- People, organizations, values
- Software development
- Why lean?
- Lean - resources
- Inspiration for improvement and making an impact
- Code quality
- Code (And Design) Quality And Why Should We Care
- Pragmatic Code Quality
- The Challenges of Legacy (Unclean) Code
- Code quality - resources
THIS IS ONLY A DRAFT
About the craft of software development and why it matters.
Effectiveness: the capability to achieve a chosen set of goals.
(Effectiveness = doing the right thing, efficiency = doing it right.)
By “craft” I mean focus on the following:
Making our organizations more effective
Building the right software, building it right, building it quickly
There are multiple aspects - organizational, human (motivation, mastery, …), technical (skills, …).
Bob Marshall: Rightshifting - according to the author, 80% of knowledge work organizations are very ineffective, wasting resources on non-value-adding activites; only few are effective, even fewer highly effective. Rightshifting is the attempt at shiting them to the right, towards higher effectiveness. Links to a few videos explaining it more. Related: Steve McConnell’s Business Case for Better Software Practices, referring to a study by SEI; “The actual distribution of software effectiveness is asymmetric. Most organizations perform much closer to the worst practice than to the best.” - the best performing 10 times better then the worst/average (productivity, speed, defects, value)
Tim O’Reilly: Create More Value Than You Capture (30 min + questions) - build apps that matter, that change how we do things. Thinking just about money is bad. Try to make the society better, smart, create more value than you capture, solve important problems, help people. Ex. startups: Uber, Square, Code for America.
Kent Beck: Making Making CoffeeScript [video, 20 min] - a wonderful and inspiring demonstration of some of the key values and practices of efficient software development (while developing a test framework for/in CoffeeScript) - focus on shortening the feedback loop and application of parallel change; iterative evolution/emergence.
Lean in keywords: autonomy feedback agility experimentation learning continual-improvement latest-responsible-moment humility
For me, lean is about admitting that the world around us is too chaotic, too changing, for us to be able to comprehend it fully and to control it. It is about giving up the false illusion of control that detailed, long-term plans and command & control structures provide and adopting a process suitable for our real chaotic environment, a process based on empirical control. An empirical process is constantly being adjusted based on the feedback from the environment. It is a scientific process: you form an hypothesis, act, observe the results, and adjust accordingly.
The consequences of adopting the lean approach are manifold. To be really able to experiment, learn, and react quickly, you must enable the people at the front line to do that, the command & control chain is too long, slow, and distant from the situation. They must have motivation, autonomy, power to decide. And the teams must be cross-functional to be able to grasp the situation and act effectively (leading to DevOps etc.). You must relentlessly question and improve your process because it is never perfect and because the situation keeps on changing. You must focus on creating fast feedback loops - for software development, this eventually leads to continuous delivery and high focus on code quality.
Lean software development: Admit that nobody really knows what should be built and that it thus has to be found out via experimentation (hypothesis → feedback). Therefore it is crucial to start by understand the business need/value. Be aware that software doesn’t just fit into a situation, it effects it - therefore ask how the processes are going to change due to / for the sake of the software to be developed. Build cross-functional teams (devops, testers, business). Do not base the development on plans but on business value and goals and measuring the project’s contribution to them. Be aware of the cost of complexity and the 80:20 rule and stop the development when enough business value has been providing (preferably before implementing the other 60-80% of the features that would be rarely used but multiply the complexity). Be aware of the fact that there can be a much cheaper, faster, perhaps non-technical solution to the business need.
TODO: Resources, ideas
Antifragile ⇒ principles (motiv. people, worker’s intelligence, …)
“feedback loops” - link to Kim’s blog
Tom Gilb: Agile revised JZ12 talk, papers, book
Gojko Adzic’s Impact Mapping
Ward Cun. & others: SW devel. is primarily a process of learning (what, why & how to build)
Lean <> agile <> code quality
cynefin’s 4 quadrants
Cash to concept - 7 rules of lean, …
quality <> speed
autonomy x motivation etc.
