Developing Applications to Automatically Grade Introductory Visual Basic Courses

There are many unique challenges associated with introductory programming courses. For novice programmers, the challenges of their first programming class can lead to a great deal of stress and frustration. Regular programming assignments is often key to developing an understanding of best practices and the coding process. Students need practice with these new concepts to reinforce the underlying principles. Providing timely and consistent feedback on these assignments can be a challenge for instructors, particularly in large classes. Plagiarism is also a concern. Unfortunately traditional tools are not well suited to introductory courses. This paper describes how AppGrader, a static code assessment tool can be used to address the challenges of an introductory programming class. The tool assesses student’s understanding and application of programming fundaments as defined in the current ACM/IEEE Information Technology Curriculum Guidelines. Results from a bench test and directions for future research are provided

Graphs Resemblance based Software Birthmarks through Data Mining for Piracy Control

The emergence of software artifacts greatly emphasizes the need for protecting intellectual property rights (IPR) hampered by software piracy requiring effective measures for software piracy control. Software birthmarking targets to counter ownership theft of software by identifying similarity of their origins. A novice birthmarking approach has been proposed in this paper that is based on hybrid of text-mining and graph-mining techniques. The code elements of a program and their relations with other elements have been identified through their properties (i.e code constructs) and transformed into Graph Manipulation Language (GML). The software birthmarks generated by exploiting the graph theoretic properties (through clustering coefficient) are used for the classifications of similarity or dissimilarity of two programs. The proposed technique has been evaluated over metrics of credibility, resilience, method theft, modified code detection and self-copy detection for programs asserting the effectiveness of proposed approach against software ownership theft. The comparative analysis of proposed approach with contemporary ones shows better results for having properties and relations of program nodes and for employing dynamic techniques of graph mining without adding any overhead (such as increased program size and processing cost)