Takeaways from Elisabeth Hendrickson’s “There’s Always A Duck”

Elisabeth Hendrickson’s book “There’s Always A Duck” has been around for a number of years but I have only been able to read it recently. Now I know what she meant about ducks. They’re literally about ducks, but also about people too. People are different, and yet we share similarities. We experience things, we communicate with each other, and we learn and get better because of those experiences. Her book tells us stories of her adventures and the lessons she’s discovered along the way, and it was nice to have had a glimpse of what she saw and felt with her encounters with software project teams and everyone involved.

Some takeaways:

  • The vast majority of programmers I have met are diligent, capable folk. They truly care about the quality of their work and want the software they produce to be useful. They work hard to make sure they are implementing the right features and writing solid code.
  • The next time you’re tempted to think of your programmers as idiots, incompetents, or quality hostile, remember that no matter what else they may be, they’re people first. Even if it seems like they’re hostile or incapable, it is far more likely that they are having a very human reaction to a particularly bad situation.
  • And before you blame someone else for a mistake, remember the last time you made one. I’ve made some real whopper mistakes in my time. We all have, whether or not we choose to admit them or even remember them. It may be that some programmers don’t care about users, but it’s more likely that bugs are honest mistakes made under difficult circumstances.
  • Even when we are speaking the same language and about the same thing, it’s hard enough to communicate.
  • The point wasn’t to catch every possible error. What seems to go wrong most often? What errors are difficult to see at first glance, and thus require concentration to prevent? What causes the most damage when it happens?
  • Janet doesn’t know anything about the ins and outs of creating software. She probably doesn’t want to know. She just wants to serve her customers well. And this software is not helping. Back at corporate, the Steering Committee, Requirements Analysts, Designers, Programmers and Testers are congratulating themselves on a solid release. What they don’t see is Janet’s pain. The feedback loop is broken. The team back at corporate has no mechanism to find out whether the software is any good. Oh, sure, they’ll detect catastrophic problems that cause servers to go down. But they won’t see the little things that cause long queues at the front desk of the hotel.
  • Testers naturally notice details. Not only do we notice, but we think about what we noticed, we attempt to interpret our observations to explain why things might be that way, we ask others if they noticed, we question our assumptions, and we poke and prod at things to see if our understanding is correct. We use our observations to inform us, and in doing so discover underlying causes and effects we otherwise might miss.
  • I sometimes fall into the trap of thinking that the first problem I see must be THE problem that needs to be solved. Perhaps the problem I spotted is indeed worth correcting, but I almost never manage to spot the true critical issue at first glance.
  • Both fear and excitement stem not from observable reality but rather from speculation. We are speculating that the bugs that we know about and have chosen not to fix are actually as unimportant to our users as they are to us. We are speculating that the fact we have not found any serious defects is because they don’t exist and not because we simply stopped looking. We are speculating that we knew what the users actually wanted in the first place. We are speculating that the tests we decided not to run wouldn’t have found anything interesting. We are speculating that the tests we did run told us something useful. None of it is real until it is in the hands of actual users. The experience those users report is reality. Everything else is speculation.
  • It’s not because Agile is about going faster. It’s because structuring our work so that we can ship a smaller set of capabilities sooner means that we can collapse that probability wave more often. We can avoid living in the land of speculation, fooling ourselves into thinking that the release is alive (or dead) based on belief rather than fact. In short, frequent delivery means we live in reality, not probability.
  • Hire the right people. If that means keeping a critical position on the team open longer than anticipated, so be it. It’s better to have an under- staffed team of highly motivated, talented, skilled people than a fully staffed but ineffective team. Remember that hiring mistakes often take only a few minutes to make, and months of wasted time to undo.
  • Listen. There are always signs when a project is in trouble: missed milestones, recurrent attitude problems, general confusion about the project. Sometimes these signs indicate a dysfunctional team, sometimes they’re just normal bumps along the road, and sometimes they are early warning signs of major problems. The only way to tell the difference is to listen carefully to what the team members have to say.
  • The best way to get people to accept change is to make it more fun, and more rewarding, to do things the new way.
  • Choose a path that takes you in the direction you want to go. Don’t choose a path simply because it takes you away from the swamp you want to avoid.

