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Managing Risk via Static Analysis

Editorial Note: I originally wrote this post for the NDepend blog.  Check out the original here, at their site.  While you’re there, take a look at the features of NDepend and download a trial, if you’re so inclined.

When software developer talk about static analysis, it’s often in the context of craft improvement.  Ask most developers in a group about static analysis tools and you’ll get a range of responses, many of which will be fueled by some degree of passion, resulting from past experience.  From here, the conversation will tend to dive into the weeds for any non-technical stakeholder that might be listening; if you’re not a programmer, you probably don’t have much of an opinion as to whether or not cyclomatic complexity of 5 is acceptable for a method.

As a result, static analysis tends to get pegged heavily as a purely a matter of shop.  The topic tends to be pretty opaque to management because developers present it to them in terms of “this will make us better and the code better.”  Management that trusts the developers will tend to agree to the purchase with a sentiment of, “okay, I’ll take your word for it.”  Management that is more skeptical says, “maybe next year if our numbers are good.”

I find this to be a shame because it’s a lost opportunity, even when management agrees.

Static analysis most certainly is a way for developers to improve their craft and their codebases.  But, in the hands of an architect or team lead that truly understands the business and works well with management, static analysis can be an excellent tool for managers, even if the use has to be a management-architect team effort.

How so?  Well, there are a lot of ways, but the one I’d like to mention today is risk management.  As the title would imply, managing risk tends to be the purview of people whose title is manager.  Sure, the developers have responsibility for this, but their primary charter is to build stuff — management exists specifically to engage in planning activities, including the crucial concern of risk management.

How does this work?  Well, I’ll show you, and I’ll do it by explaining the sort of highly technical things that static analysis could catch in highly non-technical and readable ways.  These are all going to be operational risks — static analysis can’t help you if you’re building the wrong product or badly under-staffing your projects.  But it can help you avoid landmines in your software.  If you’re a manager, allow me, for the moment, to serve as your “business-savvy architect.”

Architect

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How Do I Write Good Code?

My life has been undergoing some task thrash of late. That, combined with a decent amount of time doing car trips, has thrown me off of my recent reader question streak, in favor of cross posts.  But, today I remedy that.  A reader has a pretty straightforward question: “how do I write good code?”

Here is the question, verbatim.  It references a post that I wrote a while back that has definitely sparked some discussions and follow-up questions.

You write about how to “de-brilliant” your code. I have worked with “brilliant” code in the past and can say that experience is anything but. I’m starting my career as a software dev now and one of the things I’ve been wondering about recently is how to write good code? I think generally that I can recognize well written code from poorly written code, but I want to get even better and I’m not sure how.

First of all, congratulations on the new career!  You’re off to a good start.  I’d say you’re beginning auspiciously by asking a question that is important, easy to understand, and really, really nuanced to answer.  But, let’s try.  Here is my general take on how to write good code, in order of priority.

DevSkills

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Is Your Source Control Usage Conducive to Code Review?

Editorial Note: I originally wrote this post for the SmartBear blog.  Head over to their site and check out the original.  While you’re there, have a look around at posts by some other authors as well.

I can think back to times in my career that the source control that I was using (or not using) made me a cranky, unhappy human being.  Years and years ago, there was the time that a coworker accidentally left all of the files in the codebase checked out through Visual SourceSafe and went on vacation.  I distinctly remember enlisting a sysadmin and the two of us going into the source control server with admin credentials and hacking at settings until we could undo that and I could work.  You see, Visual SourceSafe employed a pessimistic locking strategy by which his checkout meant I couldn’t do anything with the code.

There was also the time, a few years later, when I was suffering through a project that used Rational Clear Case.  On a normal day, delivering code to the official branch or stream or whatever took half an hour.  If I had to work from home, it took all morning.

Angry guy smshing computer

And then there was the time that I was switched onto a project with no source control at all.  The C source code was stored on a production server — a production server that controlled physical machinery in the real world.  To “check things in,” you would modify the C code, turn off the physical machine, load the modified kernel modules, turn the machine on, and then revert real quick if things started blowing up.  I’m not kidding.  This was the commit/rollback strategy when I arrived (I did actually migrate this).

