Related
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 5 years ago.
Improve this question
I'm still relatively a beginner in TDD, and I often end up into the trap where I've designed myself into a corner at some point when trying to add a new piece of functionality.
Mostly it means that the API that grew out of the, say, first 10 requirements, doesn't scale when adding the next requirement, and I realize I have to do a big redesign on the existing functionality, including the structure, to add something the new stuff in a nice way.
This is fine, except in this case the API would then change, so all the initial tests would then have to change. This is usually a bigger thing than just renaming methods.
I guess my question is twofold: How should I have avoided getting into this position in the first place, and given that I get into it, what are safe patterns of refactoring the tests and allowing new functionality with a new API to grow?
Edit: Lots of great answers, will experiment will several techniques. Marked as solution the answer I felt was most helpful.
How should I have avoided getting into this position in the first place
The most general rule is: write tests with such refactorings in mind. In particular:
The tests should use helper methods whenever they construct anything API-specific (i.e. example objects.) This way you have only one place to change if the construction changes (e.g. after adding mandatory fields to the constructed object)
Same goes for checking the output of the API
Tests should be constructed as "diff from default", with the default provided by the above. For example if your test checks the effect of a method on field x, you should only set the x field in the test, with the rest of the fields taken from the default.
In fact, these are the same rules that apply to code in general.
what are safe patterns of refactoring the tests and allowing new functionality with a new API to grow?
Whenever you find out that an API change makes you change the tests in multiple places, try to figure out how to move the code into a single place. This follows from the above.
Make your tests small. A good test calls maybe 1-3 methods on the subject of the test and does some assertions on the result. These test will only need to change when one of these three methods change.
Make your test code clean. If you haven't already read 'Clean Code' by Robert C. Martin. Apply the rules to your production code AND your test code. This has the tendency to reduce the affected surface area of any refactoring.
Do refactor more often. Instead of (possibly unconsiously) waiting until you must do a large refactoring, do small refactorings a lot.
If you are faced with a huge refactoring, break it down in a couple (or if necessary a couple hundred) tiny refactorings.
In this case, I suggest you get the features locked down, and the iterations short.
Because the iterations are short, features will be grouped together into smaller, isolated groups. It lessens the need to think up of some grand design, which might not be adaptive to the needs of the users. The code for this week, will only work with the code for this week. That lessens the chances of new stuff mucking up the old stuff.
Yeah, it's a problem that is hard to avoid with TDD, since the whole idea behind it is to avoid the over-engineering caused by doing big designs upfront. So with TDD, your design is going to change, and often. The more tests you have, the more effort is required for each refactoring, which effectively discourage it, going against the whole idea behind TDD.
Even though your design will change, your basic requirements will be rather stable, so at the "high level", the way your app works shouldn't change too much. That's why I advise to put all your tests at the "high level" (integration testing, kinda). Low level tests are a liability because you have to change them when you refactor. High level testing is a bit more work, but I think it's worth it in the end.
I wrote an article about that a year ago: http://www.hardcoded.net/articles/high-level-testing.htm
The following might help..
Follow good coding standards and practices, including TDD and utilising design patterns to produce well structured designs. The application as a whole should then be easier to extend to include new features.
Good separation of concerns. If your API is well separated from the other functionality (calculations, database access etc) then changing the functionality without changing the API or vice-versa should be easier.
Use BDD to provide automated tests at a higher level (ie. more like user tests than unit tests). These should help to give you confidence while refactoring even if all your unit tests are breaking due to the refactoring.
Use a Dependency Injection Container such as Windsor. By abstracting away your class dependencies when those dependencies change it creates much less re-work (particularly if you have many unit tests) than having them coded into your classes.
You shouldn't find yourself "in a corner" with TDD. The eleventh test shouldn't so seriously change the design that the first ten tests need to change. Think hard about why so many tests need to change - look at it in detail, one by one - and see if you can come up with a way to make the change without breaking your existing tests.
If, for instance, you need to add a parameter to a method that they all call:
you could leave the existing fewer-parameter method in place, delegating to the new method and adding a default parameter;
you could have all the tests call a utility method (or perhaps a setup method) that calls the old method, so you need to change the method call in only one place;
you may be able to let your IDE do all the changes with a single command.
TDD and Refactoring work symbiotically; each helps the other. Because you emerge from TDD with comprehensive unit tests, refactoring is safe; because you have the organizational, intellectual, and editing tools to refactor freely, you can keep your tests well synchronized with your design. You say you are a beginner at TDD; perhaps you need to be growing your refactoring skills while you learn TDD.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 9 years ago.
