本文選題：屬性計數(shù)法 + 結(jié)構(gòu)度量技術(shù)　； 參考：《西北農(nóng)林科技大學(xué)》2017年碩士論文

【摘要】：為了高效檢測程序設(shè)計課程中代碼剽竊問題,減少或杜絕代碼剽竊現(xiàn)象。針對目前已有的代碼剽竊檢測系統(tǒng)檢測結(jié)果準(zhǔn)確性較差、時間復(fù)雜度高等問題,本文提出一套完整的解決方案,并依據(jù)該方案構(gòu)建出剽竊檢測系統(tǒng),用于程序設(shè)計課程的代碼剽竊檢測。主要研究內(nèi)容如下:(1)針對已有檢測系統(tǒng)運(yùn)行時間復(fù)雜度高的問題,提出了一種基于屬性計數(shù)法和結(jié)構(gòu)度量技術(shù)相結(jié)合的程序相似度計算方法,通過提取代碼屬性特征和結(jié)構(gòu)特征方法,降低了檢測系統(tǒng)的時間復(fù)雜度。實(shí)驗(yàn)表明,檢測系統(tǒng)的運(yùn)行時間復(fù)雜度與最長公共子序列算法相比降低了15.1%。(2)針對已有檢測系統(tǒng)準(zhǔn)確性低的問題,通過分析代碼剽竊的特點(diǎn),優(yōu)化了檢測流程:優(yōu)先使用GST(Greedy String Tilling)算法檢測低級的代碼剽竊問題,再依據(jù)決策函數(shù)判斷是否采用屬性計數(shù)法和結(jié)構(gòu)度量技術(shù)相結(jié)合的方法進(jìn)一步計算相似度,采用兩次檢測結(jié)果的綜合評價得出最終檢測結(jié)論,實(shí)驗(yàn)結(jié)果表明,對于構(gòu)造樣本、學(xué)生日常作業(yè)和上機(jī)考試提交的程序代碼樣本中的低級的剽竊手段,檢測結(jié)果的準(zhǔn)確率達(dá)95%;而對于較為高級的檢測手段,比如增加冗余、等價結(jié)構(gòu)替換等,本文設(shè)計的檢測系統(tǒng)比JPlag系統(tǒng)的精度提高了5.6%。(3)實(shí)現(xiàn)了程序代碼自動化檢測系統(tǒng)一套,包括代碼預(yù)處理、有效選擇源程序的特征、高效提取特征元素及相似度檢測算法的實(shí)現(xiàn)。為了驗(yàn)證本研究方法及構(gòu)建出一套剽竊檢測系統(tǒng)的有效性,選取三組典型樣本在JPlag系統(tǒng)和本研究搭建的剽竊檢測系統(tǒng)同時進(jìn)行檢測,最后比較檢測結(jié)果。綜合分析三組樣本中常見的五類剽竊手段的檢測結(jié)果比JPlag系統(tǒng)的精度提高了7.3%。軟件測試表明,該系統(tǒng)能夠穩(wěn)定可靠地工作,較好的實(shí)現(xiàn)了設(shè)計的目標(biāo)。
[Abstract]:To detect code plagiarism in programming courses efficiently, reduce or eliminate code plagiarism. Aiming at the problems of poor accuracy and high time complexity of the existing code plagiarism detection system, this paper proposes a complete solution, and constructs a plagiarism detection system based on this scheme. Code plagiarism detection for programming courses. The main research contents are as follows: (1) aiming at the problem of high time complexity of the existing detection system, a program similarity calculation method based on the combination of attribute counting and structure measurement is proposed. The time complexity of the detection system is reduced by extracting code attribute features and structural features. The experimental results show that the complexity of the detection system is 15.1than that of the longest common subsequence algorithm. (2) aiming at the problem of low accuracy of the existing detection system, the characteristics of code plagiarism are analyzed. This paper optimizes the detection flow: first using GST(Greedy String tracing algorithm to detect the low-level code plagiarism problem, and then judging whether to use attribute counting method and structure measurement technology to calculate the similarity according to the decision function. The final test results are obtained by comprehensive evaluation of the results of two tests. The experimental results show that, for the low-level plagiarism means of constructing samples, students' daily homework and program code samples submitted by computer examination, The accuracy of the detection results is 95%. For the more advanced detection methods, such as increasing redundancy and replacing equivalent structures, the precision of the detection system designed in this paper has been improved by 5.6% compared with that of the JPlag system.) the automatic detection system of program code has been realized. It includes code preprocessing, effective selection of source program features, efficient extraction of feature elements and implementation of similarity detection algorithm. In order to verify the effectiveness of this research method and construct a plagiarism detection system, three groups of typical samples were selected to simultaneously detect plagiarism in JPlag system and the plagiarism detection system built in this study. Finally, the detection results were compared. The accuracy of five kinds of plagiarism methods in three groups of samples is improved by 7.3% compared with that of JPlag system. The software test shows that the system can work stably and reliably, and achieve the design goal well.
【學(xué)位授予單位】：西北農(nóng)林科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.1-4;G434

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