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Test First Workflow – A Short Story

Saturday, February 2nd, 2013

As a depiction of the typical approach taken when solving a problem with Test First practices in mind, below is a brief excerpt from a recent conversation with a collegue who inquired of me as to how one generally goes about solving a problem using Test First methodologies. My explanation was rather simple, and read somewhat like a short story, though I describe it as being more of a step by step process from a Pair Programming perspective.

The general workflow conveyed in my description, while brief, covers the essentials:

  1. We have a problem to solve.
  2. We discuss the problem, asking questions as needed; then dig a bit deeper to ensure we understand what it is we are really trying to solve; and, most importantly, why.
  3. We consider potential solutions, identifying those most relevant, evaluating each against the problem; then agree upon one which best meets our needs.
  4. We define a placeholder test/spec where our solution will be exercised. It does nothing yet.
  5. We implement the solution in the simplest manner possible, directly within the test itself; the code is quite ugly, and that is perfectly fine, for now. We run our test, it fails
  6. We adjust our implementation, continuing to focus solely on solving the problem; all the while making sure not to become too distracted with implementation details at this point.
  7. We run our test again, it passes. We’re happy, we’ve solved the problem.
  8. We move our solution out of the test/spec to the actual method which is to be implemented, which, until now, had yet to exist.
  9. We update our test assertions/expectations against the actual (SUT). We run our test, it passes.
  10. We’re happy, we have a working, tested solution; however, the implementation is substandard; this has been nagging at us all along, so we shift focus to our design; refactoring our code to a more elegant, performant solution; one which we can be proud of.
  11. We run our test again, it fails. That’s fine, perhaps even preferable, as it verifies our test is doing exactly what is expected of it; thus, we can continue to refactor in confidence.
  12. We adjust our code, continuing to make design decisions and implementation changes as needed. We run our test again, it passes.
  13. We refactor some more, continuing to focus freely, and without worry on the soundness of our design and our implementation. We run our test again, it passes.

Rinse and Repeat…

While the above steps are representative of a typical development work-flow based on Test First processes, it is worth noting that as one becomes more acclimated with such processes, certain steps often become unnecessary. For example, I generally omit Step #5 insofar as implementing the solution within the test/spec itself is concerned; but rather, once I understand the problem to be solved, I then determine an appropriate name for the method which is to be tested, and implement the solution within the SUT itself, as opposed to the test/spec; effectively eliminating the need for Step #8. As such, the steps can be reduced down to only those which experience proves most appropriate.

Concluding Thoughts

Having become such an integral part of my everyday workflow for many years now, I find it rather challenging to approach solving a problem without using Test First methodologies. In fact, attempting to solve a problem of even moderate complexity without approaching it from a testing perspective feels quite awkward.

The simple fact is, without following general Test First practices, we are just writing implementation code, and if we are just writing implementation code, then, in turn, we are likely not thinking through a problem in it’s entirety. Consequently, it follows then that we are also not thinking through our solutions in their entirety, and hence our designs. Because of this, solutions feel uncertain, and ultimately leave us feeling much less confident in the code we deliver.

Conversely, when following sound testing practices we afford our team and ourselves an unrivaled sense of confidence in terms of the specific problems we are solving, why we are solving them, and how we go about solving them; from that, we achieve a concerted understanding of the problem domain, as well as a much clearer, holistic understanding of our designs.

Practices of an Agile Developer

Thursday, February 10th, 2011

Of the many software engineering books I have read over the years, Practices of an Agile Developer in particular continues to be one book I find myself turning to time and time again for inspiration.

Written by two of my favorite technical authors, Andy Hunt and Venkat Subramaniam, and published as part of the Pragmatic Bookshelf, Practices of an Agile Developer provides invaluable, practical and highly inspirational solutions to the most common challenges we as software engineers face project after project.

What makes Practices of an Agile Developer something truly special is the simplicity and easy to digest format in which it is written; readers can jump in at any chapter, or practically any page for that matter, and easily learn something new and useful in a matter of minutes.

While covering many of the most common subjects on software development, as well as many particularly unique subjects, it is the manner in which the subjects are presented that makes the book itself quite unique. The chapters are formatted such that each provides an “Angel vs. Devil on your shoulders” perspective of each topic. This is quite useful as one can briefly reference any topic to take away something useful by simply reading the chapters title and the “Angel vs. Devil” advice, and from that come to a quick understanding of the solution. Moreover, each chapter also provides tips on “How it Feels” when following one of the prescribed approaches. The “How it feels” approach is very powerful in that it instantly draws readers in for more detailed explanations. Complimentary to this is the “Keeping your balance” suggestions which provide useful insights to many of the challenges one might face when trying to apply the learnings of a particular subject. “Keeping your Balance” tips answer questions which would otherwise be left to the reader to figure out.