Improve this question
I understand that this question could be answered with a simple sentence and that it may be viewed as subjective, however, I am a young student who is interested in pursuing a career in programming and wondered how long it took some of you to get to the level of experience you are now?.
I ask this because I am currently working on building an application in Java on the Android platform and it bothers me that I am constantly having to look up how to write a certain section of code in my application such as writing to a database, or how the if statement should be structured.
My question really is, how long did it take for you to become experienced enough to actually know exactly how your next line of code was going to look, before you even wrote it?
The speed at which you can quickly recall language syntax, common library functions, and best practice patterns is directly proportional to the amount of time you spend using them.
In other words you will find yourself getting faster the more you do it.
I have been a C++ programmer for the last 20 years. It has taken me that long to get to this expertise level. I'm mostly a Windows programmer, and I keep the msdn website up on one of my monitors all the time.
Doesn't matter how long you've been doing it. You will never know everything from memory. Don't sweat it.
I've been programing for almost half of my life and I sill can't always recall simple syntax, let alone entire tracks of code for more complex tasks. If you ask me that's what reference books and Google are for.
A far more important skill to have is the general knowledge of programming in any language, i.e. recursion, looping, object oriented design, working with APIs, error handling etc... Once you have all that down, you can apply it to any language and platform.
I can tell you that after 25 years there are lines of code that I don't know how they're exactly going to look like.
Want an example? I'm programming in Java since last century and I can honestly still make a mistake if I were to type hashcode() or hashCode().
Why? Because actually typing such a method name yourself is so last century. Your intention is to override Object's hashCode() method, so you use programming by intention.
You hit Ctrl-O then h and you get a list of the methods starting with an 'h' that you can override. Then you hit enter. As a bonus, the "#Override" gets inserted for you too.
4 keys. 4, to get this:
#Override
public int hashCode() {
}
And honestly, whether hashCode takes an uppercase 'c' or not... I couldn't care less. This is not what an hashcode is about and my intention is not to know all the inconsistencies languages and API designers came up with. My intention is to override the method that gives back an object's hashcode and my (modern) IDE allows me to get that skeleton in four keypresses, including hitting enter.
Another example: there are people who do really type this countless times a day:
for (int i = 0; i < ; i++) {
}
or the more tricky:
for (int i = ; i >= 0; i--) {
}
Note in that latter case I can still mess up and type "i++" instead of "i--" (a 'thinko' as its called).
But I don't care at all, because I type "fi<tab>" (three keys) and I get the first one or "fir<tab>" (four keys, "for i (in) reverse") and I get the second one. You ain't beating that (especially seen that I'm a touch typist so I type these three or four keys fast). In addition to speed, as an added bonus the autocompletion won't mess you "i--".
In many case I don't know exactly the line I'll get: sure, I know it "more or less" and that's exactly the way it should be.
Don't sweat it too much. As others have mentioned it eventually gets easier to write code without looking things up so much as you work with a particular language over time.
HOWEVER
There are a few reasons that even veteran programmers find themselves constantly using reference material:
(1) Unlike days of yore, most projects now require you to use a number of languages to get the job done. For example single web site-project a web-site may require C#, XML, JavaScript, SQL, HTML, XHTML, RegEx and CSS all in the same project. Switching between some of these languages can really throw you for a loop sometimes because many of them are just similar enough to be familiar, but just different enough to make you forget the subtle differences in syntax.
(2) Just when you start getting comfortable that you know a language inside and out, the vendor will release a new update that changes everything you knew about it. For example ASP->ASP.NET.
I still look up simple things fairly frequently and I've been at this almost 20 years. The important thing is that you understand the underlying concepts and principles.
It took me 12 years to get where I am at today, which is my experience in professional programming. You will always improve when working with some programming language, even if you have been working with it for the past 5 years.
About your question, it depends. I think that you should be comfortable with the syntax after a week, comfortable with the main libraries after a month, and comfortable with the platform after 6 months.
But when you get there, don't stop!
If you code every day with the same language, you'll probably have the common language elements and patterns memorized in a month or two. But there are plenty of things that you'll probably never memorize, simply because you don't use them often enough, and also because modern IDE's can help you so much that you don't really need to remember everything if you utilize all their features (like code snippets, shortcuts, intellisense).
I've been coding for 15 years, and doing C# for the last three, and I still use the MSDN reference material every day. However, as far as the basic building blocks of the language are concerned, I had them memorized in the first month or two.
Also, the more often you code, the better you'll commit it to memory.
There's a false assumption going on here I think...
At my job I end up working all over the stack in different languages and platforms. If I'm away from a project for 6 months I end up having to look at code to get even basic things done. The advantage of experience is reducing the re-ramp up time on productivity though.