Agile in a Nutshell (originally Agile Product Ownership in a Nutshell) by Henrik Kniberg - the best explanation of the agile development process ever, in just 15 minutes and with wonderful animation; every developer should see this. Some highlights: the most important task of product owner is to say NO so that backlog doesn’t grow infinitely; at start, the estimates of size and value will suck and that’s OK because the value is in the conversation, not in the numbers (that are anyway just relative); the goal is to maximize outcome (value), not output (# features). Compromises between short-term vs. long-term goals, knowledge vs. customer value building etc. Build the right thing (PO) x build it right (devs) x build it fast (SM). Technical debt x sustainable pace. As I said - you MUST see it.
M. Fowler: The New Methodology - a good description of the rise of Agile, the motivation for it, the various Agile methodologies (XP, Lean, Scrum etc.) and what is required to be able to apply an agile approach. Main points: Agile is adaptive (vs. predictive) and relies heavily on people and their judgement and skills (vs. treating them as same, replacable units) - which also leads to the need of leadership instead of (command&control) management. Discusses unpredictability of requirements and scope, foolishness of separating design and implementation, difficulty of measurement of SW development, continuous improvement etc. Quotes: “However letting go of predictability doesn’t mean you have to revert to uncontrollable chaos. Instead you need a process that can give you control over an unpredictability. That’s what adaptivity is all about.”
The Toyota concept of ‘respect for people’ - many state that they respect their workers but fail to really understand what it means; it is not about freedom of act, it is about a mutual respect, leveraging the strengths of each other: worker’s experience and insight and manager’s broader overview, as demonstrated by the problem-solving dialog and challenges (problem - root cause - solution - measure of success, the manager challenging the worker’s answers). Also a nice example how the evaluation of individual performance leads to a much worse system and high turnover compared to a whole-oriented company.
It’s a state of mind: some practical indicators on doing agile vs. being agile - are you agile or are just “doing agile”? Read on ti find out, if you dare! F.ex. “Non Agile teams have a process that slows the review of the changes.” Cocnlusion: “An Agile mindset is just that – a state of mind, a set of values. Its a constant questioning, and an opening up to possibilities. Its a predisposition to produce great things.”
Dave Nicolett: I know how to tie my shoes - on the difficulty of convincing people to try unfamiliar software development techniques - “People change the way they operate when they are experiencing some sort of inconvenience or negative feedback. As long as things are going along reasonably well, people don’t go out of their way to change the way they work.” (with few exceptions) You can learn to tie your shoes in a split second, but why to invest the effort? You’d need to set aside assumptions, suppress habits, practice. You can argument there are many inconveniences (bugs, criticism for slow delivery, …) but “Unfortunately, that’s all pretty normal, and most people in the software field are accustomed to it. They don’t see it as a problem that calls for them to change their practices. Most of them probably have a hard time visualizing a different reality.” ⇒ Maybe that’s the reason there’s been no satisfactory answer to the question of how to convince people to adopt different practices. We shouldn’t be trying to convince people to do anything. We should be helping people solve their problems and achieve their goals. If they are satisfied with the outcomes they achieve using their current methods, then there is no problem to solve.
Why Software Projects are Terrible and How Not To Fix Them - many teams are not ready to embrace new/better software practices, primarly for two reasons: 1) most of them are nonintuitive (f.ex. adding more people will slow dev down) and need to be sold through a high hierarchy of managament - but people/managers/organizations don’t really care, it takes years for good/bad practices to have an impact, which is not relevant “now.” 2) Businss objectives change too quickly and SW is blamed for not delivering. Based on evaluating many failed projects. Conclusion: Choose carefully people/organizations your work with. Avoid blame-driven ones. Quote on middle managers: “He has to put more developers on the project, call a meeting and yell at people, and other arbitrary bad ideas. Not because he thinks those will solve the problem. In fact, managers often do this in spite of the fact that they know it’s bad. *Because that’s what will convince upper management that they’re doing their best.*” “In the vast majority of failed projects I’ve been called to looked at, the managers have not read one book on software engineering.”
