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'./mach try auto' for ESR 115 repository causes decision task timeout due to bugbug timeout

1

'./mach try auto' had been executed for the ESR 115 tree by a developer twice and it failed each time due to a bugbug timeout during the run of the...

Archaeopteryx

Today (1 day after merge day) the report says: “No crashes in the top 200 for Nightly.” I assume the bot already checked for [116.0a1](https://crash-stats.mozilla.org/topcrashers/?product=Firefox&version=116.0a1) , not [115.0a1](https://crash-stats.mozilla.org/topcrashers/?product=Firefox&version=115.0a1)

jensstutte

Automatic fix suggestion from past development history

1

Create a tool using rust-code-analysis and ML to find similar snippets of code and: - suggest fixes from past bug fixes to new patches (prevent reintroducing some bugs); - if...

marco-c

Make Regression model training set consist only of defects

3

Now that we finally have the bug type, we can make the Regressor model differentiate between defects which are regressions and defects which are not regressions, rather than between defects...

marco-c

Try using spaCy text classifier

3

We could try using the text classifier available in spaCy instead of gradient boosting and see how it behaves.

marco-c

Try using tries to store DictVectorizer and Count/TfidfVectorizer vocabularies

1

This should reduce memory usage. See also https://github.com/scikit-learn/scikit-learn/issues/2639.

marco-c

Evaluate switching to pickle DBs

2

They should be faster to read and write (we need to confirm).

marco-c

Create a model to identify bugs worth tracking

2

This is to automatically suggest bugs worth tracking / detect potential dot-release drivers early.

marco-c

Try using different textual features

5

Right now we are using `TfidfVectorizer` with its default options (basically word 1-gram). We should try a few different options and see how the accuracy changes: - [ ] word...

marco-c

Predict which lines of a crash trace are most informative for localizing the source of a crash

1

Experiment using the approaches described in [Scaffle: Bug Localization on Millions of Files](https://software-lab.org/publications/issta2020_Scaffle.pdf) and [Industry-scale IR-based Bug Localization](https://arxiv.org/pdf/2010.09977.pdf)

suhaibmujahid