Allow People To Do What They Think Is Best

To find out that the programmers in the team are seeking out product owners, stakeholders, and teammates on their own to ask clarifications and start meaningful discussions is a positive thing for me, to notice them initiate communication to whomever they need to talk to is always a major confidence booster about their ability to work on problems on their own. They never need my authority or permission to do what they think is best, they manage their own tasks, they own the responsibility to do the right thing as they see fit. I’m just there to help them perform the best work they can, in the form of suggestions and testing.

That’s why it’s bewildering to see someone get disappointed over a behavior that I deem to be on the plus side. Why would letting developers talk directly to stakeholders make you feel overstepped, if they think it supports better work? It seems to be, at least for me, a shallow use of a leadership position, a certain level of being clingy to power that’s not serving the team mission. It’s an upsetting, controlling reaction that I feel does not do any good.

Focus on empowering the team.

Team Questions I

What  does our team actually want to accomplish this particular sprint?

Do I know my teammates well enough?

Does everyone in the team feel safe working together with each other?

Can I rely on everybody in the team?

What does a user story mean to us?

Do we even need tickets in order to perform our best work?

Do we truly need this specific document to move forward?

How can I help a teammate feel good with the work he/she is doing?

What’s the minimum amount of input do we need in order to start?

What’s the 20% of activities that contribute to 80% of outputs we desire?

Do we believe in what we are building?

Which rules, in reality, help us become the best versions of ourselves? Which don’t?

Pitching a Small Tool

Last week I told our technical writer, a music expert, a video games enthusiast, a good father to his young daughter, and a loving husband to his wife, that I could build him a small tool that could quickly update a master file of local translations, so he could focus his precious time on more important matters other than the job of laboriously cross-referencing and manually updating such a document. That was a passing comment while some of us were suddenly randomly discussing the process of how he was currently maintaining the file. However, the passing comment also felt like a pitch to a software development project that had some sort of value to a very specific customer, and an easy one at that. It was a fascinating experience; it makes you think about how caring for the well-being of someone is very much a part of building software of value, and that good software connects people for the better.

Let’s see how that tool works out this week.

An Experiment on Executable Specifications

What: Create executable specifications for an ongoing project sprint. Executable specifications are written examples of a business need that can be run anytime and acts as a source of truth for how applications behave. It is a living documentation of what our software does, and it helps us focus more on solving the unusual and noteworthy problems instead of wasting time with the ones that we know we shouldn’t have been worrying about.

How:

  1. Join a software development team for one sprint duration.
  2. Discuss project tasks for that sprint with everyone.
  3. Ask about requirements examples and create executable specifications for those tasks as the application is being written.
  4. Refine the specifications when necessary.
  5. Continuously update the specifications until they pass.
  6. Keep the specifications running on a preferred schedule.

Why: To see if writing executable specifications alongside development is feasible during the duration of a sprint.

Limitations: Tester writes the executable specifications, programmers work as is.

Experiment Realizations:

  • Writing executable specifications can be done during actual app development, provided that tester is experienced with the tools for implementing it and understands well why the need for such specifications.
  • It is of course more beneficial if everyone in the team learn how executable specifications work and write/run the specifications, and why the need to implement it.
  • It will take quite a long while before executable specifications becomes a norm in the existing software development process, if ever. This is a function of whether everyone believes that such specifications are actually useful in practice, and then building the skills and habit of including these specifications in the team’s definition of done.

Lessons from Gojko Adzic’s “Specification By Example”

Automated checking is not a new concept. Gojko Adzic, however, provides us a way to make better integration of it in our software development processes. In his book titled “Specification by Example”, he talks about executable specifications that double as a living documentation. These are examples which continuously exercise business rules, they help teams collaborate, and, along with software code, they’re supposed to be the source of truth for understanding how our applications work. He builds a strong case about the benefits of writing specifications by example by presenting case studies and testimonials of teams who have actually used it in their projects, and I think that it is a great way of moving forward, of baking quality in.

