KDb/Tests: Difference between revisions

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*Areas independent of drivers (e.g. data structures and high-level logic correctness, proper modeling).
*Areas independent of drivers (e.g. data structures and high-level logic correctness, proper modeling).
*Driver-dependent areas, e.g. correctness of translation of high-level data definitions to any driver that supports given feature. Because of this, following matrix is handy:
*Driver-dependent areas, e.g. correctness of translation of high-level data definitions to any driver that supports given feature. Because of this, following matrix is handy:


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'''Certain unit tests have small number of input test data''' (example: testing data correctness of data structures, when it is enough to cover typical and corner cases). '''Other tests need massive test data''' (example: SQL parser, data migration/conversion features). In the latter case it is useful to clearly separate in order to minimize repetitive work and risk of mistakes.
'''Certain unit tests have small number of input test data''' (example: testing data correctness of data structures, when it is enough to cover typical and corner cases). '''Other tests need massive test data''' (example: SQL parser, data migration/conversion features). In the latter case it is useful to clearly separate in order to minimize repetitive work and risk of mistakes.

Revision as of 20:04, 27 June 2012

Unit tests

Warning

The current unit test coverage in Predicate is poor. Volunteers wanted!


Introduction

Predicate has complex functionality and should be covered by unit tests. It has layered architecture:

[      Predicate             ]
[Driver A] [Driver B] ....

There are two areas to test:

  • Areas independent of drivers (e.g. data structures and high-level logic correctness, proper modeling).
  • Driver-dependent areas, e.g. correctness of translation of high-level data definitions to any driver that supports given feature. Because of this, following matrix is handy:


Test Driver A Driver B ...
Test 1 PASSED PASSED ...
Test 2 PASSED N/A ...
... ... ...


Certain unit tests have small number of input test data (example: testing data correctness of data structures, when it is enough to cover typical and corner cases). Other tests need massive test data (example: SQL parser, data migration/conversion features). In the latter case it is useful to clearly separate in order to minimize repetitive work and risk of mistakes.

Summing up, for any new set of test (e.g. for whole class), it is handy to develop test plan first, and reach agreement that the plan addresses the needs. Having a test that look as compete but in fact isn't, can have negative consequences for the project - defects can be still hidden.

Proposed workflow for given existing class includes initial test plan, initial set of tests and iterative plan updates, prioritization of tasks, and further tests implementation.

Summing up, tests are consisted of three main artifacts: plans, test data and implementation. All these should be provided for review on the Review Board. Massive data can provided for review using hyperlink references.

For new new classes/functions (or after extending functionality of existing ones) it is proposed add unit tests to ASAP, and publish them for review as a part of the review for the feature implementation itself.

Running unit tests

$ cd {BUILDDIR}/Predicate/tests
$ ctest --verbose

HOWTOs

Functional tests

Functional test predicatefeaturestest uses many parts of the APIs. They can be also used by newcomers to learn how to use Predicate APIs. predicatefeaturestest is built during the default build of Predicate, although it is not installed on make install.

To run the predicatefeaturestest test:

$ cd {BUILDDIR}/tests/features
$ less README # read README file to 

1. Full test for database, tables and data creation for SQLite:

$ ./predicatefeaturestest -t tables sqlite sqlitetest

On success, sqlitetest file will be created and the test says:

main: "tables" test: PASSED

2. Full test for database, tables and data creation for MySQL server:

$ ./predicatefeaturestest -p {mysql_password} -u {mysql_user} -t tables mysql mysqltest

On success, mysqltest server database will be created and the test says:

main: "tables" test: PASSED

Similarly to MySQL, predicatefeaturestest can run on top of PostgreSQL database (the driver is called postgresql).