lumiera_/tests/16calculation.tests

TESTING "Library Test Suite: calculation" ./test-suite --group=calculation


TEST "Data Table with CSV storage" DataCSV_test <<END
return: 0
END


PLANNED "Statistic and Regression" Statistic_test << END
return: 0
END


TEST "Random numbers and Seed" Random_test << END
return: 0
END
Library: draft tests to document the new features Yesterday I decided to include some facilities I have written in 2022 for the Yoshimi-Testsuite. The intention is to use these as-is, and just to adapt them stylistically to the Lumiera code base. However — at least some basic documentation in the form of very basic unit-tests can be considered »acceptance criteria« 2024-03-11 17:44:19 +01:00			`TESTING "Library Test Suite: calculation" ./test-suite --group=calculation`



Library: complete coverage of CSV data table including storage also encompasses some coverage for the simplistic CSV format implemented as storage backend for this data table 2024-03-14 23:44:39 +01:00			`TEST "Data Table with CSV storage" DataCSV_test <<END`
Library: draft tests to document the new features Yesterday I decided to include some facilities I have written in 2022 for the Yoshimi-Testsuite. The intention is to use these as-is, and just to adapt them stylistically to the Lumiera code base. However — at least some basic documentation in the form of very basic unit-tests can be considered »acceptance criteria« 2024-03-11 17:44:19 +01:00			`return: 0`
			`END`


			`PLANNED "Statistic and Regression" Statistic_test << END`
			`return: 0`
			`END`
Library: some first thoughts regarding random number generation Relying on random numbers for verification and measurements is known to be problematic. At some point we are bound to control the seed values -- and in the actual application usage we want to record sequence seeding in the event log. Some initial thoughts regarding this intricate topic. * a low-ceremony drop-in replacement for rand() is required * we want the ability to pick-up and control each and every usage eventually * however, some usages explicitly require true randomness * the ability to use separate streams of random-number generation is desirable 2024-03-11 22:47:29 +01:00

Library: simple default implementation for random sequences Since this is a much more complicated topic, for now I decided to establish two instances through global variables: * a sequence seeded with a fixed starting value * another sequence seeded from a true entropy source What we actually need however is some kind of execution framework to define points of random-seeding and to capture seed values for reproducible tests. 2024-03-11 23:53:18 +01:00			`TEST "Random numbers and Seed" Random_test << END`
Library: some first thoughts regarding random number generation Relying on random numbers for verification and measurements is known to be problematic. At some point we are bound to control the seed values -- and in the actual application usage we want to record sequence seeding in the event log. Some initial thoughts regarding this intricate topic. * a low-ceremony drop-in replacement for rand() is required * we want the ability to pick-up and control each and every usage eventually * however, some usages explicitly require true randomness * the ability to use separate streams of random-number generation is desirable 2024-03-11 22:47:29 +01:00			`return: 0`
			`END`