Your database needs unit tests: no excuses

The test pyramid is a well-known visualization aid to classify software tests. As you climb the steps towards greater integration of components, you proceed from many, detailed, fast and isolated tests towards fewer, slower and more global tests that validate the system as a whole. It makes good sense in principle but it’s harder to explain how the stratification between unit-, integration and end-to-end tests is supposed to work. Opinions differ on what parts to integrate at which layer in the pyramid. You would think the database belongs in the upper strata, because it is expensive to set up and run. Yet it also makes sense to integrate it at the lower, detailed stage in the pyramid when it contains business-critical logic that requires detailed validation. It often needs the kind of rigorous validation that you cannot leave to a few slow, global integration tests. But let’s start with a recap of the definition of a unit test.

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The subtle art of cache configuration

Summary: It’s deceptively simple to enable caching in Spring, but you must investigate actual production usage in order to configure it properly. There are four areas of concern: peak-time load, uniqueness of requests, savings in time and resources, and the longevity of cacheable values. An example project shows these concerns in action.

I like the topic of caching in Java code. It’s a technique where the Platonic world of clean code meets actual usage. You can never tell just by looking at code whether caching is a good idea or unnecessary optimization. You need to measure or at least predict realistic production loads.

Maybe the Spring framework had made it a little too easy. With minimal boilerplate you can configure any managed object to return cached responses upon repeated requests. Call it once to run the method body, call it twice and the framework intervenes and returns the result of the first call. You can (well, must) plug in a full featured third-party implementation like Caffeine or ehcache to enable things like disk overflow and automatic eviction. 

Container terminal, Port of Rotterdam
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User-friendly API publishing and testing with Retrofit

SUMMARY: Any web service needs to export their public API if consumers want to make the best use of that service. A developer-friendly approach to do so if you work in the Java ecosystem is to package DTOs and endpoint interfaces in an API jar file and use the Retrofit framework to create type-safe clients for integration testing. This article discusses a complete example.

If you’ve worked in enterprise Java projects you will remember good old Web Services Description Language, the XML based format for describing network services by IBM and Microsoft. Maybe you still work with it? WSDL and its twin XML Schema are among those W3C standards that seasoned developers love to hate. Its specification files are not very human readable, let alone human writable. Fortunately you don’t have to. They can be generated by your server endpoint and fed straight into a code generator to create transfer objects (dtos) and service stubs.

Retrofest in Tenterden, Kent. World War 2 Theme Day.
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You don’t need orthodox TDD to code well

There is plenty of opinions on how to do Test-Driven Development well. Today I want to discuss the drawbacks of the orthodox TDD school, let’s call it OTDD. Although as a development method it lacks a how-to bible like the Scrum Guide, some proponents defend their take with a religious level of conviction. To my understanding OTDD has the following characteristics:

  • You start by writing a failing test against a skeleton implementation. Then you dress it up by implementing the scenario, making the test pass. Test and production code evolve strictly in tandem, and you typically have a one-to-one relationship between a test suite and a source file, usually a class.
  • It follows then that all dependencies of a class under test must be set up using test doubles (spies, stubs or mocks). This applies not only to unmanaged, out-of-process dependencies like database, network and file handles, but also to any class in your own deliverable.
Dressing up a skeleton. No, I didn’t google this photo. I took it in Hastings (2014)
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Unit tests are a liability, and I am not being ironic.

I have always been an advocate of proper unit testing. I believe it is a necessary attribute of building maintainable software. I also thought myself pretty experienced in writing sensible (unit) tests, but reading Unit Testing Principles, Practices and Patterns was an eye-opener in several ways. Vladimir Khorikov spends his 300+ pages teaching us what distinguishes high-quality tests from the time wasters. He assumes you know your way around the tooling already. It’s not a hard book and if you have testing experience you should get through it quickly. The examples are in C# but translate easily to Java. Let me summarize what has stuck with me most.

Scaffolding work in the historic town of Sandwich, Kent
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