How should I Test a Genetic Algorithm

Question

I have made a quite few genetic algorithms; they work (they find a reasonable solution quickly). But I have now discovered TDD. Is there a way to write a genetic algorithm (whic

Answer 1

One way I do for unit testing of non-deterministic functions of GA algorithms is put the election of random numbers in a different function of the logic one that uses that random numbers.

For example, if you have a function that takes a gene (vector of something) and takes two random points of the gene to do something with them (mutation or whatever), you can put the generation of the random numbers in a function, and then pass them along with the gene to another function that contains the logic given that numbers.

This way you can do TDD with the logic function and pass it certain genes and certain numbers, knowing exactly what the logic should do on the gene given that numbers and being able to write asserts on the modified gene.

Another way, to test with the generation of random numbers is externalizing that generation to another class, that could be accessed via a context or loaded from a config value, and using a different one for test executions. There would be two implementations of that class, one for production that generates actual random numbers, and another for testing, that would have ways to accept the numbers that later it will generate. Then in the test you could provide that certain numbers that the class will supply to the tested code.