# Guide

## Same interface for all test generators

### Increase coverage for subsets of parameters

Sometimes there are a few parameters that are more important to test fully. In that case, choose a base-level coverage for the whole test set, such as the 2-way coverage of all-pairs. Then pass a separate argument to request that the subset of parameters have greater coverage.

For instance, this requrests that the first, third, and fourth parameters have 3-way coverage, meaning full-factorial, while the second parameter has only 2-way coverage. This is more meaningful when there are lots of parameters.

test_set = all_pairs(
[1, 2, 3], ["low", "mid" ,"high"], [1.0, 3.7, 4.9], [:greedy, :relax, :optim];
wayness = Dict(3 => [[1, 3, 4]])
)
27-element Array{Array{Any,1},1}:
[1, "low", 1.0, :greedy]
[1, "mid", 1.0, :relax]
[1, "high", 1.0, :optim]
[1, "low", 3.7, :greedy]
[1, "mid", 3.7, :relax]
[1, "high", 3.7, :optim]
[1, "low", 4.9, :greedy]
[1, "high", 4.9, :relax]
[1, "mid", 4.9, :optim]
[2, "low", 1.0, :greedy]
⋮
[3, "low", 1.0, :greedy]
[3, "mid", 1.0, :relax]
[3, "high", 1.0, :optim]
[3, "low", 3.7, :greedy]
[3, "mid", 3.7, :relax]
[3, "high", 3.7, :optim]
[3, "low", 4.9, :greedy]
[3, "mid", 4.9, :relax]
[3, "high", 4.9, :optim]

The wayness argument is a dictionary, where the dictionary keys are the higher coverage levels, so "3" means all triples. The dictionary values are an array of arrays of parameter indices which, together, should be covered at the given level. This means that, were you to have 40 parameters, you could request that parameters [3:6] and parameters [25:30] be covered with triples.

array_of_forty_parameters = fill(1:4, 40)
test_set = all_pairs(
array_of_forty_parameters...;
wayness = Dict(3 => [[3:6], [25:30]])
)

## Exclude forbidden combinations of parameters

Keep the test engine from making tests that aren't allowed for your function. Pass it a filter function, one that returns true whenever a parameter combinations is forbidden.

disallow(n, level, value, kind) = level == "high" && kind == :optim
test_set = all_pairs(
[1, 2, 3], ["low", "mid" ,"high"], [1.0, 3.7, 4.9], [:greedy, :relax, :optim];
disallow = disallow
)
11-element Array{Array{Any,1},1}:
[1, "low", 1.0, :greedy]
[1, "mid", 3.7, :relax]
[1, "high", 4.9, :greedy]
[2, "low", 3.7, :optim]
[2, "mid", 1.0, :greedy]
[2, "high", 1.0, :relax]
[3, "low", 4.9, :relax]
[3, "mid", 1.0, :optim]
[3, "high", 3.7, :greedy]
[2, "mid", 4.9, :optim]
[1, "low", 3.7, :optim]

There are two problems with excluding values.

1. The disallow function needs to handle possible nothing arguments. The generator will call this function on partially-constructed argument lists, and it will pass nothing for those arguments that have not yet been chosen.

2. The generator may fail to find a solution if there is a disallow list. Both the IPOG and GND generators can get stuck when there are rules that forbid combinations. It depends on the combinations and some luck. When it does fail, you will see the code try to access a vector at location 0.

There are papers that solve these problems by pairing tuple generation with logic solvers. That sounds great. It isn't implemented here.

## Seed test cases

If there are particular tests that must be run, these already include some of the tuples that should be covered. You can pass the must-run test cases, and they will be included among the test cases.

must_test = [[1, "mid", 3.7, :relax], [1, "mid", 4.9, :relax]]
test_cases = all_pairs(
[1, 2, 3], ["low", "mid" ,"high"], [1.0, 3.7, 4.9], [:greedy, :relax, :optim];
seeds = must_test
)
12-element Array{Array{Any,1},1}:
[1, "mid", 3.7, :relax]
[1, "mid", 4.9, :relax]
[1, "low", 1.0, :greedy]
[1, "high", 1.0, :optim]
[2, "low", 3.7, :optim]
[2, "mid", 1.0, :greedy]
[2, "high", 4.9, :greedy]
[3, "low", 4.9, :relax]
[3, "mid", 1.0, :optim]
[3, "high", 3.7, :greedy]
[2, "high", 1.0, :relax]
[3, "low", 4.9, :optim]

The must-run cases are a list of arrays of arguments.