{"title":"在线课程管理系统的智能代码分析器","authors":"J. Kuo, Louisa Chu","doi":"10.1109/SERA.2005.47","DOIUrl":null,"url":null,"abstract":"Online course management system (OCMS) mainly aids various events in online instructing, including testing, course discussion, assignment submission, and assignment grading. This paper is mainly designed basing on the study of completed OCMS of the past. Online assignment submission is prone to easy plagiarism, infecting the learning process of the students and interfering with their studies. In the past, using human power to inspect for plagiarism is very time-consuming. This research then is focused on allowing programming courses to employ procedures such as code standardization, textual analysis, structural analysis, and variable analysis, to evaluate and compare programming codes. We provide an intelligent agent as a daemon to analyze the program code for OCMS. Textually, we use document fingerprinting algorithm as a basis for text comparison; structurally, we utilize formal algebraic expression and dynamic control structure tree (DCS tree) to rebuild and evaluate the program structure; variable-wise, we not only record relevant information for each variable, but also analyze the programming structure where the variables are positioned. By applying a similarity measuring method, we output a similarity value for each program in the three aspects mentioned above. This research implements a convenient user interface that can be applied independently for assignment analyzation. Moreover, we have designed a set of application programming interface (API) that could be embedded into online course management systems.","PeriodicalId":424175,"journal":{"name":"Third ACIS Int'l Conference on Software Engineering Research, Management and Applications (SERA'05)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Intelligent code analyzer for online course management system\",\"authors\":\"J. Kuo, Louisa Chu\",\"doi\":\"10.1109/SERA.2005.47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online course management system (OCMS) mainly aids various events in online instructing, including testing, course discussion, assignment submission, and assignment grading. This paper is mainly designed basing on the study of completed OCMS of the past. Online assignment submission is prone to easy plagiarism, infecting the learning process of the students and interfering with their studies. In the past, using human power to inspect for plagiarism is very time-consuming. This research then is focused on allowing programming courses to employ procedures such as code standardization, textual analysis, structural analysis, and variable analysis, to evaluate and compare programming codes. We provide an intelligent agent as a daemon to analyze the program code for OCMS. Textually, we use document fingerprinting algorithm as a basis for text comparison; structurally, we utilize formal algebraic expression and dynamic control structure tree (DCS tree) to rebuild and evaluate the program structure; variable-wise, we not only record relevant information for each variable, but also analyze the programming structure where the variables are positioned. By applying a similarity measuring method, we output a similarity value for each program in the three aspects mentioned above. This research implements a convenient user interface that can be applied independently for assignment analyzation. Moreover, we have designed a set of application programming interface (API) that could be embedded into online course management systems.\",\"PeriodicalId\":424175,\"journal\":{\"name\":\"Third ACIS Int'l Conference on Software Engineering Research, Management and Applications (SERA'05)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third ACIS Int'l Conference on Software Engineering Research, Management and Applications (SERA'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SERA.2005.47\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third ACIS Int'l Conference on Software Engineering Research, Management and Applications (SERA'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERA.2005.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent code analyzer for online course management system
Online course management system (OCMS) mainly aids various events in online instructing, including testing, course discussion, assignment submission, and assignment grading. This paper is mainly designed basing on the study of completed OCMS of the past. Online assignment submission is prone to easy plagiarism, infecting the learning process of the students and interfering with their studies. In the past, using human power to inspect for plagiarism is very time-consuming. This research then is focused on allowing programming courses to employ procedures such as code standardization, textual analysis, structural analysis, and variable analysis, to evaluate and compare programming codes. We provide an intelligent agent as a daemon to analyze the program code for OCMS. Textually, we use document fingerprinting algorithm as a basis for text comparison; structurally, we utilize formal algebraic expression and dynamic control structure tree (DCS tree) to rebuild and evaluate the program structure; variable-wise, we not only record relevant information for each variable, but also analyze the programming structure where the variables are positioned. By applying a similarity measuring method, we output a similarity value for each program in the three aspects mentioned above. This research implements a convenient user interface that can be applied independently for assignment analyzation. Moreover, we have designed a set of application programming interface (API) that could be embedded into online course management systems.