Tag Archives: design

Pitfall of Scrum: Excessive Preparation/Planning

Regular big up-front planning is not necessary with Scrum. Instead, a team can just get started and use constant feedback in the Sprint Review to adjust it’s plans. Even the Product Backlog can be created after the first Sprint has started. All that is really necessary to get started is a Scrum Team, a product vision, and a decision on Sprint length. In this extreme case, the Scrum Team itself would decide what to build in its first Sprint and use the time of the Sprint to also prepare some initial Product Backlog Items. Then, the first Sprint Review would allow stakeholders to provide feedback and further develop the Product Backlog. The empirical nature of Scrum could even allow the Product Owner to emerge from the business stakeholders, rather than being assigned to the team right from the start.

Starting a Sprint without a Product Backlog is not easy, but it can be done. The team has to know at least a little about the business, and there should be some (possibly informal) project or product charter that they are aware of. The team uses this super basic information and decides on their own what to build in their first Sprint. Again, the focus should be on getting something that can be demoed (and potentially shippable). The team is likely to build some good stuff and some things that are completely wrong… but the point is to get the Inspect and Adapt cycle started as quickly as possible. Which means of course that they need to have stakeholders (customers, users) actually attend the demo at the end of the Sprint. The Product Owner may or may not even be involved in this first Sprint.

One important reason this is sometimes a good approach is the culture of “analysis paralysis” that exists in some organizations. In this situation, an organization is unable to do anything because they are so concerned about getting things right. Scrum is a framework for inspect and adapt and that can (and does) include the Product Backlog. Is it better for a team to sit idle while someone tries to do sufficient preparation? Or is it better to get started and inspect and adapt? This is actually a philosophical question (as well as a practical question). The mindset and philosophy of the Agile Manifesto and Scrum is that trying to produce valuable software is more important that documentation… that individuals and how they work together is more important than rigidly following a process or tool. I will agree that in many cases it is acceptable to do some up-front work, but it should be minimized, particularly when it is preventing people from starting to deliver value. The case of a team getting started without a product backlog is rare… but it can be a great way for a team to help an organization overcome analysis paralysis.

The Agile Manifesto is very clear: “The BEST architectures, requirements and designs emerge out of self-organizing teams.” [Emphasis added.]

Hugely memorable for me is the story that Ken Schwaber told in the CSM course that I took from him in 2003.  This is a paraphrase of that story:

I [Ken Schwaber] was talking to the CIO of a large IT organization.  The CIO told me that his projects last twelve to eighteen months and at the end, he doesn’t get what he needs.  I told him, “Scrum can give you what you don’t need in a month.”

I experienced this myself in a profound way just a couple years into my career as an Agile coach and trainer.  I was working with a department of a large technology organization.  They had over one hundred people who had been working on Agile pilot projects.  The department was responsible for a major product and executive management had approved a complete re-write.  The product managers and Product Owners had done a lot of work to prepare a product backlog (about 400 items!) that represented all the existing functionality of the product that needed to be re-written.  But, the big question, “what new technology platform do we use for the re-write?” had not yet been resolved.  The small team of architects were tasked with making this decision.  But they got stuck.  They got stuck for three months.  Finally, the director of the department, who had learned to trust my advice in other circumstances, asked me, “does Scrum have any techniques for making these kind of architectural decisions?”

I said, “yes, but you probably won’t like what Scrum recommends!”

She said, “actually, we’re pretty desperate.  I’ve got over a hundred people effectively sitting idle for the last three months.  What does Scrum recommend?”

“Just start.  Let the teams figure out the platform as they try to implement functionality.”

She thought for a few seconds.  Finally she said, “okay.  Come by this Monday and help me launch our first Sprint.”

The amazing thing was that the teams didn’t lynch me when on Monday she announced that “our Agile consultant says we don’t need to know our platform in order to get started.”

The first Sprint (two weeks long) was pretty chaotic.  But, with some coaching and active support of management, they actually delivered a working increment of their product.  And decided on the platform to use for the rest of the two-year project.

