Better Isolate Than Never

How do you test a product with distributed logic and non-deterministic components? Well, it depends on the product and when the question is asked. This post is one answer, for now.

A service I work on exposes an API for internal and external clients and calls multiple other services. It orchestrates a reasonably complex journey for a user, with their inputs and the responses of the services determining each step.

Our customers can configure the service to provide a variant of the standard journey for their users. This gives them choices on the available steps, the order of the steps, and, importantly, some of the logic for taking particular steps. This configuration lives in a different repository to the service, not owned by us, and it can be changed and deployed independently from the service.

As you can imagine, we test our service in multiple ways at different granularities using the usual tooling, including unit tests for the core pieces of functionality of the service, integration tests that hit the service's endpoints in different scenarios, and end-to-end tests that run against a live service and dependencies.

The usual trade-offs of all of those approaches apply but the concern that has exercised us for a while is the gap between those tests and the additional logic described in the configurations. That, and the fact that some of the other services are not owned by us, not hosted by us, or are non-deterministic because LLMs.

Naturally we have in-repo checks to cover variant configurations, but it's the combination of service and configuration that determine the available paths and the scenarios in which specific options are allowed. If we change either, then we'd like to know that the journeys our customers want are still available, under the conditions they have specified, long before that combination hits production. (And let's take it as read that we can't move the external logic into our world at the moment.)

What we felt we needed was something along these lines: use real configurations from a nominated branch, use a nominated service version, hit the API not the FE, run locally or in CI, and cover all customer configurations ... but target the important special cases only. Also the usual stuff: be readable, understandable, maintainable, and extensible; provide useful debugging information; run reliably and quickly.

Where we're at currently is a test suite in the service's repo using a single Dockerised Wiremock instance for all of the dependency services. In CI we run our service in the Docker container too. There's a thin DSL for journey navigation and a clear structure to the tests and test data.

The core of this setup is that mocking makes the runs fast and deterministic; the control we have with the mocks means we can target very specific paths; collecting mocked responses by scenario makes them much easier to find and read than having them buried deep in code; using a single Wiremock instance makes housekeeping straightforward.

Allowing any service version to run against any set of configurations gives us an easy way to compare any combo that's interesting at any point and restricting to just the key scenarios (we hope) helps us to keep a lid on maintenance.

--00--

To sketch in some detail, Wiremock's standalone server deals with two different file types: stub responses (in a mappings directory) and JSON payloads (in __files). Stub files map an incoming URL to an outgoing response, optionally using a payload from __files.

Here's how our Wiremock configuration is structured:

Each scenario has its own response files for the services that are involved in that scenario. For example, scenario 2 involves two other services, but scenario 3 only one.

We write stub files per service, setting them up so that their response payload comes from a file of the same name, so mappings/service1.json returns the contents of current/service1.json.

The __files/current directory is mounted by the Docker container. As part of the setup for each scenario, we copy the relevant files into it and ask Wiremock to re-read them. Although Wiremock provides an admin API for updating responses, we found that copying files on disk was more reliable for us even it it's frankly pretty clunky.

The test code has functions like the ones below in classes per scenario, using operators like submit from our DSL to move through steps in the journey and standard test framework assertions on expected state.

@ConfigurationTest(only = [Config.A, Config.B])
fun Scenario2_AB(config: Configuration) {
	setMockResponses("scenario2")
	journey(config) {
		expect { ... }
		submit(...) expect { Result_AB }
		...
	}
}
	
@ConfigurationTest(only = [Config.C, Config.D])
fun Scenario2_CD(config: Configuration) {
	setMockResponses("scenario2")
	journey(config) {
		expect { ... }
		submit(...) expect { Result_CD }
		...
	}
}

The setMockResponses() call does test setup and the @ConfigurationTest custom annotation arranges a parameterised test and the values to run it on. In the example above, the only key shows clearly which configs can share a particular test function and in the example below, the except keyword specifies the case that is different to the rest.

@ConfigurationTest(except = [Config.E])
fun Scenario3_Default(config: Configuration) {
	setMockResponses("scenario3")
	journey(config) {
		...
	}
}
	
@ConfigurationTest([Config.E])
fun Scenario3_E(config: Configuration) {
	setMockResponses("scenario3")
	journey(config) {
		...
	}
}

The mock responses are JSON payloads and are as real as they need to be to exercise the particular logic combination that the scenario cares about and otherwise as self-describing as they can be. See Real vs Clear for more about my position on that.