I first read Practices of an Agile Developer almost 4 years ago, and to this day I regularly find myself returning to it time and time again for inspiration. A seminal text by all means, I highly recommend it as a must read for Software Developers of all levels and disciplines.

Some useful Tips to keep in mind

Sunday, February 28th, 2010

Throughout my career I have always been drawn to books which provide a practical way of thinking about software. Books of this nature tend to have an emphasis on fundamental principles which apply to all software engineering disciplines, and form much of the basis of the Agile methodologies many of us have come to appreciate.

Often, I find myself going back to the seminal text The Pragmatic Programmer as it provides a great source of some important things I like to keep in mind from day to day. And so, I just wanted to take a moment to share some of the best tips from the book which I have found to be particularly useful, and inspiring.

Care About Your Craft

Why spend your life developing software unless you care about doing it well?

Provide Options, Don’t Make Lame Excuses

Instead of excuses, provide options. Don’t say it can’t be done; explain what can be done.

Critically Analyze What You Read and Hear

Don’t be swayed by vendors, media hype, or dogma. Analyze information in terms of you and your project.

Design with Contracts

Use contracts to document and verify that code does no more and no less than it claims to do.

Refactor Early, Refactor Often

Just as you might weed and rearrange a garden, rewrite, rework, and re-architect code when it needs it. Fix the root of the problem.

Costly Tools Don’t Produce Better Designs

Beware of vendor hype, industry dogma, and the aura of the price tag. Judge tools on their merits.

Start When You’re Ready

You’ve been building experience all your life. Don’t ignore niggling doubts.

Don’t Be a Slave to Formal Methods

Don’t blindly adopt any technique without putting it into the context of your development practices and capabilities.

It’s Both What You Say and the Way You Say It

There’s no point in having great ideas if you don’t communicate them effectively.

You Can’t Write Perfect Software

Software can’t be perfect. Protect your code and users from the inevitable errors.

Build Documentation In, Don’t Bolt It On

Documentation created separately from code is less likely to be correct and up to date.

Put Abstractions in Code, Details in Metadata

Program for the general case, and put the specifics outside the compiled code base.

Work with a User to Think Like a User

It’s the best way to gain insight into how the system will really be used.

Program Close to the Problem Domain

Design and code in your user’s language.

Use a Project Glossary

Create and maintain a single source of all the specific terms and vocabulary for a project.

Be a Catalyst for Change

You can’t force change on people. Instead, show them how the future might be and help them participate in creating it.

DRY – Don’t Repeat Yourself

Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

Eliminate Effects Between Unrelated Things

Design components that are self-contained, independent, and have a single, well-defined purpose.

Iterate the Schedule with the Code

Use experience you gain as you implement to refine the project time scales.

Use the Power of Command Shells

Use the shell when graphical user interfaces don’t cut it.

Don’t Panic When Debugging

Take a deep breath and THINK! about what could be causing the bug.

Don’t Assume It – Prove It

Prove your assumptions in the actual environment—with real data and boundary conditions.

Write Code That Writes Code

Code generators increase your productivity and help avoid duplication.

Test Your Software, or Your Users Will

Test ruthlessly. Don’t make your users find bugs for you.

Don’t Gather Requirements—Dig for Them

Requirements rarely lie on the surface. They’re buried deep beneath layers of assumptions, misconceptions, and politics.

Abstractions Live Longer than Details

Invest in the abstraction, not the implementation. Abstractions can survive the barrage of changes from different implementations and new technologies.

Don’t Think Outside the Box—Find the Box

When faced with an impossible problem, identify the real constraints. Ask yourself: “Does it have to be done this way? Does it have to be done at all?”;

Some Things Are Better Done than Described

Don’t fall into the specification spiral—at some point you need to start coding.

Don’t Use Manual Procedures

A shell script or batch file will execute the same instructions, in the same order, time after time.

Test State Coverage, Not Code Coverage

Identify and test significant program states. Just testing lines of code isn’t enough.

Gently Exceed Your Users’ Expectations

Come to understand your users’ expectations, then deliver just that little bit more.

