Bug reports can be a great source of information, but usually finding the information requires extensive work in reading through all of the discussions and understanding the details about it.

Could it be that machine learning can be used to extract meaningful information out of that? That's what this project is about. The idea is to explore some different methods and see what the results are.

Here are some rough ideas on what to try:

  • clustering
  • sentiment analysis
  • filtering

As a dataset, the plan is to collect SLE bugs and openSUSE bugs from our very own bugzilla and use this data to train/validate some models.

Looking for hackers with the skills:

Nothing? Add some keywords!

This project is part of:

Hack Week 20

Activity

  • 9 months ago: ONalmpantis liked this project.
  • 9 months ago: acho liked this project.
  • 9 months ago: llansky3 liked this project.
  • 9 months ago: jufa liked this project.
  • 9 months ago: ories liked this project.
  • 9 months ago: mlnoga liked this project.
  • 10 months ago: j_renner liked this project.
  • 10 months ago: moio liked this project.
  • 10 months ago: hennevogel disliked this project.
  • 10 months ago: hennevogel liked this project.
  • All Activity

    Comments

    • alnovak
      10 months ago by alnovak | Reply

      I see two large sources of data that would be useful to include:

      • supportconfigs - these are either attached to Bugzilla, or available (short-term) on a filesystem - present great overview of our customers' environment

      • L3 metadata - for L3 bugs (~ 3000 / year), there are data that may be highly relevant for the clustering as well, among other:

        • customer identification
        • what PTFs (fixed packages) were delivered in the case, what was the feedback on those

      • gboiko
        10 months ago by gboiko | Reply

        Hi @alnovak

        Thank you for your feedback! I will try to include those as well in the analysis.

        Even though I already had in mind L3 metadata, I haven't thought of supportconfigs, nice hint, thank you!

    • mslacken
      9 months ago by mslacken | Reply

      I had the same idea last year, but did not really succeed. You might want to have a look at: https://github.com/mslacken/ml-bugs I also gave a talk at the Super Compute 2019: https://gitlab.suse.de/mslacken/sc-2019 Feel free to ping me, if you need any additional information.

      • gboiko
        9 months ago by gboiko | Reply

        Hi @mslacken

        Thank you for the pointers. I will take them a quick look and then I will certainly ping you about it.

        Enjoy hackweek :)

    Similar Projects

    This project is one of its kind!