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Mozilla’s Browser to Generate Bug Reports Through AI

Mozilla announced in a blog on April 9, 2019, that it has optimized the method to segregate bugs in projects such as Firefox. The company is using BugBug, a Machine Learning powered open-source Bugzilla tool to segregate bugs by product and by components. Hence bug reports will now be filtered by –

  • Firefox
  • Firefox for Android
  • Thunderbird
  • Subsets
  • Products

For Mozilla, this was not an easy task. The tool required over two years to be built — training the tool to automatically detect and slot bugs into components and products took 100,000 bugs. Add that with an indisposed data set if the bug changed in function, for the tool only operational after screening and prioritization of the bug. The workaround to this (or the fix) for Mozilla was to roll-back these ‘rogue’ bugs and re-filter it.

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“Getting bugs to the right eyes as soon as possible is essential in order to fix them quickly,” Mozilla’s Marco Castelluccio and Sylvestre Ledru wrote. “Historically, the product/component assignment has been mostly done manually by volunteers and some developers. [but] unfortunately, this process fails to scale, and it is an effort that would be better spent elsewhere.”

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Then, with this set-up, Mozilla built the model which took around 40 minutes as compared to a whole week it takes for manual bug assessment. Castelluccio and Ledru said that since the model’s deployment since February 2019, 350 bugs have been triaged with a 90 percent accuracy rate. Also, Machine Learning ensures that the tool only begins its operation if it is at least 60% sure of its decision.

“By presenting new bugs quickly to triage owners, we hope to decrease the turnaround time to fix new issues,” Castelluccio and Ledru said.

BugBug, at the moment, is only available for Mozilla products but the company is confident that it will release the tool across various platforms.

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