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* Build # Building out auto-classification tooling to be able to handle more types of intermittent failure types.*#* Create an engine that will automatically match failures and annotate them properlybuilding #* Building a user interface inside of Treeherder for annotating/matching failures
→Treeherder: Clarifications & fix formatting
=== Treeherder ===
'''Mentor: ''' Ed Morley and Cameron Dawson<br />'''IRC: ''' #treeherder (emorley or camdOverview: Treeherder is the web application for visualising continuous integration tasks used to build and test Firefox. Treeherder processes a lot of data everyday to be able to visualise this data.It's used by Firefox devs to check whether their new code works, by release managers to decide whether to include a new feature in the next version of Firefox.)
'''Overview:''' [[EngineeringProductivity/Projects/Treeherder|Treeherder]] is the web application for visualising continuous integration tasks used to build and test Firefox. Treeherder processes a lot of data everyday to be able to visualise this data. It's used by Firefox devs to check whether their new code works, and by release managers to decide whether to include a new feature in the next version of Firefox. Inside this data we have a number of failures that occur and are intermittent making it difficult to track and reproduce: “When . When a developer tests out code, they want to know:"Did my code cause any regressions?” ". Currently this can be difficult to figure out.
We need to start building up metrics on these to help engineering teams know which intermittent failures are important and which are not.
You will be working on '''one ''' of the following:* # Visualising intermittents and their regularity*#* Create a frontend to visual historical trends of failures with creative ways to browser and compare. This will be used by developers and sheriffs who are trying to fix these failures.#** building Building a user interface inside of Treeherder for annotating/matching failures*#* Create a backend for storing unique identifiers for failures which will be referenced by an auto classification engine, the frontend for annotating, and the historical view for finding trends
You will need to know a little bit of the following and learn the rest as you go:
* Python(for use with the Django/Django REST framework backend)* JavaScript (For using for use with the React or /AngularJSfrontend)
* HTML/CSS