You must trust your team.

If your organization is spending more than a few days preparing for the start of a project, it is probably suffering from this pitfall.  This is the source of great waste and lost opportunity.  Use Scrum to rapidly converge on the correct solutions to your business problems instead of wasting person-years of time on analysis and planning.  We can help with training and coaching to give you the tools to start fast using Scrum and to fix your Scrum implementation.

This article is a follow-up article to the 24 Common Scrum Pitfalls written back in 2011.

[UPDATE: 2015/08/19] I’ve just added a video to the “Myths of Scrum” YouTube series that adds a bit to this:


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Design Debt & UX Debt is Technical Debt

Hey! Let’s all work together, please.

Technical Debt is a term which captures sloppy code, unmaintainable architecture, clumsy user experience, cluttered visual layout, bloated feature-sets, etc.  My stance is that the term, Technical Debt, includes all the problems which occur when people defer professional discipline — regarding any/every technical practice such as product management, visual and UX design, or code.

I assert that the change we need to catalyze in the business community is larger than any one discipline and I am worried that I have seen an increase in blog articles in recent years about concepts like “Design Debt”, “UX Debt”, “Experience Debt” — these articles unfortunately are not helping and have served only to divide the community. They are divisive, not because we shouldn’t be discussing the discreet facets in which Technical Debt can manifest, but because authors often take a decidedly combative approach in their writing.  Take these phrases for example:

  • “Product Design Debt Versus Technical Debt” written by Andrew Chen
  • “User Experience Debt: Technical debt is only half the battle” written by Clinton Christian
  • “Design debt is more dangerous because…” written by James Engwall.

I agree with Andrew Chen that Product Design Debt is a problem — I just don’t like that he chose to impose a dichotomy where there is none.  Why must he argue one “versus” another?  Clinton Christian has implied that we’re in a “battle”.  James Engwall has compared the “danger” of Design Debt relative to Technical Debt.  These words are damaging, I argue, because they divert attention to symptoms and away from root causes.

The root cause of Technical Debt is that people forget this simple principle of the Agile Manifesto: “Continuous attention to technical excellence and good design enhances agility.”

The root solution to Technical Debt — all of its forms — is to help business leaders realize there is a difference between “incremental” development and “iterative” development so they may understand the ROI of refactoring.  No technical expert should ever have to justify the business case for feature-pruning, refreshing a user interface, refactoring code, prioritizing defects.  Every business leader should trust that their technical staff are disciplined and excellent.

Yes, please blog about UX Debt and Product Development Debt, etc.  But please do so in a way that encourages cohesion and unity within the Product Development community.


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Evolution of a Scrum Diagram

Over the many years that I have been teaching Scrum (since 2005!), I have had a Scrum diagram as part of my slides and/or handouts.  The diagram has gone through several major and minor changes throughout that time.  Here is the progression from oldest to newest:

First Attempt

This diagram was used in some of my earliest slides when I first started delivering Scrum training.  It is bad.  It is woefully incomplete.  But, here it is:

01 Scrum Process Diagram

Second Diagram

I knew the first one was bad so after not too long, I created this next diagram as a supplement that was meant to show the whole Scrum process all in one page. Similar to other Scrum “cheat sheet” style diagrams. I used this diagram until about 2008 when I got some very good feedback from a great trainer, Jim Heidema.

02 All of Scrum Diagram

Third Try

The changes I made were small, but to me, significant.  Changing from a “mathematical” language of “Sprint N”, “Sprint N+1” to a more general language of “Current”, “Future” was a big deal.  I really struggled with that.  Probably because I was still relatively new to being non-technical.

03 All of Scrum Diagram

Diagram Four

This fourth diagram made some minor formatting changes, but most importantly added “Backlog Grooming”.  It’s funny how long I talked about grooming in my classes before realizing that it was missing from the diagram.  I used the previous diagram and this diagram for a couple years each before making a rather major change to create the next one.

