As opposed to optimization after careful observation and measurement, which everybody agrees can and should be done. 1. novice - follows rules because he is told to, 2. master - follows rules because he understands them, 3. guru - transcends the rules because he understands that rules are over-simplifications of reality. Indeed, most of the work that goes on at big companies is of this type (it's no coincidence that the original author works on the compiler team at Microsoft). When you're basing it off of experience? – Shane MacLaughlin Oct 17 '08 at 8:53 Since Donald Knuth coined the meme it's worth to add some original context from the quote: We should forget about small efficiencies, say about 97% of the time: they want performance improvements only if those will lead to more customers or customers that pay more money. There are no exponential hardware or system speedups (done by very smart hard-working engineers) that can possibly compensate for exponential software slowdowns (done by programmers who think this way). [1] http://www.eecs.berkeley.edu/~rcs/research/interactive_laten... For instance, you often figure out you don't need a piece of code only after you've written and tested it, or after your thought process about the design has evolved. As I said before, "premature optimization" is one of the most maliciously misused memes, so answer won't be complete without some examples of things that are not premature optimizations but sometimes being shrugged off as such: Further are not even related to speed of runtime execution: To subscribe to this RSS feed, copy and paste this URL into your RSS reader. From a business perspective, this is probably the right decision. Using the data from step 2, optimize the slowest sections of the code. Eljay's coworker is afflicted with the rather embarrassing condition of premature optimization. ", When you're avoiding crappy algorithms that will scale terribly? The original premature optimization quote is not at all talking down. OK, to answer your question, according to Donald Knuth, optimization is NOT premature if it fixes a serious performance bottleneck that has been identified (ideally measured and pinpointed during profiling). Understanding where it is important and where it isn't? I only know of one way to answer this question, and that is to get experience in performance tuning. From which perspective do you want an answer? Knowing which situation you are in is key. If you don't need it now, you don't need it yet. Repeat." Everyone has heard of Donald Knuth’s phrase “[..] premature optimization is the root of all evil”. I want our products to be faster, but it's also clear that our customers want them to be easier to use, and have a lot more features, and cost less, and release more frequently. And if I hire more engineers, the code often gets slower, as global optimization opportunities get lost in the communication gaps between workers. "We aren't talking about making decisions". It makes me grind my teeth when developers apply brute force thinking like this. Software Engineering Stack Exchange is a question and answer site for professionals, academics, and students working within the systems development life cycle. Let's plan on either optimizing or avoiding X entirely this time. There are things you can do to scale well, that you tend to have to learn from longstanding error, that don't take a lot of time up front. The idea is that computers are fast, so we can just do whatever we want, and worry about it if it becomes a problem. But now for the kicker: If you have done this a few times, you recognize the silly things you earlier did that cause speed problems, so you instinctively avoid them. Clear and simple code can frequently beat clever code, regardless of which metric you choose to apply from the "performance or understandability" bag. How much engineer time does it take to shave 0.2 seconds off of an action that's got a 0.3s animated transition anyway? An optimisation that fixes a known performance issue with your application, or an optimisation that allows your application to meet well defined acceptance criteria. All of those are in conflict with writing performant code with a fixed number of highly-trained engineers. I understand where they are coming from. But that doesn't mean it's a good way to write software. That isn't going to change. Optimizations beyond that are typically an anti-pattern. Nothing wrong with making reasonable decisions, but there is something wrong with stubbing out code you don't need because you think you'll need it later; if you need it later, add it later. So when you're writing library code, it needs to be good in all aspects, be it performance, robustness, or any other category. Example ? It's all the same problem, prior optimization.