Skip to main content

Why are you not using Design by Contract?

When learning to program I distinctly remember coming across the concept of placing asserts within your code. Assert statements are primarily used for "things that cannot happen", but in my early days I was too focused on the stuff that was supposed to happen!

"Defensive programming" was also introduced. Principles such as "Never trust the user" and "80% of your code will be validation and verification" were highlighted. Despite these introductions many years ago, the concept of asserts never stuck with me. Yet I program defensively like there is no tomorrow.

The use of asserts can be extended into "Design by Contract" or DBC. In DBC the developer makes use of pre-conditions, post-conditions and invariants. Some languages such as Effiel have taken DBC as a core feature while other languages leave DBC up to libraries.

One of my favourite programming books is the Pragmatic Programmer. Having stood up to many re-reads I always found myself intrigued by the idea of DBC. Yet I never found myself following this interest through, at least in a production environment.

Our team recently came across a bug in which part of the system was using a component in a way which was deemed invalid. We had a suite of tests to accompany this feature, but these tests were unable to highlight the problem. When the object was sent across the wire, the Javascript front end was firing a null reference across, this was out of our control in the back end of the application. As the feature crossed a boundary and spoke to another system defensive programming would have been difficult. All we could do was error and inform the developer what was wrong. Even without defensive programming, the system was currently doing this anyway. We had little to gain.

Here I decided to experiment for the first time in my programming career with code contracts. A contract was applied that said the collection sent into the system must not be null or empty. If so, the second system would blow up informing the developer what was wrong. This contract was a very primitive example of a pre-condition - something that must be true in order for the rest of the following code to execute.

The benefit here came from just a few mere lines of code. Had we tried to program defensively the second systems' code base would have suffered for little gain. We would need to report the error, add error codes, introduce exception handling and so on, all for a simple defect that could be fixed immediately and potentially never occur again once the developer integrating has configured the components correctly.

One important factor to consider with DBC is the contract violations should never be caught or handled. Every single contract that is violated is a bug. To stop the violation you need to fix the code that is breaking the contract. Likewise contracts make little sense when dealing with a public API. On the edge of the system you should presume your users will make mistakes and "do the wrong thing", here you must use defensive programming.

Since this day I've liberally applied code contracts whenever we cross system boundaries or interact with the infrastructural aspects of our code, e.g. database helpers. This has increased my confidence that the system as a whole has been correctly "glued together". Another benefit is several bugs have been thwarted thanks to the contracts as unlike unit tests, contracts are always present when enabled, meaning missed boundary conditions can easily be detected.

Hand in hand with our automated test suite, code contracts make a great companion. Never alone will one suffice, but when used in conjunction they can be extremely powerful. So the question is, why aren't you using them?


Popular posts from this blog

Three Steps to Code Quality via TDD

Common complaints and problems that I've both encountered and hear other developers raise when it comes to the practice of Test Driven Development are: Impossible to refactor without all the tests breakingMinor changes require hours of changes to test codeTest setup is huge, slow to write and difficult to understandThe use of test doubles (mocks, stubs and fakes is confusing)Over the next three posts I will demonstrate three easy steps that can resolve the problems above. In turn this will allow developers to gain one of the benefits that TDD promises - the ability to refactor your code mercifully in order to improve code quality.StepsStop Making Everything PublicLimit the Amount of Dependencies you Use A Unit is Not Always a Method or ClassCode quality is a tricky subject and highly subjective, however if you follow the three guidelines above you should have the ability to radically change implementation details and therefore improve code quality when needed.

DRY vs DAMP in Tests

In the previous post I mentioned that duplication in tests is not always bad. Sometimes duplication becomes a problem. Tests can become large or virtually identically excluding a few lines. Changes to these tests can take a while and increase the maintenance overhead. At this point, DRY violations need to be resolved.SolutionsTest HelpersA common solution is to extract common functionality into setup methods or other helper utilities. While this will remove and reduce duplication this can make tests a bit harder to read as the test is now split amongst unrelated components. There is a limit to how useful such extractions can help as each test may need to do something slightly differently.DAMP - Descriptive and Meaningful PhrasesDescriptive and Meaningful Phrases is the alter ego of DRY. DAMP tests often use the builder pattern to construct the System Under Test. This allows calls to be chained in a fluent API style, similar to the Page Object Pattern. Internally the implementation wil…

Coding In the Real World

As a student when confronted with a problem, I would end up coding it and thinking - how do the professionals do this?For some reason I had the impression that once I entered the industry I would find enlightenment. Discovering the one true way to write high quality, professional code.It turns out that code in industry is not too far removed from the code I was writing back when I knew very little.Code in the real world can be:messy or cleanhard or easy to understandsimple or complexeasy or hard to changeor any combination of the aboveVery rarely will you be confronted with a problem that is difficult. Most challenges typically are formed around individuals and processes, rather than day to day coding. Years later I finally have the answer. Code in the real world is not that much different to code we were all writing when we first started out.If I could offer myself some advice back in those early days it would be to follow KISS, YAGNI and DRY religiously. The rest will fall into plac…

Feature Toggles

I'm a fan of regular releasing. My background and experience leads me to release as regularly as possible. There are numerous benefits to regular releases; limited risk, slicker release processes and the ability to change as requirements evolve.The problem with this concept is how can you release when features are not functionally complete?SolutionIf there is still work in progress, one solution to allow frequent releases is to use feature toggles. Feature toggles are simple conditional statements that are either enabled or disabled based on some condition.This simple example shows a feature toggle for an "Edit User" feature. If the boolean condition is false, then we only show the "New User" feature and the "Admin" feature. This boolean value will be provided by various means, usually a configuration file. This means at certain points we can change this value in order to demonstrate the "Edit User" functionality. Our demo environment could …

Reused Abstraction Principle

This is the second part of my series on abstractions.Part 1 - AbstractionsPart 3 - Dependency Elimination PrincipleThe Reused Abstraction Principle is a simple in concept in practice, but oddly rarely followed in typical enterprise development. I myself have been incredibly guilty of this in the past.Most code bases have a 1:1 mapping of interfaces to implementations. Usually this is the sign of TDD or automated testing being applied badly. The majority of these interfaces are wrong. 1:1 mappings between interfaces and implementations is a code smell.Such situations are usually the result of extracting an interface from an implementation, rather than having the client drive behaviour.These interfaces are also often bad abstractions, known as "leaky abstractions". As I've discussed previously, these abstractions tend to offer nothing more than simple indirection.ExampleApply the "rule of three". If there is only ever one implementation, then you don't need …