1 / 5

Exploring Source Code with Latent Dirichlet Allocation

This paper by Trevor Savage, Bogdan Dit, Malcom Gethers, and Denys Poshyvanyk discusses Latent Dirichlet Allocation (LDA) for exploring topics in source code. LDA is a probabilistic topic model that represents documents as mixtures of topics. The paper introduces the concept of Maximal Weighted Entropy (MWE) to capture the average probability and distribution of topics, enabling a deeper understanding of source code structures. This presentation was given at the 26th IEEE International Conference on Software Maintenance in Timișoara, Romania on September 16, 2010. For more information, visit SEMERU at William and Mary: http://www.cs.wm.edu/semeru/TopicXP

grunewald
Download Presentation

Exploring Source Code with Latent Dirichlet Allocation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. TopicXP: Exploring Topics in Source Code using Latent Dirichlet Allocation Trevor Savage, Bogdan Dit,Malcom Gethers and Denys Poshyvanyk 26th IEEE International Conference on Software Maintenance Timişoara, Romania September 16, 2010

  2. Latent Dirichlet Allocation (LDA) • Probabilistic Topic Models (Latent Dirichlet Allocation –LDA [Blei’03]) • Models documents as mixture of topics

  3. Maximal Weighted Entropy (MWE) • Occupancy(tj) captures the average probability of topic tj • Distribution (tj) captures distribution of tj using information entropy • MWE(Cj)=max(Occupancy(tj) x Distribution (tj))

  4. Demonstration

  5. Thank you. Questions? SEMERU @ William and Mary http://www.cs.wm.edu/semeru/TopicXP

More Related