What is instrumental?

instrumental is a structural coverage reporting tool. instrumental can tell you which parts of your program have been executed after it has been run. You can use this information to verify that your tests have executed your code and to determine which code has not been tested.

What’s the problem?

Testing is hard. Writing test cases is the easy part (and it isn’t always that easy). The hard part is determining which tests to write and which inputs to choose when you write those tests.

Let’s say that your code contains an ‘’‘and’‘’ decision that comprises three conditions as inputs. Maybe your decision looks like this:

(a == 4) and (b > 2) and c

We’ll assume that the three conditions (a == 4, b > 2, and c (is not False)) are significant. This should be a safe assumption to make; if those conditions don’t significantly affect the result of your program then they probably shouldn’t be in the code in the first place.

Since these are significant conditions, it is important to test them thoroughly. This means ensuring that there are tests that depend on each of the conditions to force the decision result to a predictable value. The way to do this is, when testing a particular condition, to hold the other conditions that can affect the result of the decision to particular values.

These ideas should be starting to feel familiar. This is what we do when we write unit tests; we isolate individual units so that we can verify their behaviour without having to worry about any other code confounding the results of our testing. So think of this as testing units within units. It isn’t possible to break the and decision into smaller functional units, but the other conditions can be effectively removed from the equation by holding them constant.

So then to test our first condition in our decision, a == 4, we’ll need to write at least two cases. We need one case in which a is 4 and one in which it isn’t. Further, we need to neutralize the other conditions. In the case of an and decision we do this by holding the other input conditions to True. This allows us to prove that if the result of the decision is True, then it must have been a taking a value of 4 that caused it. We can similarly prove that if the result of the decision is False then it must have been a taking a value other than 4 that was the cause. The following table illustrates input selections that do just this:

a b c
4 3 True
5 3 True

Inputs that fully test this decision might look like this:

a b c
4 3 True
5 3 True
4 2 True
4 3 False

If we display this as the result of evaluating the individual conditions, we get a table that looks like this:

True True True
False True True
True False True
True True False

You can see that we need a case where all conditions are True, and then we ‘walk’ the False across the conditions to get cases where the significant condition forces the parent decision False.

This is a simple case, but you can see that the kind of analysis involved here is non-trivial. When you extrapolate this to a realistic program, the analysis quickly becomes prohibitively time-consuming and tedious. This is where instrumental can help.

What does instrumental do?

instrumental executes your program for you. Upon completion, it can produce a report indicating whether or not the significant cases for a decision were executed.

What doesn’t instrumental do?

instrumental doesn’t currently provide branch coverage. We are unlikely to provide branch coverage any time soon since we provide decision coverage, a superset of branch coverage.