DocumentCode :
3578849
Title :
Automatic grader for programming assignment using source code analyzer
Author :
Yulianto, Susilo Veri ; Liem, Inggriani
Author_Institution :
Sch. of Electr. Eng. & Inf., Inst. Teknol. Bandung, Bandung, Indonesia
fYear :
2014
Firstpage :
1
Lastpage :
4
Abstract :
Source code analyzer is a tool for analyzing source code that aim to improve the quality of programs in software development. This research enhanced the ability of source code analyzer for automatic grading of programming assignments. The automatic grading process runs in three phases: (a) source code analysis by source code analyzer, (b) analytical results unification, and (c) unification results assessments. Analysis unification use the XSLTtransformation process, while the assessment done by matching bugs/flaws found in the source code with a list of bugs/flaws that have been defined. This research deliver application called SCAGrader. SCAGrader consists of a Java engine application in the Java language and web-based user interface. The score obtained by giving a negative score to each bugs/flaws found in student´s source code. Beside its independent capability, SCAGrader also integrated to existing blackbox autograding system by services. The other result of this study is a classification of bugs/flaws for teaching programming, based on five source code analyzers.
Keywords :
Java; computer science education; pattern matching; program debugging; programming; software quality; source code (software); teaching; user interfaces; Java engine application; Java language; SCAGrader; Web-based user interface; XSLT transformation process; automatic programming assignment grader; blackbox autograding system; bug matching; flaw matching; program quality; programming teaching; software development; source code analysis; source code analyzer; student source code; Computer bugs; Electrical engineering; Encoding; Engines; Java; Programming; XML; XML; XSLT; source code analyzer; static analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data and Software Engineering (ICODSE), 2014 International Conference on
Print_ISBN :
978-1-4799-8175-5
Type :
conf
DOI :
10.1109/ICODSE.2014.7062687
Filename :
7062687
Link To Document :
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