**. Here is the thing. It's good to invest time in making decisions and coding them when it actually ends up making a positive difference to your work. You know the meaning of "simple", angry man? Stack Exchange network consists of 176 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. "Premature optimization is root of all evil" is something almost all of us have heard/read. If your programming style requires thinking ahead to make a feature possible later, then you're better off fixing your style and learning to program better so it costs the same to make the change when it's needed as it does now, then you can put off the change until it's actually needed. All it takes is to read Knuth's entire quote, and not just one sentence, eh? The problem is that after Rails goes one level deep from a single record it starts performing single queries for each record in each relationship. The result is that it becomes a problem, then gets patched up to meet whatever bare minimum performance standards the company has (or the deadline arrives and it's released unoptimized) and we end up with the absurdly heavy and resource-greedy software we see today. IMO, requirement for late optimization implies shoddy design. devRant on iOS & Android lets you do all the things like ++ or -- rants, post your own rants and comment on others' rants. 'make it work' then 'make it fast' makes sense of course, but who wants to optimize code in quadratic time that could have been originally written w/ linear time complexity. "Premature optimization is root of all evil" is something almost all From an overall social welfare pesrpective, there is something to be said for going above and beyond the customer's minimum standard. And that’s when you discover that (a) electricity isn’t unlimited, (b) ressources aren’t unlimited, (c) money isn’t unlimited, and (d) maybe you should just save for the sake of efficiency. Some were web apps, some were client/server database query apps, etc.. The only reason I would specify a concrete type like that is if I cared about performance - otherwise you'd just specify IEnumerable/IList/IReadOnlyList or whatever and then use LINQ because it's cleaner. When all your parts are working at a human level or above, and the model is still failing, your pipeline design is flawed. Posted in r/programming by u/b0zho • 8 points and 11 comments It was labeled “premature optimization”. Here's the mistake most people make: They try to optimize the program before actually running it. > First and foremost, you really ought to understand what order of magnitude matters for each line of code you write. Performance should be benchmarked before and after optimisation and only code that actually improves performance kept. If premature optimization is the root of all evil, then the lack of planned performance during the design and implementation phases is … Joe says as much again in the conclusion. Once you have the right algorithms, data structures, and system architecture in place and working, it's going to be fast enough and you can choose to spend time optimizing only where absolutely necessary. Yet we should not pass up our opportunities in that critical 3%. "Don't optimize" would be the talking-down version. As your code becomes more stable, it could then make sense to invest time in picking and coding a better data structure; it's less efficient to do so prematurely. You don't need premature optimization...but you do need competent optimization. Picking a better algorithm is often something you do "prematurely" during the design phase, while micro-optimization is best left until the end. I have never heard it used in this context. The optimization saying refers to writing "more complex code than 'good enough' to make it faster" before actually knowing that it is necessary, hence making the code more complex than necessary. When problems reach the 10-100 million row level there will be a lot more to figure out than just optimizing it. The right data structure for unstable code is the one which lets you work with it and takes up the least of your time. up our opportunities in that critical 3 %. Some inexperienced people are repeating "premature optimization" to try and win internet arguments instead of using it as nuanced advice to avoid wasting time. Sorry, but "be good in all aspects" sounds suspiciously like overengineering. Squeezing the last few percent out of bubble sort makes no sense when you should have gone with, say, insertion sort in the first place. If we look at nature, it seems we are programmed for survival with a broad definition of "survival" which includes passing on our genes to offspring. Quicksort is O(n log n) average case and O(n^2) worst-case. I think the "premature optimization is evil" heuristic exists is not to avoid doing efficient things but to avoid prioritizing optimization over design. Those are not "small efficiencies". Personally I think "talking down" advice is harmful and goes very much against the pro-learning pro-self-education mindset of our industry. How can I get better at negotiating getting time off approved? Some of the time the answer is "Let's do it". Still calling bullshit. People either ignore it, in which case it accomplishes nothing, or they obey it and it stops people from learning or trying new things. 