The single most important quality in a piece of software is simplicity. It’s more important than doing the task you set out to achieve. It’s more important than performance. The reason is straightforward: if your solution is not simple, it will not be correct or fast.
Given enough time, you’ll find that all software which solves sufficiently complex problems is going to (1) have bugs and (2) have performance problems. Software with bugs is incorrect. Software with performance problems is not fast. We will face this fact as surely as we will face death and taxes, and we should prepare ourselves accordingly. Let’s consider correctness first.
Complicated software breaks. Simple software is more easily understood and far less prone to breaking: there are less moving pieces, less lines of code to keep in your head, and fewer edge cases. Simple software is more easily tested as well - after all, fewer code paths to run through. Sure, simple software does break, and when it does the cause and appropriate solution are often apparent.
Now let’s consider performance. You may have some suspicions about your bottlenecks when you set out, and you should consider them in your approach. However, when the performance bill comes due, you’re more likely to have overlooked something than not. The only way to find out for sure what’s slow is to measure. Which is easier to profile: a complicated program, or a simple one? Anyone who’s looked at a big enough flame graph knows exactly what I’m talking about.
Perhaps complicated software once solved a problem. That software needs to be maintained - what is performant and correct today will not be tomorrow. The workload will increase, or the requirements will change. Software is a living thing! When you’re stressed out at 2 AM on Tuesday morning because the server shat itself because your 1,831st new customer pushed the billing system over the edge, do you think you’re well equipped to find the problem in a complex piece of code you last saw a year ago?
When you are faced with these problems, you must seek out the simplest way they can be solved. This may be difficult to do: perhaps the problem is too large, or perhaps you were actually considering the solution before considering the problem. Though difficult it may be, it is your most important job. You need to take problems apart, identify smaller problems within them and ruthlessly remove scope until you find the basic problem you can apply a basic solution to. The complex problem comes later, and it’ll be better served by the composition of simple solutions than with the application of a complex solution.
Articles from blogs I follow around the net
We are excited to launch the new Go official swag and merch store shipping worldwide. We are even more excited to announce that 100% of the proceeds from the Go store go directly to GoBridge. GoBridge is a non-profit organization focused on building bridges…via The Go Programming Language Blog July 18, 2019
This is a psuedo-transcript for a talk given at Deconstruct 2019. To make this accessible for people on slow connections as well as people using screen readers, the slides have been replaced by in-line text (the talk has ~120 slides; at an average of 20 k…via Dan Luu July 12, 2019
This post gives an overview of the recent updates to the Writing an OS in Rust blog and the used libraries and tools. My focus this month was to finish the Heap Allocation post, on which I had been working since March. I originally wanted to include a sect…via Writing an OS in Rust July 6, 2019
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