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resarch:nlpa:research_proposal [2014/10/02 16:09] preethac created |
resarch:nlpa:research_proposal [2014/10/02 16:16] (current) preethac |
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* Data flow chain | * Data flow chain | ||
* Extended SWIFT | * Extended SWIFT | ||
- | \\ **Action Unit Similarity, Clustering, and Example and Code Template Generation** | + | * Action Unit Similarity, Clustering, and Example and Code Template Generation |
+ | \\ | ||
+ | * Refine the approach to identify action units based on more evaluation and data analysis. | ||
+ | * Develop an algorithm to detect similarity between action units and cluster similar units. | ||
+ | * Develop a technique to generalize from action unit clusters to generate code templates. | ||
+ | * Evaluate effectiveness of action units for intended uses in developer learning in context. | ||
\\ **Identifying/Characterizing Facts & Advice from Mixed Text-Code Artifacts** | \\ **Identifying/Characterizing Facts & Advice from Mixed Text-Code Artifacts** | ||
+ | * Perform manual analysis of different kinds of mixed text-code artifacts to learn clues for facts of different kinds and positive and negative polarity advice. | ||
+ | * Develop a corpus of text and annotate with category information about facts and advice. | ||
+ | * Based on the learned clues or features, develop a rule-based system or machine-learning to automatically recognize the clues to identify different kinds of facts and advice in mixed text-code artifacts. | ||
+ | * Build a system based on the approach, evaluate, and refine the approach. | ||
\\ **Context-based Learning Nugget Analysis** | \\ **Context-based Learning Nugget Analysis** | ||
+ | * develop techniques to associate our mined learning nuggets with corresponding software components, | ||
+ | * implement, evaluate and refine the current techniques for representing and using developer context to extract the learning nuggets for the given context, using the established associations. |