The User Inexperience

I think a lot about the user experience when I'm testing. Not only for conformance with the UX guide we refer to but also in less tangible, subjective, respects such as how the software will feel to different kinds of users.

The UX guide can't help here. Although it has value and the potential to save time - for example, by reducing the number of discussions about capitalisation policy for dialog title bars to merely single figures per release - at close to 900 pages it is not a shining example of usability itself and it doesn't try to answer the question who's a user? In particular, it has only a handful of mentions of new users outside of the section on first-timers which itself is largely about setting up the product rather than using it.

Inexperienced users will at various points form a significant enough proportion of your userbase that they merit special attention and when that happens, you'll need to think about lack of experience with your product, this class of product, this complexity of product, this domain, computers in general and so on.

You'll make your assumptions about which and how to model them when you need to, taking into account your situation and software. Perhaps you're working out from early adopters and your target user will still be quite tech savvy and accommodating. Or maybe you're moving to an adjacent market and it's the domain details that'll change. Or perhaps you're working on a mass-market killer app where an unpleasurable or complex user experience could be the app's killer and so you'll be thinking about those little old ladies, busy parents, children and senior management.

It may be tempting, but don't just focus on workflow, on greasing the path from input to result, because, while this is often advantageous, your newbies may not even know what the workflow is yet. Maintain visibility of the whole product, including documentation, and look at the kinds of heuristics that can be employed when considering the product aside from stated requirements. Get your newest employees to try the software without training and, especially, think about feedback and whether users will understand what they've achieved, how, and how to change it to what they really wanted. Remember: if users can't get that, inexperienced or not, they'll certainly know enough to go somewhere else.
Image: http://flic.kr/p/4NkPkQ

Modal-Driven Development

If extracting feature motivations, requirements and priorities from stakeholders is an art, presenting the analysis requires artfulness. The MoSCoW method suggests using English words Must, Should, Could and Won't as an alternative to purely numeric priorities to make it more transparent that not everything listed will be delivered.

But reversing the MoSCoW rules can help to obtain the implicit prioritisations. You'll frequently hear "we must have a solution to X" or "Y should be improved in this release" or "we'd like to get Z into the payload if we could". Key verbs like this can be mapped to prioritisations, e.g. P1 (must), P2 (should), P3 (could). We use these clues to bootstrap priority discussions and, perhaps surprisingly, I often apply it to my own bug reports to get an idea of my intuition on an issue.

You ought to beware that there will not be a 1:1 mapping between key word and priority, and negation does not help. For example, "could not" might be "must" but can be "could":

"I'm sorry but we could not do A, the customer would scream." 

"We're currently doing A, B and C; but we could not do A."

And "must", "should" and "could" may have epistemic and deontic readings that context mightn't disambiguate. Take this, from a bug ticket I read this week:

 "In Release A the behaviour should be more robust but in Release B we have to fix the issue." 

How can "should" be read? Could the reporter be saying that he thinks Release A is already more robust, or might he think that we still have to make Release A more robust? (He meant the former; our triage prioritised on the latter.)

So, now you've read this, could your requirements analysis be improved?
Image: FreeDigitalPhotos.net

Can The Modeller Control The View?

One of the reasons that software testing is challenging, both intellectually and practically, is that the information about the state of the system under test is partial. It's part of the testing role to formulate a model (or, more usually, a cloud of overlapping, incomplete and contradictory models) that represent our best view of the system at any given time and we've developed a collection of monochrome boxes that reflect the idea that access to source code can help make sense of it. But even that doesn't equate to an understanding of the model that the software has when it operates. For example:

• The tester may not follow the source code (completely).
• External libraries may implement a substantial part of the functionality but appear minimally in the source.
• Interactions with other layers, such as the operating system for file operations, will form part of the model without being part of the codebase.
• If the source code is compiled, it may be optimised in ways that contradict the tester's understanding.

And the tester isn't the only person without a clear idea of the system's take on the world. Some end users would find value in understanding the software states and how they are transitioned. Even developers would welcome a way to see the bigger picture easily when they're in code they don't modify often.

An aside. A few weeks ago, during heavy rain, I heard a rapid and repetitive thudding on our flat kitchen roof. I assumed was a drip and when the rain had stopped I got up and had a look. There were two obvious candidates: a join in the guttering between us and next door and a TV aerial pointing slightly below the horizontal. The weather was dry but I know about soak testing, so I poured a bucket of water over the aerial and another into the guttering which prompted water droplets forming on the joint and falling in a rhythmic way.

I'm no guttering expert (although as a student I once got mistaken for a tramp; that's a different kind of gutter)  but I could see that a clip on a plastic band that applied pressure to the two pipes had cracked, opening up the seal. I squirted some sealant into the joint and forced the clip shut.

It broke.

After cursing for a while, I drilled through the band and the guttering, put a bolt through the hole and tightened a nut onto it. Pouring more water in showed no leak so I put some grease on the nut and bolt to waterproof them for the future me revisting the cheap and cheerful repair and made myself a nice cup of tea.

And the point of this DIY yarn? While I was on the roof it occurred to me that my model of the system I was testing and working with was very close to being the system itself. I can touch or visualise the entire thing easily. Sure, there are levels beyond my comprehension - I don't understand the chemical or physical properties of the materials used to manufacture the guttering, the nut and bolt or the clip but I have general experience of plastics, metals and so on that covers enough of that to give me what I need.

Even considering the wider systems in which this is a small component, I could initially see that there were multiple candidates for the source of the drip and latterly recognise that when it gets wet the bolt might rust which would make further maintenance more difficult.

That's not to suggest that all software can be reduced to the complexity of a joint between two half-pipes or that all physical things can be analysed simply by looking and interacting - I wouldn't have a chance with the engine in my car, for example. But, it is the case that the more of the underlying thing that can be inspected, the less effort is required to create the initial models and the more time can be spent on refining and testing them.

So I'm going to be giving myself some time to think what we can do to make the model the software I'm testing has of its state - or, more realistically, the sub-models it has of the bits of state of interest at any given time - more available and useful to the testers and other users.

For the record, I noted down my initial thoughts while I was writing this:

• when reporting derived metrics the raw data should be available too,
• logging should be as complete as possible or (to some sensible level) complete logging should be available,
• log time stamps from different components should be in step,
• error and warning messages should be precise, clear and informative,
• similar operations on the model should be similar operations in the view,
• similar structures (semantically and/or physically) should have similar realisations in the product,
• naming conventions should be consistent and transparent from the UI through the variables in the code to the model itself,
• any extra reporting must be trustworthy, and the trust should be economic to establish, or else we'll have an additional test burden.

These seem to be concerned with consistency and testability. Where else should I be looking?
Image: http://flic.kr/p/bpTUr