Business-Friendly Functional Programming – Part 1: Asynchronous Operations

Recently, we refactored one of our micro-services in order to apply the Each library. Each is a macro library developed by Thoughtworks that converts native imperative syntax to scalaz‘s monadic expressions. This means that we can write, among other things, asynchronous code with Futures in a plain imperative style.

The micro-service is a Scala application that serves as a RESTful server. It receives requests from browsers. For each of the requests, the micro-service fetches data from other internal RESTful servers, composites these data into one response, and sends the response to browsers.
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Language use at REA

As previously discussed we’re pretty keen on micro services at REA. Our delivery teams are organised around small, autonomous “squads” that get to choose pretty much any language and technology stack they wish to implement their solutions.

This inevitably leads to a fairly broad church of language use. 🙂

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To Kill a Mockingtest

Please don’t use mocks or stubs in tests.  While they are seemingly ubiquitous in enterprise development, they have serious drawbacks, and typically mask easily fixable deficiencies in the underlying code.

Even their most ardent defenders concede that mocks and stubs have flaws. These include:

Dependence on fragile implementation details

Mocks and stubs require intimate knowledge of how code interacts with other modules.  Even if the implementation is correctly refactored without altering public contracts, these tests will tend to break, and draw your attention away from more productive tasks.

Testing incidental properties with no bearing on correctness

What is the point of this code?  This is an essential question to ask, in order to understand it.  Tests have a story to tell here, and mocks invariably tell the wrong one.  Is the point of makeCoffee() that we made a coffee, or that we opened the fridge to get the milk?  When we payShopkeeper(), do we care that we completed a transaction, or that we rummaged though our wallet for change?  When mocking tests fail, the poor maintainer is left to reconstruct the real intent from a trail of indirect clues and anecdotes.

Web of lies

It is good practice to write data structures that are correct-by-construction; any constructor or sequence of method calls is guaranteed to leave the data in a meaningful state.  Stubs introduce test-only fictions that are stripped of any of the safety latches and guarantees that may have been built in; they introduce fresh sources of error that are not present in the codebase.  There is no value in detecting any failure that arises in such a way.

As time goes on, lies beget more lies.  It is not unusual for a stubbed input in one place to result in another here, and another there; the fiction leaks and spreads into some kind of evil facsimile of the original code, but with more bulk, complexity and defects.

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Feeling Validated – A different way to validate your input

TL;DR

The following post is a Scala example of validating input into your software.  We use Scala, but you can do this in many other languages like Ruby, JavaScript and even Java!  After trying a more traditional approach we then use a type called Validation to encode our business rules.  It’s a different way of thinking.  It uses the Scalaz library.

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The abject failure of weak typing

More discussion on Hacker News, and the Clojure, Haskell, Rust and Programming subs on Reddit.

Over the last few years of maintaining code old and new at REA, it has become abundantly clear that the neglect and misuse of type-systems has had a sharply negative impact on our codebases. Here we address the concrete causes and consequences, and propose concrete and achievable solutions.

Types at REA

REA’s codebases vary between statically typed languages such as Java and Scala on one hand, and “dynamic” languages such as Ruby, Javascript, and Perl on the other. I’ll mostly leave the dynamic ones alone — while the same arguments obviously apply, they are what they are. However, if we are paying for the conceptual overhead of a static type system, we need to be sure we are using it effectively; otherwise we are simply writing the same old Ruby play-dough but with long build-times and cumbersome syntax. Used properly, the tradeoff of static types is overwhelmingly beneficial. Continue reading