Automated Testing (Unit Tests)

Table of Contents Aim Testing frameworks/libraries used CUnit Test framework Python unittest CTest(CMake Testing System) Code Progress C/C++ Functions testing SQL functions testing Writing New tests SQL Testing

Aim

To provide unit tests for the core functions(c++) and also to the wrapper functions(sql) to make it easier to check for bugs before committing changes.

Testing frameworks/libraries used

CUnit Test framework

• CUnit provides a framework for running tests against c/c++ code
• It is used by PostGIS to test its geometry library(liblwgeom)
• It is used to test core functions implementing routing algorithms and has the advantage that future integration with PostGIS will be a bit easier
• Link to project page

Python unittest

• `unittest` is an easy to use python testing framework
• It is used to test pl/pgsql functions using psycopg2 driver for PostgreSQL
• Link to unittest library

CTest(CMake Testing System)

• CTest is provided by CMake, the build system used by pgrouting
• Ties down the testing code into CMake configuration
• CTest is used to invoke the above two frameworks to test the c/c++ code as well as the core and wrapper SQL functions
• Link to CTest wikipage

Code

The code is under active development in a separate branch: https://github.com/justjkk/pgrouting/commits/unittests

Progress

C/C++ Functions testing

• Tests are written for validating boost wrapper of dijkstra implementation
• Have to write tests for other routing algorithm implementations like Astar, Shooting star, etc...

SQL functions testing

• The basic framework for creating test database, loading just compiled SQL functions, creating and populating test tables are done
• Very primitive testing for Dijkstra(proof of concept) is implemented
• Have to write tests for all core and wrapper SQL functions with diverse test data

Writing New tests

SQL Testing

• Add necessary sql files inside SetUpDB function in tests/.py
• Create yourdata.sql and yourdata.csv files under tests/loaders ( use simplegraph.csv and simplegraph.sql for the format )
• Create yourtest.py in tests/ using tests/test_dijkstra.py as reference
• Use loadTable() inside SetUp function of yourtest class and pass yourdata as argument to load yourdata.sql and yourdata.csv during testing
• Add yourtest.py inside tests/CMakeLists.txt
• Make sure you have a tests/settings.py copied from tests/settings.py.sample and filled with actual values
• cmake; make; make test to test the application
• Or run yourtest.py to run your test alone