CSC/ECE 517 Spring 2017/OSS M1706 Tracking intermittent test failures over time
This is a request from the Servo OSS project to reduce the impact intermittent test failures have on the software. The request made is for a Flask service using Python 2.7. The intermittent test failure tracker stores information regarding a test that fails intermittently and also provides means to quickly query for tests that have failed.
Scope
The intermittent test failure tracker initial steps include:
- Build a flask service
- Use a JSON file to store information
- Request/create required parameters: Test file, platform, test machine (builder), and related GitHub pull request number
- Allow querying the store results given a particular test file name
- Use the known intermittent issue tracker as an example of a Simple flask server
Subsequent steps include:
- Add ability to query the service by a date range, to find out which were occurred the most often
- Build an HTML front-end to the service that queries using JS and reports the results
- Links to GitHub
- Sorting
- Make filter-intermittents command record a separate failure for each intermittent failure encountered
- Propogate the required information for recording failures in saltfs
Design
Application Flow
Saving a Test
The servo build agent calls a webhook inside the test tracker. The webhook then calls a handler that contains any business logic necessary to transform the request. Finally the handler persists the request into the db, in this case a json file. This flow can be seen in the graph below.
+---------------------------------------------+ | Intermittent Test Failure Tracker | | | +--------------+ | +-----------+ +---------+ +------+ | | | | | | | | | | | +--------+ | Servo | | | | | | | | | | | | Build +------> webhook +------> handler +----> db +---------> json | | Server | | | | | | | | | | file | | | | | | | | | | | | | +--------------+ | +-----------+ +---------+ +------+ | +--------+ | | +---------------------------------------------+
Implementation
The implementation is entirely influenced by the request, the servo team clearly defines what the service should do and how it would be made.
Data model
The model for an intermittent test is defined mostly by the request with a few additions to help with querying in later steps of the OSS request.
Name | Type | Description |
---|---|---|
test_file | String | Name of the intermittent test file |
platform | String | Platform the test failed on |
builder | String | The test machine (builder) the test failed on |
number | Integer | The GitHub pull request number |
fail_date | ISO date (String) | Date of the failure |
Datastore
To store the intermittent test failures, a library called TinyDB is used. This library is a native python library that provides convenient SQL command like helpers around a JSON file to more easily use it like a database. The format of the JSON file is simply an array of JSON objects, making the file easily human readable.
Flask Service
Flask is a microservice framework written in Python. A flask service is a REST (representational state transfer) API that maps URL and HTTP verbs to python functions. Some basic examples of flask routes:
@app.route('/') def index(): return 'Index page' @app.route('/user/<username>') def show_user(username): return db.lookup(username)
The first method returns 'index page' at the root URL. The second method accepts a URL param after user and returns the user from a database.
Submission
The work has been started in a new GitHub repo located here. When servo developers are ready, the project will be pulled in to the servo project on GitHub.