If your process is the same in a year from now then you are far less efficient than you could be. #kaizen
Learn the rules, practice them, transcend them. No methodology is perfect, no rule or pattern is absolute. You need to think for yourself, question, experiment, think originally.
Forget delivering software. Make an impact, deliver valuable change. What valuable change should your current project cause? And no, software is not always the right answer.
Be humble, respect people, question your thinking. Often we see something, jump to a conclusion, rush for an action, persuaded about our truth and determined to win and change the situation as we want for the good of all involved. Do not act based on unverified assumptions and beliefs - make your though process transparent to yourself and to others, check it with them, act based on open, verifiable data - see the Ladder of Inference for details (nicely introduced in this 5 min TED video called Rethinking thinking, by Trevor Maber).
A traveller meets a woodcutter cutting trees with a blunt axe and asks: “Why don’t you sharpen your axe?” Woodcutter: “I’ve no time for that, I must cut trees!” (unknown origin)
clean code values (impl. patt. KB): communication, simplicity, flexibility
guiding principles (Kent): locality of change etc.
principles: SRP, SoC, KISS, DRY ⇒ small methods on the same level of abstraction, intention-revealing name and organization, …
cleanliness maintenance during dev.: as cooks that end up with totally dirty and thrashed kitchen x those ending up with a clean one ready for further cooking
structure and abstractness level: code as a journalist - the pyramid structure of an article (incr. level of detail and amount of content)
What, when is “good enough”? - always can be increased; economics: cost x benefit
From the code alone you can see what happens but not why this behavior is there. A business requirement may be implemented in multiple ways. If the code isn’t well structured then you cannot distinguish which part is there as an essential consequence of the requirement and which part is there just because of the particular implementation way chosen. Thus “the code is the documentation” really fails here.
When you need to modify - e.g. fix - a piece of duplicated (due to copy&paste[&modify] etc.) logic, you usually need to modify also the other duplicates. This is easy to forget (especially because the code is hard to understand), leading to only partially fixed defects and inconsistencies.
Testing is a key practice enabling clean code.
Local testing-related posts:
(Presumabely) good books about testing (though, according to Kent Beck as of 11/2012, “Really, the right book has yet to be written.”):
Martin Fowler: The Value of Software Design (talk, 22 min, from 0:45:00 til 1:07; Feb 2013) - a balanced argument for the value of good software design and internal code quality based on paying off by enabling us to keep our development speed. Discusses the DesignStaminaHypothesis (bad design ⇒ rapid decline of development speed), TechnicalDebt, TechnicalDebtQuadrant (Prudent x Reckless, Deliberate x Inadvertent), TradableQualityHypothesis. According to the experience of Fowler and others, the good design payoff point “it’s weeks, not months.”
Opportunistic Refactoring by Martin Fowler – refactor on the go – how & why
Michael Feathers: Getting Empirical about Refactoring – gather information that helps us understand the impact of our refactoring decisions using data from a SCM, namely File Churn (frequency of changes, i.e. commits) vs. Complexity – files with both high really need refactoring. Summary: “If we refactor as we make changes to our code, we end up working in progressively better code. Sometimes, however, it’s nice to take a high-level view of a code base so that we can discover where the dragons are. I’ve been finding that this churn-vs.-complexity view helps me find good refactoring candidates and also gives me a good snapshot view of the design, commit, and refactoring styles of a team.“
Principles for Creating Maintainable and Evolvable Tests - naming, proper level of abstraction
CodingHorror: Coding Without Comments (2008) - a very good explanation if how to treat comments (similar what Clean Code says): write code so that it is self-explanatory (using good method and variable names), if necessary, add comments that explain why (while the code shows what/how).
I like my tests to by very simple examples of what the production code does. I don’t like it when I have to think about what the tests mean…
- Matteo Vaccari in a post about Kent Beck’s Simplification strategy
Any fool can write code that a computer can understand. Good programmers write code that humans can understand.