecting similarities in text documents and source codes
• Author: Anita Božić
• Mentor: Marin Golub (mentor)
• Committee member: Marin Golub (predsjednik povjerenstva)
• Committee member: Ante Đerek (član povjerenstva)
• Committee member: Marko Đurasević (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-08, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U ovom radu opisani su postojeći sustavi za otkrivanje sličnosti te algoritmi koje neki od najpoznatijih sustava za otkrivanje sličnosti koriste. Razvijena je desktop aplikacija koja obavlja pretprocesuiranje i usporedbu izvornih tekstova programa prema potrebama Fakulteta elektrotehnike i računarstva, Sveučilišta u Zagrebu. Usporedba tekstova izvršava se pomoću tri algoritma: algoritam odabira prozora, usporedba sažetaka sadržaja datoteka i usporedba karakteristika datoteka. Analizirani su rezultati koje daje razvijeni sustav Maat u usporedbi sa sustavom MOSS, prikazan je utjecaj mijenjanja parametara usporedbe čime je objašnjena razlika u rezultatima između različitih sustava te je izvršeno mjerenje vremena izvođenja pretprocesuiranja i usporedbe datoteka.

Abstract (english)

This paper describes existing similarity detection systems and algorithms used by some of the most well-known similarity detection systems. A desktop application has been developed that performs preprocessing and comparison of the source codes according to the needs of the Faculty of Electrical Engineering and Computing, University of Zagreb. Text comparison is performed using three algorithms: Winnow algorithm, file hash comparison and file properties comparison. The results given by the developed Maat system in comparison with the MOSS system are analyzed, the influence of changing the comparison parameters is shown, which explains the difference in results between different systems, and the measurement of preprocessing and file comparison execution time is performed.

• Keywords: sustavi za otkrivanje sličnosti; tekstualni dokumenti; izvorni tekstovi programa; algoritam odabira prozora; sažeci datoteka; karakteristike datoteka; pretprocesuiranje; usporedba datoteka
• Keywords (english): similarity detection systems; text documents; source codes; winnowing; file hashes; file properties; preprocessing; file comparison
• Language: croatian
• URN:NBN: urn:nbn:hr:168:177603
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 11:51:19