--00--

The suite we've built runs quickly through a range of scenarios and is notably not flaky, unlike the E2E tests against live services that we run alongside it using shared machinery for navigating the user journeys.

The speed comes from two places: first the mocks return instantly unlike the high latency on some of the external calls and, second, we can use the mocks to shorten the journeys. If the logic we want to test exists on say, step 13 of a journey, the mocked test can receive the state from step 12 as its first response, effectively skipping all other steps. This acceleration is powerful because it also makes the test logic, data, and crucially intent, much easier to comprehend.

Interestingly, or perhaps predictably and depressingly, one of the headaches around our team discussions about the gap this suite fills was naming, and the assumptions we all make when particular names for things are used. We didn't have a shared language for talking about whatever kinds of tests these are, and it took time for the vocabulary to (a) be suggested, (b) be agreed upon, and (c) be used consistently.

What we've ended up calling them is isolated tests and they sit as siblings of the E2E tests I mentioned in a hierarchy of API tests. There's still some quibbles about the appropriateness of "E2E" given that those tests don't touch the user interface or necessarily complete a user journey once the desired logic is covered. I think we've made our peace with that though.

For me, it remains to be seen whether the approach scales. The thing is readable today but there are more scenarios to add, including migrating some things covered by the E2E tests, and there will be new feature and configuration combinations to test in future.

Exhaustive enumeration of files per scenario aids readability, but there's the later tension with maintainability to consider. I am expecting that the APIs involved are sufficiently stable and future changes will be sufficiently predictable, that widespread edits to the test data will be rare and can be automated easily. A one-time cost for that against the every-time cost that hard-to-read code and data impose.

--00--

The problem I posed at the top was how to test a product with distributed logic and non-deterministic components?

If I had to summarise the approach we've iterated to it's this:

identify a place to exercise the combination from
find a way to deliver the scenarios we want to test
drive the combination to the important states
check the important features of that state

Yes, at its heart, this just the standard Arrange, Act, Assert. Despite that, I can imagine some people will object to the approach because it's deliberately not hitting live services.

I take that point, but I think I've shown that we've thought hard about what we're doing and, to be honest, the other alternatives we've tried gave us nothing of value.

Better isolate than never, you might say.
Code highlighting: pinetools

Meet Me Halfway?

The Association for Software Testing is crowd-sourcing a book, Navigating the World as a Context-Driven Tester , which aims to provide responses to common questions and statements about testing from a context-driven perspective . It's being edited by Lee Hawkins who is posing questions on Twitter , LinkedIn , Mastodon , Slack , and the AST mailing list and then collating the replies, focusing on practice over theory. I've decided to contribute by answering briefly, and without a lot of editing or crafting, by imagining that I'm speaking to someone in software development who's acting in good faith, cares about their work and mine, but doesn't have much visibility of what testing can be. Perhaps you'd like to join me? --00-- "Stop answering my questions with questions." Sure, I can do that. In return, please stop asking me questions so open to interpretation that any answ...

How do I Test AI?

Recently a few people have asked me how I test AI. I'm happy to share my experiences, but I frame the question more broadly, perhaps something like this: what kinds of things do I consider when testing systems with artificial intelligence components . I freestyled liberally the first time I answered but when the question came up again I thought I'd write a few bullets to help me remember key things. This post is the latest iteration of that list. Caveats: I'm not an expert; what you see below is a reminder of things to pick up on during conversations so it's quite minimal; it's also messy; it's absolutely not a guide or a set of best practices; each point should be applied in context; the categories are very rough; it's certainly not complete. Also note that I work with teams who really know what they're doing on the domain, tech, and medical safety fronts and some of the things listed here are things they'd typically do some or all of. Testing ...

The Best Programmer Dan Knows

I was pairing with my friend Vernon at work last week, on a tool I've been developing. He was smiling broadly as I talked him through what I'd done because we've been here before. The tool facilitates a task that's time-consuming, inefficient, error-prone, tiresome, and important to get right. Vern knows that those kinds of factors trigger me to change or build something, and that's why he was struggling not to laugh out loud. He held himself together and asked a bunch of sensible questions about the need, the desired outcome, and the approach I'd taken. Then he mentioned a talk by Daniel Terhorst-North, called The Best Programmer I Know, and said that much of it paralleled what he sees me doing. It was my turn to laugh then, because I am not a good programmer, and I thought he knew that already. What I do accept, though, is that I am focussed on the value that programs can give, and getting some of that value as early as possible. He sent me a link to the ta...

