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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
Line 24: Line 24:
   * 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.
resarch/nlpa/research_proposal.1412280560.txt.gz · Last modified: 2014/10/02 16:09 by preethac
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