Vivek Lakshmanan

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This paper focuses on the use of code features for automatic plagiarism detection. Instead of the text-based analyses employed by current plagiarism detectors, we propose a system that is based on properties of assignments that course instructors use to judge the similarity of two submissions. This system uses neural network techniques to create a(More)
We describe the requirements – scientific, technical and economic – of scientists and engineers who are developing new meteorological algorithms and products. We argue that these requirements call for quick and ready access to multiple, disparate sources of data (including the outputs of other algorithms) in a uniform manner. We also argue that developer(More)
Exploiting File System Awareness for Improvements to Storage Virtualization Vivek Lakshmanan Master of Science Graduate Department of Computer Science University of Toronto 2009 File systems are tasked with storing, organizing, and retrieving valuable data for long periods of time. This requires them to provide excellent fault-tolerance and reliability(More)
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