How did you find that bug? Are we sitting comfortably, then I'll begin.

How did you find that bug? - They asked with a sort of puzzled "he dun't thunk like uz" look on their faces. An expression that suggested they were unsure whether to commend the discovery or gather their pitchforks and organise a well overdue witch burning.

Likewise, I now knew why they needed me. The team members were genuinely hard working people trying to build something new and exciting. But they lacked one thing, someone exploring & asking questions - trying to find out new things about their application. Exploring is literally a step into the unknown, and that can be uncomfortable for those not experienced in how to do it well.

Exploring is literally a step into the unknown.

So how did I find that bug? It's easy to tell a story of how I tried that particular input value because... Paragraph 3 of v4.6 of the requirements document stated that the user shall indeed on occasion X given input Y in Chrome v62 do... Or spout some other overly verbose explanation of why that broken 'scenario' came to be valid.

But I wouldn't be answering their question, and I wouldn't be telling the truth. The truth of how I (and other testers) do this is harder to remember. But having a better idea of how you got there is going to help you get there again.

Let's take a trivial example. A few years ago, working on a new editorial system for a financial news organisation: I discovered that entering a double quote character into the content search feature caused it to crash. Even worse it returned no results (But it didn't fail to provide the users with a nasty technical error message). This had not been noticed before, yet many tests had been written and run. They had more acceptance tests than they could run in a night.

I had not examined requirements documentation for that feature. I had not perused the Acceptance Criteria for the Search feature. I had not reviewed the unreliable test automation. What I did was speak to the team and then type some quoted text into the search form. I had thought that the search should behave like Google, whereby if you include text in quotes - it will search for an exact match to that string of characters. I was interested to see what happened.

I did not know whether the search should support this sort of exact phrase matching. But I was exploring. I knew 'searches' [in my experience] worked like this - so I decided to check if this one did. This was the first step in a series of related tests that allowed me and my colleagues to uncover many more issues with the search feature.

When a team is focused on short-term delivery goals they can lose sight of the features not listed right in front of them. You need someone to question, someone to explore someone to point out that crashing when an editor uses a quote is sub-optimal. That's what I do at Investigating Software.

Comments

Don't be a Vogon, make it easy to access your test data!

The beginning of the hitch-hikers guide to the galaxy leads with an alien ship about to destroy the Earth, and the aliens saying we (mankind) should have been more prepared – as a notice had been on display quite clearly – on Alpha Centauri the nearby star system, for 50 years. Seriously, people - what are you moaning about – get with the program? The book then continues with the theme of bureaucratic rigidity and shallow interpretations of limited data. E.g. The titular guide’s description of the entire Earth is one word: “Harmless”, but after extensive review the new edition will state: “Mostly harmless”. Arthur Dent argues with the Vogons about poor data access This rings true for many software testing work, especially those with externally developed software, be that external to the team or external to the company. The same approaches that teams use to develop their locally developed usually don’t work well. This leads to a large suite of shallow tests that are usually h...

Can 'reasoning' LLMs help with recs data creation?

A nervous tourist, glances back and forth between their phone and the street sign. They then rotate their phone 180 degrees, pauses, blink and frown. The lost traveller, flags a nearby ‘local’ (the passer-by has a dog on a lead. “Excuse me…” she squeaks, “How may I get to Tower Hill?” “Well, that’ s a good one” ponders the dog walker, “You know…” “Yes?” queries the tourist hopefully. “Yeah…” A long pause ensues then, “Well I wouldn’t start from here” He states confidently. The tourist almost visibly deflates and starts looking for an exit. That’s often how we start off in software testing. Despite the flood of methodologies, tips on pairing, power of three-ing, backlog grooming, automating, refining and all the other … ings ) We often find ourselves having to figure out and therefore ‘test’ a piece of software by us ing it. And that’s good. Its powerful, and effective if done right. But, like our dog walker, we can sometimes find ourselves somewhere unfamiliar...

What possible use could Gen AI be to me? (Part 1)

There’s a great scene in the Simpsons where the Monorail salesman comes to town and everyone (except Lisa of course) is quickly entranced by Monorail fever… He has an answer for every question and guess what? The Monorail will solve all the problems… somehow. The hype around Generative AI can seem a bit like that, and like Monorail-guy the sales-guy’s assure you Gen AI will solve all your problems - but can be pretty vague on the “how” part of the answer. So I’m going to provide a few short guides into how Generative (& other forms of AI) Artificial Intelligence can help you and your team. I’ll pitch the technical level differently for each one, and we’ll start with something fairly not technical: Custom Chatbots. ChatBots these days have evolved from the crude web sales tools of ten years ago, designed to hoover up leads for the sales team. They can now provide informative answers to questions based on documents or websites. If we take the most famous: Chat GPT 4. If we ignore the...

investigating software

Search This Blog