So, instead of it taking weeks or months to get back to a point where I can write 80% of the code from memory it takes a few or several days (if that sometimes). I've been programming for about 5 years now. I'm just now getting to the point of being able to visualize small applications in their entirety.
As long as you're working on solving a problem that you haven't already solved (numerous times) you'll probably always have to look up code.
If it can be done I'm guessing it takes longer than 5 years for most people, unless they work in one language with one editor and in one area. (ex: C#, Visual Studio, file system operations) My company isn't big enough to employee someone that specific.
Don't be downhearted by having to consult documentation all the time man, that's what it's there for. Over time you get used to syntax and things like that but don't sweat it if you can't remember library methods or ways to connect to a DB.
Over time (with experience) you might remember these off the top of your head but in reality there's nothing wrong with taking a quick consultation of the documentation to refresh the memory.
Also remember that technology is ever changing so it's good to keep the mind fresh with new ways of thinking/ways to do things.
Question is not 100% clear. One of the best programmers I know doesn't remember anything and needs to look up printf formatting strings almost daily. On the other hand if you are having hard time figuring out how to write that for (int i = 0; i < len; i++) loop after doing this for 6 months -- that doesn't sound right.
the idea that one could every bit of code from even a single language and then type plainly from memory is pretty far out. the amount of pre-defined functions for, say PHP or Java alone is immense.
but that being said, its important to learn the programming structures, and know them the best you can. structures like foreach, if then else, switch, etc. are really the things that need to be integrated thoroughly. also, conceptual things like Object Orientation (not just "using" objects like mysqli, but understanding things like controlling code, client code, bottom-up and top-down architecture) are the real things that make good programmers great. for myself, i know that i have not the capacity to learn every defined function thats provided by language writers so i instead learn whether or not it can be done(and of course still try on occasion to do things that cant be done, lol). if you know that, then its a matter of google and books to find the "specific" mechanisms on how.
cheers my friend.
Not an answer per se, but I just wanted to say that as a novice myself, this q&a is one of the most useful things I've read on SO. It seems that yes, experts can probably code the basic stuff from memory, but even they revert to book for complex problems, and for beginners, that's what the book is for.
I feel like I'm just beginning
You should use code snippet if you are using certain piece of code repeatedly. I doesn't bother me if I cannot remember some piece of code from memory.
For me, it depends heavily on what I'm writing. For example, I doubt that most people ever quite memorize all the parameters to some Windows functions. I may know that I need to call CreateFile on the next line, but don't know all the parameters in order until they're typed in (with help from Intellisense, and sometimes MSDN).
With something that's doing simple computation, I'm a lot more likely to be limited by my typing speed (but I'm a fairly poor typist, so thinking faster than I can type doesn't take much).
That means it's really a question of how much of the time you need to refer to something to type the next line of code -- at first, it's a pretty small percentage, and over time it grows. I doubt it ever gets to 100% for anybody though. I, for one, don't think I'd want it to -- that would indicate I wasn't working on new and different things...
If you use eclipse and java, you may find yourself already there.
Other combinations may be a little slower to a lot slower.
Java has the advantage that it's pretty easy for the environment to build an entire parse tree while you are typing. At any place in your code, typing ctrl-space can give you an entire list of valid options.
Also syntax errors are always underlined.
If you want to go hard core though, I started in C before the day of decent editors and it took me about a year before I typed in more than a few lines and didn't get a compile error.
I don't know about memorization. Repetition is mother of all learning and that applies to all aspects of life. Look at the experienced accountant vs. the novice when filing taxes, who looks up stuff more. But what I did discover recently is that I navigate documentations much quicker and have a sense for going directly to where my question is answered. I got 6h sense - I can see the code! Seriously, it all comes with experience. Still, when learning something completely new, there's no shame in looking up how to do certain things. That's what separates humans right, learning from others. The more you work on something, the better you become.
There is absolutely nothing wrong with having to lookup the documentation every time you want to write some code. I got lucky in that once I use a certain function, I don't forget it very easily. However, most of the time, especially when I'm coding in a language that I haven't used in a while,
I start out by writing a flowchart of the algorithm that I want to code - just the pure logic. The most important reason for doing this is so that I don't lose my train of thought and forget the algorithm that solves my problem in the midst of technical problems like syntax and < what library functions exist? >
Then I look at the documentation and check to see if there are simple function calls that will help me accomplish each task in my algorithm
If such functions do not exist, then I either modify my algorithm to accommodate for what functions the language does provide or write helper functions do fill in the gaps.