Some favorite takeaways from the book:

  • Tests are specifications; specifications are tests.
  • “If I cannot have the documentation in an automated fashion, I don’t trust it. It’s not exercised.” -Tim Andersen
  • Beginners think that there is no documentation in agile, which is not true. It’s about choosing the types of documentation that are useful. There is still documentation in an agile process, and that’s not a two-feet-high pile of paper, but something lighter, bound to the real code. When you ask, “does your system have this feature?” you don’t have a Word document that claims that something is done; you have something executable that proves that the system really does what you want. That’s real documentation.
  • Fred Brooks quote: In The Mythical Man-Month 4 he wrote, “The hardest single part of building a software system is deciding precisely what to build.” Albert Einstein himself said that “the formulation of a problem is often more essential than its solution.”
  • We don’t really want to bother with estimating stories. If you start estimating stories, with Fibonacci numbers for example, you soon realize that anything eight or higher is too big to deliver in an iteration, so we’ll make it one, two, three, and five. Then you go to the next level and say five is really big. Now that everything is one, two, and three, they’re now really the same thing. We can just break that down into stories of that size and forget about that part of estimating, and then just measure the cycle time to when it is actually delivered.
  • Sometimes people still struggle with explaining what the value of a given feature would be (even when asking them for an example). As a further step, I ask them to give an example and say what they would need to do differently (work around) if the system would not provide this feature. Usually this helps them then to express the value of a given feature.
  • QA doesn’t write [acceptance] tests for developers; they work together. The QA person owns the specification, which is expressed through the test plan, and continues to own that until we ship the feature. Developers write the feature files [specifications] with the QA involved to advise what should be covered. QA finds the holes in the feature files, points out things that are not covered, and also produces test scripts for manual testing.
  • If we don’t have enough information to design good test cases, we definitely don’t have enough information to build the system.
  • Postponing automation is just a local optimization. You might get through the stories quicker from the initial development perspective, but they’ll come back for fixing down the road. David Evans often illustrates this with an analogy of a city bus: A bus can go a lot faster if it doesn’t have to stop to pick up passengers, but it isn’t really doing its job then.
  • Workflow and session rules can often be checked only against the user interface layer. But that doesn’t mean that the only option to automate those checks is to launch a browser. Instead of automating the specifications through a browser, several teams developing web applications saved a lot of time and effort going right below the skin of the application—to the HTTP layer.
  • Automating executable specifications forces developers to experience what it’s like to use their own system, because they have to use the interfaces designed for clients. If executable specifications are hard to automate, this means that the client APIs aren’t easy to use, which means it’s time to start simplifying the APIs.
  • Automation itself isn’t a goal. It’s a tool to exercise the business processes.
  • Effective delivery with short iterations or in constant flow requires removing as many expected obstacles as possible so that unexpected issues can be addressed. Adam Geras puts this more eloquently: “Quality is about being prepared for the usual so you have time to tackle the unusual.” Living documentation simply makes common problems go away.
  • Find the most annoying thing and fix it, then something else will pop up, and after that something else will pop up. Eventually, if you keep doing this, you will create a stable system that will be really useful.

Contemplating In-Office Knowledge-Sharing Sessions

In the past I tend to prepare presentation slides if I want to share something to tester colleagues at work, often clippings of interesting articles which I felt could be useful for our knowledge-sharing sessions. It worked, but after some time the sessions felt monotonous and tedious. Probably because I always have to explain in detail the ideas and the lessons behind those clippings. I try to make my presentations interesting, but I think that after a while hearing the same voice over and over can get old.

These days I’m sharing videos instead. The videos are usually recorded conference talks or tutorials I have watched and learned from in recent years, and I have taken care in listing the the ones that are insightful, fun, and relatively short. It’s like I’m inviting officemates to watch a short movie for free. The big change: I don’t take a lot of time talking during the knowledge-sharing anymore. There are of course still bits of discussions before, after, or during the showing of a video, whenever necessary, for explaining why I have taken a liking to the talk or to ask them about what they understood. We take turns telling stories about our experiences related to the ideas shared by the speaker, which is nice. And compared to the powerpoint presentations I did before, I felt that because the speaker is someone from outside it makes the ideas shared in the talks and tutorials feel more fresh and real than when I’m merely showing them quoted paragraphs from blogs. That makes it easier for my colleagues to get curious and actually learn something, which is exactly the point of the activity.