04 All of Scrum Diagram

Fifth Go

A couple years ago I realized that I wasn’t really talking about the Scrum values in my classes.  I started to introduce them in some of my other handouts and discussions, but it still took a while for me to reflect those values in my diagram.  I had also received a lot of feedback that having two Product Backlogs in the diagram was confusing.  Finally, I realized that I was missing an opportunity to use colour more systematically.  So, a major reformatting, systematic colour coding and the addition of the Scrum values was my next change.

05 All of Scrum Diagram

Branded Diagram (ug.)

In a rush, I added some logos to the diagram. Just made it gross, but it’s badness, combined with feedback about said badness, actually inspired a major change for the next version.

05 All of Scrum Diagram - Branded

Seventh Diagram (Sep. 2014)

I was showing my brand-new branded diagram to a bunch of people who really care about design and UX.  The very first comment when I handed out the diagram was: “wow, you can really tell this wasn’t done by a designer!”  Well, that got me thinking deeply about the diagram (again).  So, here is my newest, latest and greatest (still not done by a designer) version of my Scrum diagram!

06 The Scrum Process

Eighth Diagram (2016-ish)

This new diagram represents many small changes including a much stronger focus on Scrum “by-the-book”.  The most important and significant change is the addition of a bit of information about the definition of done.  It also includes some other very minor layout and content changes, and updated branding (again) with the new BERTEIG logo.  This one has been in use since some time in 2016, but I don’t remember the exact date.

All of Scrum Diagram

Ninth Diagram (June 2019)

A re-branding of the diagram with color and iconography meant to be consistent with our other diagrams.  The work on converting from the previous diagram to this one was done by my son, Justice Berteig.

All of Scrum Diagram June 2019

Tenth Diagram (Sep 2019)

There were quite a few things that were missing from the previous diagram and a small number of things lingering that still were not compliant with the definition of Scrum from the Scrum Guide.  I think this one has all the needed changes.  Big additions include the “Development Team”, “Transparency, Inspection and Adaptation”, “Product Vision” and “Marketplace”.

All of Scrum Diagram - September 2019

The Future

I would absolutely love constructive feedback about this latest diagram. Of course, if you like it, please let me know that too! The thing I like about this is that it is a way of looking back at almost 9 years of my teaching history. Continuous improvement is so important, so I welcome your comments! If you have your own diagrams, please link to them in the comments – I would love to see those too! In fact, it would be really cool if a bunch of people could make little “Evolution of a Scrum Diagram” posts – let me know if you do!!!

PS.  Here is a Scrum diagram created by my colleague Travis Birch.


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Great Article about TDD by J. B. Rainsberger

I just finished reading “Test-Driven Development as Pragmatic Deliberate Practice“.  Fantastic article.  I highly recommend it to anyone who is actively coding.  It strongly reflects my understanding of TDD as a fundamental technique in any Software Development Professional’s toolkit.


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ANN: Agile Software Engineering Practices training by Isráfíl Consulting

Isráfíl Consulting is finally prepared for the first series of its Agile Software Engineering Practices training courses. This series is offered in partnership with Berteig Consulting who are graciously hosting the registration process. Their team has also helped greatly in shaping the presentation style and structure of the course. The initial run will be in Ottawa, Toronto (Markham), and Kitchener/Waterloo.   

Topics covered will include Test Driven Development (TDD), testability, supportive infrastructure such as build and continuous integration, team metrics, incremental design and evolutionary architecture, dependency injection, and so much more. (This course won’t present the planning side of XP, but covers many other aspects common to XP projects) It makes a great complement for training in Agile Processes such as XP, Scrum, or OpenAgile. The overview slide presentation is available for free download from the Isráfíl web site.

