The notion that Test Coverage alone can provide an adequate metric for determining how well a particular piece of code, or worse, an entire codebase, is being tested has always troubled me as, in my experience, this can be a very misleading assumption.

Like so many of my previous themes, with Test Coverage context trully is key as, relying on a predetermined percentage threshold as a true measure of successful testing fails to take into account the numerous factors involved. For example, the preceived thoroughness of a systems tests can easily be increased – beit mistakenly or intentionally – by testing parts of the system which could be considered irrelevant; such as getters, setters and the like.

Personally, I prefer (and advocate) focusing first on testing the most critical behaviors and state of a particular piece of code. The tests should not be limited to just testing the expected cases but also, and of equal importance, the testing of exceptional and negative tests.

I could go on about this in great detail however I recently came across a really good post from googletesting (which I found via Mike Labriola) which I think pretty much sums it up.

Often I come across what I like to call “Misplaced Code”, that is, code which should be refactored to a specific, independent concern rather than mistakenly being defined in an incorrect context.

For instance, consider the following example to get a better idea of what I mean:

Taking the above example into a broader context, it is quite common to see code such as this scattered throughout a codebase; particularly in the context of view concerns. At best this could become hard to maintain and, at worst, it will result in unexpected bugs down the road. In most cases (as in the above example) the actual code itself is not necessarily bad, however it is the context in which it is placed which is what I would like to highlight as it will almost certainly cause technical debt to some extent.

Considering the above example, should code such as this become redundantly implemented throughout a codebase it is quite easy to see how it can become a maintenance issue as, something as simple as a change to a hostname would require multiple refactorings. A much more appropriate solution would be to encapsulate this logic within a specific class whose purpose is to provide a facility from which this information can be determined. In this manner unnecessary redundancy would be eliminated (as well as risk) and valuable development time would be regained as the code would need only be tested and written once – in one place.

So again, using the above example, this could be refactored to a specific API and client code would leverage the API as in the following:

This may appear quite straightforward, however, I have seen examples (this one in particular) in numerous projects over the years and it is worth pointing out. Always take the context to which code is placed into consideration and you will reap the maintenance benefits in the long run.

Throughout my career I have always been drawn to books which provide a practical way of thinking about software. Books of this nature have an emphasis on the 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.

From time to time I find myself going back to the seminal text The Pragmatic Programmer as it provides a great source of what should be kept in mind from day to day. I thought I would share some tips from the book with my readers that I find of particular value, and would be happy to explain them at length; in the context of real world software challenges.

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.

I suggest keeping these tips, or a subset of them, as well as some of your own, somewhere visible; even if some appear rather obvious, as it will serve as a good general reminder of the things you should always keep in mind.

Ever need to determine what versions of a specific Maven dependency are available in a public repository? Or more importantly, determine if a dependency even exists in a public repository? If so, then javacio.us, a free, subscription based service available to anyone with a Google account can be used to help quickly and easily resolve maven dependencies.

Usage is simple:

1. Search Google for the name of the dependency (e.g. concurrent pom) and you will get a list of all groups in which the dependency is under a public repository.
2. Select the specific group you require
3. Select the version you require

And that’s it! Now you can simply copy the coordinates and the dependency has been resolved.

While there are certainly other services available which do more or less the same thing (e.g. Maven Repository Browser, etc.), the simplicity of being able to just search from Google is rather convenient.