Don’t Live with Broken Windows

Fix bad designs, wrong decisions, and poor code when you see them.

Remember the Big Picture

Don’t get so engrossed in the details that you forget to check what’s happening around you.

Make It Easy to Reuse

If it’s easy to reuse, people will. Create an environment that supports reuse.

There Are No Final Decisions

No decision is cast in stone. Instead, consider each as being written in the sand at the beach, and plan for change.

Estimate to Avoid Surprises

Estimate before you start. You’ll spot potential problems up front.

Use a Single Editor Well

The editor should be an extension of your hand; make sure your editor is configurable, extensible, and programmable.

Fix the Problem, Not the Blame

It doesn’t really matter whether the bug is your fault or someone else’s—it is still your problem, and it still needs to be fixed.

“select” Isn’t Broken

It is rare to find a bug in the OS or the compiler, or even a third-party product or library. The bug is most likely in the application.

Learn a Text Manipulation Language

You spend a large part of each day working with text. Why not have the computer do some of it for you?

Use Exceptions for Exceptional Problems

Exceptions can suffer from all the readability and maintainability problems of classic spaghetti code. Reserve exceptions for exceptional things.

Minimize Coupling Between Modules

Avoid coupling by writing shy” code and applying the Law of Demeter.

Design Using Services

Design in terms of services: independent, concurrent objects behind well-defined, consistent interfaces.

Don’t Program by Coincidence

Rely only on reliable things. Beware of accidental complexity, and don’t confuse a happy coincidence with a purposeful plan.

Organize Teams Around Functionality

Don’t separate designers from coders, testers from data modelers. Build teams the way you build code.

Test Early. Test Often. Test Automatically.

Tests that run with every build are much more effective than test plans that sit on a shelf.

Find Bugs Once

Once a human tester finds a bug, it should be the last time a human tester finds that bug. Automatic tests should check for it from then on.

Sign Your Work

Craftsmen of an earlier age were proud to sign their work. You should be, too.

It is my hope that you will find some of these tips helpful and, if so, I suggest keeping those which resonate with you (as well as some of your own) someplace visible for reference as it will help serve as a nice reminder of the more important things we should always keep in mind.

Why is programming fun?

Wednesday, September 16th, 2009

Just recently while going through some old files I rediscovered a quote that is rather inspiring.

The quote is an extract from the book “The Mythical Man-Month”, and while the book was originally published in 1974 before being republished in 1995, I feel it will always remain relevant:

Why is programming fun? What delights may its practitioner expect as his reward?

First is the sheer joy of making things. As the child delights in his mud pie, so the adult enjoys building things, especially things of his own design. I think this delight must be an image of God’s delight in making things, a delight shown in the distinctness and newness of each leaf and each snowflake.

Second is the pleasure of making things that are useful to other people. Deep within, we want others to use our work and to find it helpful. In this respect the programming system is not essentially different from the child’s first clay pencil holder “for Daddy’s office.”

Third is the fascination of fashioning complex puzzle-like objects of interlocking moving parts and watching them work in subtle cycles, playing out the consequences of principles built in from the beginning. The programmed computer has all the fascination of the pinball machine or the jukebox mechanism, carried to the ultimate.

Fourth is the joy of always learning, which springs from the non-repeating nature of the task. In one way or another the problem is ever new, and its solver learns something: sometimes practical, sometimes theoretical, and sometimes both.

Finally, there is the delight of working in such a tractable medium. The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by exertion of the imagination. Few media of creation are so flexible, so easy to polish and rework, so readily capable of realizing grand conceptual structures.

Yet the program construct, unlike the poet’s words, is real in the sense that it moves and works, producing visible outputs separately from the construct itself. It prints results, draws pictures, produces sounds, moves arms. The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard, and a display screen comes to life, showing things that never were nor could be.

Programming then is fun because it gratifies creative longings built deep within us and delights sensibilities we have in common with all men.

This quote really hits home with me, so I shared it with my team and felt I should also share it with the community, as I imagine it will also inspire many others as well.

Perfectionism, Prudence and Progress

Thursday, June 11th, 2009

Yesterday there was an interesting article on InsideRIA titled: “How much is too much?”. This is a great topic, one which at times I have questioned myself.

Personally, I never take the “easy way out”, preferring to do things the “hard way”, so to speak. At times the benefits in doing things according to best practices, standards and conventions (a.k.a. “the right way”) may not always be immediately obvious. However over the years experience has taught me that in time the benefits always reveal themselves and the pros certainly outweigh the cons.