The courses are scheduled for:

The course is $1250 CAD per student, and participants receive a transferrable discount of $100 CAD for other training with Berteig Consulting as a part of our ongoing partnership. I initially prototyped this course in Ottawa this December, and am very excited to see this through in several locales. Class size is limited to 15, so we can keep the instruction style more involved. The above schedules are linked to Berteig Consulting’s course system and have registration links at the bottom of the description. Locations are TBD, but will be updated at the above links as soon as they’re finalized.

A further series is planned for several US cities in March, and we’ll be sure to announce them as well.


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Yet another misunderstanding of TDD, testing, and code coverage

I was vaguely annoyed to see this blog article featured in JavaLobby’s recent mailout. Not because Kevin Pang doesn’t make some good points about the limits of code coverage, but because his title is needlessly controversial. And, because JavaLobby is engaging in some agile-baiting by publishing it without some editorial restraint.

In asking the question, “Is code coverage all that useful,” he asserts at the beginning of his article that Test Driven Development (TDD) proponents “often tend to push code coverage as a useful metric for gauging how well tested an application is.” This statement is true, but the remainder of the blog post takes apart code coverage as a valid “one true metric,” a claim that TDD proponents don’t make, except in Kevin’s interpretation.

He further asserts that “100% code coverage has long been the ultimate goal of testing fanatics.” This isn’t true. High code coverage is a desired attribute of a well tested system, but the goal is to have a fully and sufficiently tested system. Code coverage is indicative, but not proof, of a well-tested system. How do I mean that? Any system whose authors have taken the time to sufficiently test it such that it gets > 95% code coverage is likely (in my experience) thinking through how to test their system in order to fully express its happy paths, edge cases, etc. However, the code coverage here is a symptom, not a cause, of a well-tested system. And the metric can be gamed. Actually, when imposed as a management quality criterion, it usually is gamed. Good metrics should confirm a result obtained by other means, or provide leading indicators. Few numeric measurements are subtle enough to really drive system development.

Having said that, I have used code-coverage in this way, but in context, as I’ll mention later in this post.

Kevin provides example code similar to the following:

String foo(boolean condition) {
    if (condition)
        return "true";
    else
        return "false";
}

… and talks about how if the unit tests are only testing the true path, then this is only working on 50% coverage. Good so far. But then he goes on to express that “code coverage only tells us what was executed by our unit tests, not what executed correctly.” He is carefully telling us that a unit test executing a line doesn’t guarantee that the line is working as intended. Um… that’s obvious. And if the tests didn’t pass correctly, then the line should not be considered covered. It seems there are some unclear assumptions on how testing needs to work, so let me get some assertions out of the way…

  1. Code coverage is only meaningful in the context of well-written tests. It doesn’t save you from crappy tests.
  2. Code coverage should only be measured on a line/branch if the covering tests are passing.
  3. Code coverage suggests insufficiency, but doesn’t guarantee sufficiency.
  4. Test-driven code will likely have the symptom of nearly perfect coverage.
  5. Test-driven code will be sufficiently tested, because the author wrote all the tests that form, in full, the requirements/spec of that code.
  6. Perfectly covered code will not necessarily be sufficiently tested.

What I’m driving at is that Kevin is arguing against something entirely different than that which TDD proponents argue. He’s arguing against a common misunderstanding of how TDD works. On point 1 he and I are in agreement. Many of his commentators mention #3 (and he states it in various ways himself). His description of what code coverage doesn’t give you is absurd when you take #2 into account (we assume that a line of covered code is only covered if the covering test is passing). But most importantly – “TDD proponents” would, in my experience, find this whole line of explanation rather irrelevant, as it is an argument against code-coverage as a single metric for code quality, and they would attempt to achieve code quality through thoroughness of testing by driving the development through tests. TDD is a design methodology, not a testing methodology. You just get tests as side-effect artifacts of the approach. Useful in their own right? Sure, but it’s only sort of the point. It isn’t just writing the tests-first.

In other words – TDD implies high or perfect coverage. But the inverse is not necessarily true.

