You can go to read the previous very interesting points #4, #5, #6.
7. Beware the Share by Udi Dahan
It was my first project at the company. I'd just finished my degree and was anxious to prove myself, staying late every day going through the existing code. As I worked through my first feature I took extra care to put in place everything I had learned — commenting, logging, pulling out shared code into libraries where possible, the works. The code review that I had felt so ready for came as a rude awakening — reuse was frowned upon!
How could this be? All through college reuse was held up as the epitome of quality software engineering. All the articles I had read, the textbooks, the seasoned software professionals who taught me. Was it all wrong?
It turns out that I was missing something critical.
The fact that two wildly different parts of the system performed some logic in the same way meant less than I thought. Up until I had pulled out those libraries of shared code, these parts were not dependent on each other. Each could evolve independently. Each could change its logic to suit the needs of the system's changing business environment. Those four lines of similar code were accidental — a temporal anomaly, a coincidence. That is, until I came along.
The libraries of shared code I created tied the shoelaces of each foot to each other. Steps by one business domain could not be made without first synchronizing with the other. Maintenance costs in those independent functions used to be negligible, but the common library required an order of magnitude more testing.
While I'd decreased the absolute number of lines of code in the system, I had increased the number of dependencies. The context of these dependencies is critical — had they been localized, it may have been justified and had some positive value. When these dependencies aren't held in check, their tendrils entangle the larger concerns of the system even though the code itself looks just fine.
These mistakes are insidious in that, at their core, they sound like a good idea. When applied in the right context, these techniques are valuable. In the wrong context, they increase cost rather than value. When coming into an existing code base with no knowledge of the context where the various parts will be used, I'm much more careful these days about what is shared.
Beware the share. Check your context. Only then, proceed.8. The Boy Scout Rule by Uncle Bob
The Boy Scouts have a rule: "Always leave the campground cleaner than you found it." If you find a mess on the ground, you clean it up regardless of who might have made the mess. You intentionally improve the environment for the next group of campers. Actually the original form of that rule, written by Robert Stephenson Smyth Baden-Powell, the father of scouting, was "Try and leave this world a little better than you found it."
What if we followed a similar rule in our code: "Always check a module in cleaner than when you checked it out." No matter who the original author was, what if we always made some effort, no matter how small, to improve the module. What would be the result?
I think if we all followed that simple rule, we'd see the end of the relentless deterioration of our software systems. Instead, our systems would gradually get better and better as they evolved. We'd also see teams caring for the system as a whole, rather than just individuals caring for their own small little part.
I don't think this rule is too much to ask. You don't have to make every module perfect before you check it in. You simply have to make it a little bit better than when you checked it out. Of course, this means that any code you add to a module must be clean. It also means that you clean up at least one other thing before you check the module back in. You might simply improve the name of one variable, or split one long function into two smaller functions. You might break a circular dependency, or add an interface to decouple policy from detail.
Frankly, this just sounds like common decency to me — like washing your hands after you use the restroom, or putting your trash in the bin instead of dropping it on the floor. Indeed the act of leaving a mess in the code should be as socially unacceptable as littering. It should be something that just isn't done.
But it's more than that. Caring for our own code is one thing. Caring for the team's code is quite another. Teams help each other, and clean up after each other. They follow the Boy Scout rule because it's good for everyone, not just good for themselves.9. Check Your Code First before Looking to Blame Others by Allan Kelly
Developers — all of us! — often have trouble believing our own code is broken. It is just so improbable that, for once, it must be the compiler that's broken.
Yet in truth it is very (very) unusual that code is broken by a bug in the compiler, interpreter, OS, app server, database, memory manager, or any other piece of system software. Yes, these bugs exist, but they are far less common than we might like to believe.
I once had a genuine problem with a compiler bug optimizing away a loop variable, but I have imagined my compiler or OS had a bug many more times. I have wasted a lot of my time, support time, and management time in the process only to feel a little foolish each time it turned out to be my mistake after all.
Assuming the tools are widely used, mature, and employed in various technology stacks, there is little reason to doubt the quality. Of course, if the tool is an early release, or used by only a few people worldwide, or a piece of seldom downloaded, version 0.1, Open Source Software, there may be good reason to suspect the software. (Equally, an alpha version of commercial software might be suspect.)
Given how rare compiler bugs are, you are far better putting your time and energy into finding the error in your code than proving the compiler is wrong. All the usual debugging advice applies, so isolate the problem, stub out calls, surround it with tests; check calling conventions, shared libraries, and version numbers; explain it to someone else; look out for stack corruption and variable type mismatches; try the code on different machines and different build configurations, such as debug and release.
Question your own assumptions and the assumptions of others. Tools from different vendors might have different assumptions built into them — so too might different tools from the same vendor.
When someone else is reporting a problem you cannot duplicate, go and see what they are doing. They maybe doing something you never thought of or are doing something in a different order.
As a personal rule if I have a bug I can't pin down, and I'm starting to think it's the compiler, then it's time to look for stack corruption. This is especially true if adding trace code makes the problem move around.
Multi-threaded problems are another source of bugs to turn hair gray and induce screaming at the machine. All the recommendations to favor simple code are multiplied when a system is multi-threaded. Debugging and unit tests cannot be relied on to find such bugs with any consistency, so simplicity of design is paramount.
So before you rush to blame the compiler, remember Sherlock Holmes' advice, "Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth," and prefer it to Dirk Gently's, "Once you eliminate the improbable, whatever remains, no matter how impossible, must be the truth."
The 'episodes' #10, #11, #12 come in the next posting :)