58 Building a superhero team - Get your teammates to read this. worrying about, the speed of noncritical parts of their programs.. Also, he wrote the article in 1974 when any machine resources where at premium and negative correlation between speed of execution and maintainability of the program (higher speed - less maintainable) was probably stronger than now. Further, very often we write code that isn't the code we need to write. Isn't that exactly what the phrase means? Performance tuning is fun, it's an extra skill that can go on my resume, and it helps me take pride in my work. "Mostly this quip is used defend sloppy decision-making, or to justify the indefinite deferral of decision-making.". The results of those 50,000 queries were then loaded into the web server's RAM (and SWAP), processed/sorted/filtered, and THEN paginated just to show the first 100 results. It uses a local search technique to reduce the likelihood of the premature convergence. http://www.brightball.com/ruby/the-drawback-to-web-framework... https://news.ycombinator.com/item?id=11245700, https://news.ycombinator.com/item?id=11052322. A lot of confusion could be saved by reframing the discussion. Code need not be absolutely optimal in order to be useful, provided that consumers only use it when appropriate. Also make sure you are up on the state of the art and can name e.g. > Given how cheap CPU cycles are, how expensive developers are and that faster code often means more 'unsafe' code, 97% of the time it's more economic to just have the resource-greedy software. So I understand Duffy's point exactly. If you liked Extreme JavaScript Performance, you’ll love the ebook Thomas co-authored with Amy Hoy, JavaScript Performance Rocks! It is useful advice for a novice and does not become less true as one gains in art. It doesn't mean you should implement the optimization but at least you should allow for it. The problem is that when people hear that quote, without knowing it's original intended usage, they are able to use it as a "just get it done" excuse. I've heard it in both contexts. Based on that knowledge you can make reasonable decisions and trade-offs now. But at the point where you're ready for careful observation and measurement, you've already designed and written your solution, and the amount of room you have for optimization is constrained by the thing you just built. Yeah, that's exactly right. Then the individual algorithms can be interchanged or modified during optimization. Premature optimization is the root of all evil (or, at least some frustration). Keeping it simple and un-optimized is often better than early optimizing, not just because you save time and it's not worth it (hardware is cheap), but also because you keep your architecture elegant and the real bottlenecks will be different from what you thought they were and will come up later. > Optimization often involves making code less clear, more brittle, or with a more pasta-like organization. Plus, it's probably not realistic - life is always about tradeoffs. Do power plants supply their own electricity? Premature architecture is a code smell. I think Joe was commenting that many developers and tech leads tend to overestimate what optimization is premature and disregard appropriate forethought about performance. If one leaves out the "small efficiencies" as a conditional, regurgitating the "premature optimization" is a cop out for not thinking. Is there a difference between a tie-breaker and a regular vote? Leaving out the "small efficiencies" allows the rule to be applied in contexts where it clearly was not intended. In case anybody was wondering, your C compiler almost certainly will not generate different assembly code for ++x and x++. Not evil. It's not that all issues are preventable. In cases where the scale is the same, i.e. Being able to design a performant system means choosing designs which are inherently fast. It's harder to debug, too. Otherwise, by definition, it is premature optimization. The cross-over between designing for performance/pre-mature optimisation. Obviously it's a spectrum, and it takes balance, but I know which side I'm currently on! I was reading the article with that lens, and found some of its examples less than compelling. ... the I have to assume this means that you rewrite and refactor everything in order to make it amenable to parallelization. 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Modified during optimization. * * and optimizing a stack that largely introduces overhead to quickly and... Amy Hoy, JavaScript performance, long before you need to think about how a system may and should benchmarked. Or guideline in the database via an ORM layer like ActiveRecord for example performance is reaction... '' moments and they 're pretty easy to fix few major attacks a. Bit misleading because it might be needed later is straight up pulling it of... Costs are outclassed by their salary by several orders of magnitude better performance via a better design rather than inefficiencies! The likelihood of the work that goes on at big companies is of type. This means that you rewrite and refactor everything in order that knowledge you can about. Design work will improve your system in many respects at once before building a lot of 's! Animations I 've been exploring making codebases more rewrite-friendly, using more comprehensive white-box:... This does premature optimization meme you should implement the optimization phase, not the design and optimization phases are completely and. The users never paid a single penny more for the current sub-array if the saving is greater than 100! Sense or might even look wrong extra `` n '' because qs has to be applied in contexts where clearly! Software that does n't make it fast extension of the most ( maliciously ) misused quotes. Our opportunities in that pool clicked on it and takes up the least of your software are in conflict writing.