How do you achieve thoroughness by driving your development with tests? You imagine the functionality you need next (your next increment of useful change), and you write or modify your tests to “require” the new piece of functionality. They you write it, then you go green. Code coverage doesn’t enter into it, because you should have near perfect coverage at all times by implication, because every new piece of functionality you develop is preceded by tests which test its main paths and error states, upper and lower bounds, etc. Code coverage in this model is a great way to notice that you screwed up and missed something, but nothing else.

So, is code-coverage useful? Heck yeah! I’ve used coverage to discover lots of waste in my system. I’ve removed whole sets of APIs that were “just in case I need them” APIs, because they become rote (lots of accessors/mutators that are not called in normal operations). Is code coverage the only way I would find them? No. If I’m dealing with a system that wasn’t driven with tests, or was poorly tested in general, I may use coverage as a quick health meter, but probably not. Going from zero to 90% on legacy code is likely to be less valuable than just re-writing whole subsystems using TDD… and often more expensive.

Regardless, while Kevin is formally asking “is code coverage useful?” he’s really asking (rhetorically) is it reasonable to worship code coverage as the primary metric. But if no one’s asserting the positive, why is he questioning it? He may be dealing with a lot of people with misunderstandings of how TDD works. He could be dealing with metrics bigots. He could be dealing with management-imposed-metrics initiatives which often fail. It might be a pet peeve or he’s annoyed with TDD and this is a great way to do some agile-baiting of his own. I don’t know him, so I can’t say. His comments seem reasonable, so I assume no ill intent. But the answer to his rhetorical question is “yes, but in context.” Not surprising, since most rhetorically asked questions are answerable in this fashion. Hopefully it’s a bit clearer where it’s useful (and where/how) it’s not.

(This article is a cross-post from “Geek in a Suit”)


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Dependecy Injection on J2ME/CLDC devices.

This post is a little geeky and technical and product-related for AgileAdvice, and is a shameless self-promotion. Nevertheless, since testability, test-driven-development, and incremental design are non-exclusive sub-topics of Agile, I though I’d report this here anyway.

Many developers use the Dependency Injection and Inversion of Control (IoC) patterns through such IoC containers as Spring, Hivemind, Picocontainer, and others. They have all sorts of benefits to testability, flexibility, etc. that I won’t repeat here, but can be read about here, here, and here. A great summary of the history of “IoC” can be found here. J2ME developers, however, especially those on limited devices that use the CLDC configuration of J2ME, cannot use the substantial number of IoC/DI containers out there, because they nearly all rely on reflection. These also often make use of APIs not present in the CLDC – APIs which could not easily be added. Lastly there’s a tendency among developers of “embedded software” to be very suspicious of complexity.

In working out some examples of DI as part of a testability workshop at one of my clients, I whipped up a quick DI container, and being the freak that I am, hardened it until it was suitable for production, because I hate half-finished products. So allow me to introduce the Israfil Micro Container. (That is, the Container from the Israfil Micro project). As I mention in the docs, “FemtoContainer” just was too ridiculous, and this container is smaller than pico-container. The project is BSD licensed, and hosted on googlecode, so source is freely available and there’s an issue/feature tracker, yadda yadda.

Essentially I believe that people working on cellphones and set-top boxes shouldn’t be constrained out of some basic software design approaches – you just have to bend the design approach to fit the environment. So hopefully this is of use to more than one of my clients. It currently supports an auto-wiring registration, delayed object creation (until first need), and forthcoming are some basic lifecycle support, and a few other nicities. It does not use reflection (you use a little adapter for object creation instead), and performs quicker than pico-container. Low, low overhead. It’s also less than 10 classes and interfaces (including the two classes in the util project). It’s built with Maven2, so you can use it in any Maven2-built project with ease, but of course you can always also just download the jar (and the required util jar too). Enjoy…

P.S. There are a few other bits on googlecode that I’m working on in the micro-zone. Some minimalist backports of some of java.lang.concurrency (just the locks), as well as some of the java.util.Collections stuff. Not finished, but also part of the googlecode project.


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