Hi all,
We currently test the correctness of individual runtime operators using our integration tests but not the "released" algorithms. To be fair, we do test a subset of "simplified" algorithms on synthetic datasets and compare the accuracy with R. Also, we are testing subset of released algorithms using our Python tests, but it's intended purpose is to only test the integration of the APIs: Simplified algorithms: https://github.com/apache/incubator-systemml/tree/master/src/test/scripts/applications Released algorithms: https://github.com/apache/incubator-systemml/tree/master/scripts/algorithms Python tests: https://github.com/apache/incubator-systemml/tree/master/src/main/python/tests Though the released algorithm is tested when it is initially introduced, other artifacts (spark versions, API changes, engine improvements, etc) could cause them to return incorrect results over a period of time. Therefore, similar to our performance test suite ( https://github.com/apache/incubator-systemml/tree/master/scripts/perftest), I propose we create another test suite ("accuracy test suite" for lack of a better term) that compares the accuracy (or some other metric) of our released algorithms on standard datasets. Making it a requirement to add tests to accuracy test suite when adding the new algorithm will greatly improve the production-readiness of SystemML as well as serve as a usage guide too. This implies we run both the performance as well as accuracy test suite before our release. Alternative is to replace simplified algorithms with our released algorithms. Advantages of accuracy test suite approach: 1. No increase the running time of integration tests on Jenkins. 2. Accuracy test suite could use much larger datasets. 3. Accuracy test suite could include algorithms that take longer to converge (for example: Deep Learning algorithms). Advantage of replacing simplified algorithms: 1. No commit breaks any of the existing algorithms. Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar
