Testing Workflows – Test-First
- by Timothy Klenke
Originally posted on: http://geekswithblogs.net/TimothyK/archive/2014/05/30/testing-workflows-ndash-test-first.aspxThis is the second of two posts on some common strategies for approaching the job of writing tests. The previous post covered test-after workflows where as this will focus on test-first. Each workflow presented is a method of attack for adding tests to a project. The more tools in your tool belt the better. So here is a partial list of some test-first methodologies. Ping Pong Ping Pong is a methodology commonly used in pair programing. One developer will write a new failing test. Then they hand the keyboard to their partner. The partner writes the production code to get the test passing. The partner then writes the next test before passing the keyboard back to the original developer. The reasoning behind this testing methodology is to facilitate pair programming. That is to say that this testing methodology shares all the benefits of pair programming, including ensuring multiple team members are familiar with the code base (i.e. low bus number). Test Blazer Test Blazing, in some respects, is also a pairing strategy. The developers don’t work side by side on the same task at the same time. Instead one developer is dedicated to writing tests at their own desk. They write failing test after failing test, never touching the production code. With these tests they are defining the specification for the system. The developer most familiar with the specifications would be assigned this task. The next day or later in the same day another developer fetches the latest test suite. Their job is to write the production code to get those tests passing. Once all the tests pass they fetch from source control the latest version of the test project to get the newer tests. This methodology has some of the benefits of pair programming, namely lowering the bus number. This can be good way adding an extra developer to a project without slowing it down too much. The production coder isn’t slowed down writing tests. The tests are in another project from the production code, so there shouldn’t be any merge conflicts despite two developers working on the same solution. This methodology is also a good test for the tests. Can another developer figure out what system should do just by reading the tests? This question will be answered as the production coder works there way through the test blazer’s tests. Test Driven Development (TDD) TDD is a highly disciplined practice that calls for a new test and an new production code to be written every few minutes. There are strict rules for when you should be writing test or production code. You start by writing a failing (red) test, then write the simplest production code possible to get the code working (green), then you clean up the code (refactor). This is known as the red-green-refactor cycle. The goal of TDD isn’t the creation of a suite of tests, however that is an advantageous side effect. The real goal of TDD is to follow a practice that yields a better design. The practice is meant to push the design toward small, decoupled, modularized components. This is generally considered a better design that large, highly coupled ball of mud. TDD accomplishes this through the refactoring cycle. Refactoring is only possible to do safely when tests are in place. In order to use TDD developers must be trained in how to look for and repair code smells in the system. Through repairing these sections of smelly code (i.e. a refactoring) the design of the system emerges. For further information on TDD, I highly recommend the series “Is TDD Dead?”. It discusses its pros and cons and when it is best used. Acceptance Test Driven Development (ATDD) Whereas TDD focuses on small unit tests that concentrate on a small piece of the system, Acceptance Tests focuses on the larger integrated environment. Acceptance Tests usually correspond to user stories, which come directly from the customer. The unit tests focus on the inputs and outputs of smaller parts of the system, which are too low level to be of interest to the customer. ATDD generally uses the same tools as TDD. However, ATDD uses fewer mocks and test doubles than TDD. ATDD often complements TDD; they aren’t competing methods. A full test suite will usually consist of a large number of unit (created via TDD) tests and a smaller number of acceptance tests. Behaviour Driven Development (BDD) BDD is more about audience than workflow. BDD pushes the testing realm out towards the client. Developers, managers and the client all work together to define the tests. Typically different tooling is used for BDD than acceptance and unit testing. This is done because the audience is not just developers. Tools using the Gherkin family of languages allow for test scenarios to be described in an English format. Other tools such as MSpec or FitNesse also strive for highly readable behaviour driven test suites. Because these tests are public facing (viewable by people outside the development team), the terminology usually changes. You can’t get away with the same technobabble you can with unit tests written in a programming language that only developers understand. For starters, they usually aren’t called tests. Usually they’re called “examples”, “behaviours”, “scenarios”, or “specifications”. This may seem like a very subtle difference, but I’ve seen this small terminology change have a huge impact on the acceptance of the process. Many people have a bias that testing is something that comes at the end of a project. When you say we need to define the tests at the start of the project many people will immediately give that a lower priority on the project schedule. But if you say we need to define the specification or behaviour of the system before we can start, you’ll get more cooperation. Keep these test-first and test-after workflows in your tool belt. With them you’ll be able to find new opportunities to apply them.