Tools Affect Behavior

These things make for fun war stories, but they also serve to illustrate how source control dictates behavior.  With Visual SourceSafe, we implemented some kind of out of band email protocol to remind people to check in.  With Rational Clear Case, I implemented a homegrown SVN for day to day version control and delivered/integrated only a few times per month.  With the machine server, there was extensive historical commenting in every single source file.  These tools spur you toward behaviors, and, in these cases, toward wasteful or bad behaviors.

For the examples I listed, I was steered toward useless process, steered away from continuous integration, and steered toward neurotic documentation.  But the steering can apply to almost anything, and that includes having a healthy code review process.

There have been studies conducted that demonstrate the importance of code review.  It is uniquely effective when it comes to catching defects earlier than later, and it promotes collective code ownership, thus reducing “bus factor.”  I could go on, but let’s take it as axiomatic in this post that you want to do it.

Does your source control situation make it easy for you to conduct code reviews?  Or does it discourage you, making life tough if you do them, and thus making you less likely to do them.  If it’s the latter, that’s not a good situation.

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The Human Cost of Tech Debt

Editorial Note: I originally wrote this post for the Infragistics blog.  Head over to their site and check out the original.  While you’re there, have a look at the other blog authors and their product offering.

If you’re not already familiar with the concept of technical debt, it’s worth becoming familiar with it.  I say this not only because it is a common industry term, but because it is an important concept.

Coined by Ward Cunningham, the term introduces the idea that taking shortcuts in your software today not only means paying the price eventually — it means paying that price with interest.  In other words, introducing that global variable today and saving half a day’s work ahead of shipping means that you’re going to pay for it with more than half a day’s labor down the line.

Man holding heavy chest

The Power of the Metaphor

I’ve spent significant time doing IT management consulting in recent years, after spending years and years writing code.  And I can tell you that this metaphor for shortcuts in the codebase is a powerful one when it comes to communication between the business and the software development group.  When you explain software decisions to managers and MBAs using the language of economics, they get it.

Because of the metaphor’s power and subsequent effectiveness for business concerns, it is often used to describe the health of projects, particularly vis a vis deadlines and milestones.  The developers may communicate that an aggressive deadline will result in technical debt, making features in the future take longer to ship.  Analysts and project managers might account for technical debt when discussing slipped deadlines.  IT upper management might ask for an assessment of the amount of technical in an application when making a strategic, replace/retire/rewrite decision.

The problem of technical debt is for most people, in essence, a problem of time to market.

But I’d like to talk today about the human side of the problem.  And, make no mistake — in business, all human problems are also business problems,viewed with a wide enough lens.  Unhappy humans are unhappy workers, and unhappy workers are less productive.  Yet, this angle of technical debt is seldom discussed, in my experience.

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Easy to Miss Code Smells

Editorial Note: I originally wrote this post for the NDepend blog.  Please head over to the site and check out the original.  There’s a lot of great content over there, and, if you’re not familiar with NDepend, download a trial and try it out.

The concept of a code smell is, perhaps, one of the most evocative in our profession.  The name itself has a levity factor to it, conjuring a mental image of one’s coworkers writing code so bad that it actually emits a foul odor.  But the metaphor has a certain utility as well in the “where there’s smoke, there may be fire” sense.

In case you’re not familiar, a code smell is an observable feature of the code (the smoke) that often belies a deeper existing problem (the fire).  When you say that a code smell exists, what you’re communicating is “you may be justified here, but I’m skeptical – in my experience this is probably a design flaw.”

Smelly computer

Of course, accusing code of having a smell is only slightly less incendiary to the author than accusing code of being flat out bad.  Them’s fightin’ words, as they say.  But, for all the arguments and all of the righteous indignation that code smell accusations have generated over the years, their usefulness is undeniable.

No doubt you’ve heard of some of the most common and easiest to visualize code smells.  The God Class, Primitive Obsession, and Inappropriate Intimacy all come to mind.  These indicate, respectively a class in your code base doing way too much, a tendency to use primitive types when you should take advantage of classes, and a module or class that breaks encapsulation by knowing too many details about another.  The combination of their visual memorability and their wisdom has prodded us over the years to break things down, to create cohesive objects, and to preserve encapsulation.

I would argue, however, that there are many more code smells out there than the big, iconic ones that get a lot of attention.  I’d like today to discuss a few that I don’t think are as commonly known.  I’ll make the case for why, once you’ve mastered avoiding the well-known ones, you should watch for these as well.

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