Notes on Testing Notes

Ben Dowen pinged me and others on Twitter last week , asking for "a nice concise resource to link to for a blog post - about taking good Testing notes." I didn't have one so I thought I'd write a few words on how I'm doing it at the moment for my work at Ada Health, alongside Ben. You may have read previously that I use a script to upload Markdown-based text files to Confluence . Here's the template that I start from: # Date + Title # Mission # Summary WIP! # Notes Then I fill out what I plan to do. The Mission can be as high or low level as I want it to be. Sometimes, if deeper context might be valuable I'll add a Background subsection to it. I don't fill in the Summary section until the end. It's a high-level overview of what I did, what I found, risks identified, value provided, and so on. Between the Mission and Summary I hope that a reader can see what I initially intended and what actually...

On Herding Cats

Last night I was at the Cambridge Tester meetup for a workshop on leadership. It was a two-parter with Drew Pontikis facilitating conversation about workplace scenarios followed by an AMA with a group of experienced managers. I can't come to work this week, my cat died. Drew opened by asking us what our first thoughts would be as managers on seeing that sentence. Naturally, sadness and sympathy, followed by a week ? for a cat ? and I only got a day for my gran! Then practicalities such as maybe there's company policy that covers that , and then the acknowledgement that it's contextual: perhaps this was a long-time emotional support animal . Having established that management decisions are a mixture of emotion, logic, and contingency Drew noted that most of us don't get training in management or leadership then split us into small groups and confronted us with three situations to talk through: Setting personal development goals for others. Dropping a clange...

Reasonable Doubt

In Your job is to deliver code you have proven to work Simon Willison writes: As software engineers we ... need to deliver code that works — and we need to include proof that it works as well. He is coming at this from the perspective of LLM-assisted coding, but most of what he says applies in general. I think this is a reasonable consise summary of his requirements for developers: Manual happy paths: get the system into an initial state, exercise the code, check that it has the desired effect on the state. Manual edge cases: no advice given, just a note that skill here is a sign of a senior engineer. Automated tests: should demonstrate the change like Manual happy paths but also fail if the change is reverted. He notes that, even though LLM tooling can write automated tests, it's humans who are accountable for the code and it's on us to "include evidence that it works as it should." Coincidentally, just the week before I read his post I told one of my...

Vanilla Flavour Testing

I have been pairing with a new developer colleague recently. In our last session he asked me "is this normal testing?" saying that he'd never seen anything like it anywhere else that he'd worked. We finished the task we were on and then chatted about his question for a few minutes. This is a short summary of what I said. I would describe myself as context-driven . I don't take the same approach to testing every time, except in a meta way. I try to understand the important questions, who they are important to, and what the constraints on the work are. With that knowledge I look for productive, pragmatic, ways to explore whatever we're looking at to uncover valuable information or find a way to move on. I write test notes as I work in a format that I have found to be useful to me, colleagues, and stakeholders. For me, the notes should clearly state the mission and give a tl;dr summary of the findings and I like them to be public while I'm working not just w...

Open Your Mind

Jerome Groopman, in How Doctors Think , reviews ways in which doctors can make poor choices, identifies potential causes, and suggests some practices, for both doctor and patient, that can help to prevent them. I find this interesting for a couple of reasons: first, I work in the health space, although not in a therapeutic area and, second, I like to reflect on my own thought processes. I'll take three broad themes from Groopman's analysis: the business of healthcare and how that impacts a physician's ability to practice; the doctor-patient relationship and how that impacts the experience of both sides; and the cognitive failings that impact a correct and timely diagnosis for any given patient. Naturally, these overlap. The book is written from the perspective of the notoriously commercialised American medical system and is around 20 years old, so doubtless some of the details are different outside of the US and have changed since pu...

Why Test, Test What, Then How?

There was a time when testing was all about the mnemonics . Well, we had no AI back then so thinking about our human craft and how to share what we had learned using our human intelligence with other engaged humans for later recall in their human heads seemed important. But this post isn't about dumping on AI. It isn't about mnemonics either even if WTTWTH does look like something that'd fit well into that ancient world. No, this post is just a snappier version of what I said to my team this week when I was walking through some testing I'd done the day before. It was concerned with a change to a particular turn in the dialog system we're building where multiple variables are in play, some populated by an external call to an LLM service. I wanted to make the point that the bulk of the testing work was done in the research I did and the spreadsheet I made, not in the interaction with our product. That spreadsheet was the result of me looking in our service's cod...

Hiccupps

Search This Blog