Github actions plugin to check flakiness of tests by calculating fliprates.
Project description
Flaky tests detection
Visualize tests whose state changes most often. During software development, it is often common that some tests start to randomly fail,
but finding those tests is a tedious and time consuming problem. Flaky tests detection solves that problem by processing historical xunit test
results and checks which tests changes state most often. Flaky tests detection is available as Github Action plugin and
Python package. For usage, see example
at the actions page.
Implementation is based on "Modeling and ranking flaky tests at Apple" by Kowalczyk, Emily & Nair, Karan & Gao, Zebao & Silberstein, Leo & Long, Teng & Memon, Atif.
Features
- Prints out top test names and their latest calculation window scores (normal fliprate and exponentially weighted moving average fliprate that take previous calculation windows into account).
- Calculation grouping options:
ndays.nruns.
- Heatmap visualization of the scores and history.
Parameters
Data options (choose one)
--test-history-csv- Give a path to a test history csv file which includes three fields:
timestamp,test_identifierandtest_status.
- Give a path to a test history csv file which includes three fields:
--junit-files- Give a path to a folder with
JUnittest results.
- Give a path to a folder with
Calculation options
-
--grouping-optiondaysto usendays for fliprate calculation windows.runsto usenruns for fliprate calculation windows.
-
--window-size- Fliprate calculation window size
n.
- Fliprate calculation window size
-
--window-count- History size for exponentially weighted moving average calculations.
-
--top-n- How many top highest scoring tests to print out.
Heatmap generation
--heatmap- Turn heatmap generation on.
- Two pictures generated: normal fliprate and exponentially weighted moving average fliprate score.
- Same parameters used as with the printed statistics.
Full examples
- Precomputed
test_history.csvwith daily calulations. 1 day windows, 7 day history and 5 tests printed out.--test-history-csv=example_history/test_history.csv --grouping-option=days --window-size=1 --window-count=7 --top-n=5
JUnitfiles with calculations per 5 runs. 15 runs history and 5 tests printed out.--junit-files=example_history/junit_files --grouping-option=runs --window-size=5 --window-count=3 --top-n=5
- Precomputed
test_history.csvwith daily calculations and heatmap generation. 1 day windows, 7 day history and 50 tests printed and generated to heatmaps.--test-history-csv=example_history/test_history.csv --grouping-option=days --window-size=1 --window-count=7 --top-n=50 --heatmap
Install module
make install
Install module and development packages
make install_dev
Run pytest
make run_test
Acknowledgement
The package was developed by F-Secure Corporation and University of Helsinki in the scope of IVVES project. This work was labelled by ITEA3 and funded by local authorities under grant agreement “ITEA-2019-18022-IVVES”
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