When given a good amount of forethought to a decision, a design an implementation and so forth a team almost certainly is afforded the ability to continue development feasibly and in a less challenging manner (as opposed to dealing with endless maintenance challenges). When things are done quickly with little regard for anything other than getting working code out the result is always failure at some level, most commonly the maintainability of a product.

With all this in mind it is important to understand that at the end of the day our development efforts, for better or for worse, are simply a means to an end for a specific business need. Therefore just as writing “quick and dirty” code has a negative impact on the business, so too does being a complete perfectionist. Admittedly, this used to be a challenge for me as I would tend to need designs, tests and code to “feel right” for them to be considered production ready, which typically resulted in me working many extra hours on my own time. This in itself is not necessarily a bad thing, but could rather be considered a labor of passion.

Ultimately the goal should be to find just the right balance of perfectionism, prudence and progress, providing necessary trade-offs where appropriate.

Pattern Recognition

Saturday, January 17th, 2009

It has been said that the true sign of intelligence lies in ones ability to recognize patterns – and there is a lot to be said of that statement as patterns can be found everywhere, in everything, in everyday life.

One of the greatest strengths of human intelligence is in our ability to recognize patterns and abstract symbolic representations even when they occur in contexts different from that in which we originally learned them. It’s why hard to grasp concepts which are foreign or new to us become very clear when explained through metaphor.

This ability to recognize patterns is essential to our survival, always has been. For example, practically all ancient civilizations had a very, very good understanding of the recurring patterns in their environment; something we like to call seasons. This understanding of patterns in time and climate was crucial to the survival of these early civilizations. Our ability to recognize patterns is essential to our learning and understanding of the world around us. Pattern recognition is a cognitive process much like intuition. Arguably they are inter-related or possibly one and the same.

Suppose you you want to lose a few pounds, or save a little extra money, or learn a new programming language etc. but you are not seeing the results you would like. By recognizing patterns in your behavior you will begin to notice areas which need to be adjusted and from that determine an appropriate solution and the necessary adjustments to be made in order to achieve your goal. For example, maybe you’ve been trying to save some extra money and after a few months realize you are getting nowhere. You then analyze your behavior for recurring patterns and realize your spending half your pay every weekend on beer, just kidding, but you get my point.

Pattern Recognition in Software Development

In the world of software development patterns apply in pretty much just the same way – our ability to recognize them is essential to ensuring the success of a software application. When we discover patterns of recurring problems in software we are then able to consider various potential patterns from a catalog of named solutions, i.e. Design Patterns. Once an appropriate solution is found we can apply it to resolve the problem regardless of the domain.

When designing software, patterns are something that should reveal themselves, never forced into a design. This is how patterns should always be applied; you have a problem, and based on that problem you begin to recognize common patterns, or maybe new ones, which can be applied as a solution to resolve the problem. It should never be the other way around, that is, a solution (Pattern) looking for a problem. However this happens quite often and is pretty evident in many software applications. Many refer to this as “pattern fever“, personally I like to call it “patterns for patterns sake“, or simply “for patterns sake“. Because that’s really what it is.

For example, have you ever found a Singleton implementation where an all static class would have sufficed (e.g. utilities). Or a code behind implementation class which masquerades as an abstract class. Or an Interface where there is clearly only a need for a single concrete implementation (e.g. data centric implementations), or a marker Interface which serves no purpose at all. The list goes on and on.

In some cases it very well may just be an innocent flaw in the design, however the majority of the time it’s a tell tale sign of someone learning a new pattern and knowingly, albeit, mistakenly, attempting to implement the pattern into production code. This is clearly the wrong way of learning a new pattern. Learning new design patterns is great and a lot of fun but remember, there is a time and place for everything, and production code isn’t it.

Learning Patterns

One of the best ways to learn a new pattern (or anything new for that matter) is to explore it. Begin by reading enough about it to get some of the basic concepts to sink in a bit. Put it into context, think of it in terms of metaphor – in ways that make sense to you, remember you are learning this. Question it. Then experiment with it. See how it works, see how it doesn’t work, break it, figure out how to put it back together, and so on, but whatever works best for you. Most importantly always do it as a separate effort such as a POC, but never in production code.

Once you get this down and understand the various patterns you’ll find you never need to look for them, for if they are needed they will reveal themselves sure enough.