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Detection of Programming Difficulties

Detection of Programming Difficulties. Nils Erik Persson University of North Carolina at Chapel Hill npersson@cs.unc.edu Advisor: Prasun Dewan. Motivation. As programmers, we experience difficulty constantly We seek assistance from the internet, colleagues, superiors, etc.

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Detection of Programming Difficulties

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  1. Detection of Programming Difficulties Nils Erik Persson University of North Carolina at Chapel Hill npersson@cs.unc.edu Advisor: Prasun Dewan

  2. Motivation • As programmers, we experience difficulty constantly • We seek assistance from the internet, colleagues, superiors, etc. • Search time and energy is a barrier to all of these

  3. Vision • Create a difficulty recommendation system that can: • Detect user difficulty • Determine the current task • Provide reasonable assistance

  4. Project Goal • Develop the framework to support classification and assistance

  5. Task Overview • Capture all words in user’s code • Determine keywords • Capture searches in browser logs • Store/update keyword -> search mappings in a database • Recommend searches based on keywords to the user

  6. What You’ll Learn • Eclipse plugin development • Chrome extension development • Database creation and management • Distributed systems (centralized server with multiple clients) • Machine learning (classification)

  7. Classification Example • Count of words created from underlying code over time • Document states clustered based on the counts Cluster/ Topic Document state word counts

  8. Classification Example • Determine which words are important for each cluster • Look at relative weights of each word on classification • Label topics with these words!

  9. Questions?

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