I only start coding NOW, which is not too difficult to do anymore, because I already have all the relevant functions written down. So now it's just a question of translating pure logic into syntactically accurate code.
Proper syntax usually does not elude me, but if that does happen (VERY rare), Google provides very nice code snippets if you ask nicely.
Hope this helps
May the Force be with you
I'm programming Java now for about 5 years, and I never have had any trouble remembering syntax. I can <brag>write almost all java.util.*, java.io.*, java.lang.* and javax.swing.* stuff out of my memory</brag>, but does it help me? Not very much. It doesn't make me a better programmer than someone who can't!
I'm using Netbeans, which greatly helps working with libraries. Also, the documentation, just in the place where you need it. Sometimes, it's quite unnecessary, but sometimes you'd wish the "auto complete" screen would popup faster!
The best thing as a student is to concentrate on what you are doing, not how fast you are doing it. Looking up things isn't bad; as it'll help your so-called "unconsciousness mind" process what you are really trying to accomplish. Having such breaks, e.g. by looking up a certain documentation or syntax reference, may even let you be better at programming (no proof for this, though).
Question is quite subjective.
With the great many IDE's available and the "newbie" tutorials on getting started, it won't take you long before you're off writing your own apps.
That said, unless you have a "thirst" for how stuff works kinda attitude all the time towards everything, you won't go far. In this field, you really have to have a passion for what you do to be great.
... It bothers me that I am continually having to look things up... How long did it take you to get to the level where you are now?
For me, and for most of the students I teach, the answer depends on two variables:
How many lines of code have I written?
Do I use the language or library every day?
(Reading other people's code is very helpful for learning a language and learning how to think in a language, but for me at least, it hasn't helped me become a fluent writer of programs in a language. Only writing code does that.) So my first comment is that time should be measured in lines of code written, not hours or years.
(Ray Bradbury once advised aspiring writers of fiction to write a thousand words a day six days a week, and after they've written a million words they might start to know something about their craft. This is good advice for programmers too.)
As for my own experience, across a half dozen languages that I currently know well or once knew well, it's been pretty consistent for me that
After writing 100 lines I am continually looking things up in the manual and don't really know what I am doing.
After writing 1,000 lines I use the manual occasionally and am starting to learn how to think in the language.
After writing 10,000 lines I am about as good as I'm going to get without making special efforts.
After writing 25,000 lines I probably will not need the manual again.
It's also true that
To learn to write 100 lines I had to read 100 to 1,000 lines that someone else wrote.
For the first 1,000 lines I write it is good for me to read 2,000 lines someone else wrote. For the next 1,000 lines it is good for me to read 1,000 lines someone else wrote.
After I've written 5,000 lines I learn the most by reading code written by world experts or by people who designed the language and understand what is there. I no longer have much to learn by reading just any program.
On the other hand, my experience about when I stop having to refer continually to the documentation is much less consistent.
I find it especially hard when two languages are very similar; I will never stop needing the ksh manual to tell me what is different from sh or bash, and I will never stop needing the Haskell manual to tell me what is different from Standard ML (though the need grows less with each additional 1,000 lines of Haskell that I write). I also find it interesting that while I have written over 35,000 lines of Lua code, and I will never need the manual again for a language question, I have to look up libraries and API functions almost every time I write something longer than 500 lines. (I've written a lot of short Lua programs and a couple of long ones, and I don't use the language every day, although I definitely use it at least several days each month.)
As for the unspoken question, when are you personally going to get better?, take some advice from Watts Humphrey: measure your own performance and track it over time. I think if each day you count the number of times you had to stop and look things up, and graph that against number of lines of code written or edited (which you can get from source-code control), you will be pleasantly surprised by objective evidence of improvement. And I think once you have such evidence, you will be able to focus more on continuing to improve, and not so much on where you are now or where you hope to be in a year.
It's true that after some years of programming you'll be able to remember a lot of thing without having to check the "manual". For me this is not an important milestone in your programming life though, the really important moment is when you reach the point where you don't know how to do something... but you're sure that can be done and you know where and how to research about it :-)
You made a very important step participating on this site. Exchanging ideas and helping each other it's a excellent way of learning.
Sociologist Malcolm Gladwell believes that ten thousand hours is a good benchmark for the amount of practice required to become world class at many fields of endeavour. I think that sort of number applies to programming as well. This isn't quite what you asked, though; being able to code competently certainly requires familiarity with your environment (language constructs, system libraries, third party libraries and perhaps something of the concepts underpinning them), but there are many soft skills involved which are harder to describe and can only really be acquired through practice.
As others have said, being good at programming is not about typing code from memory; it's about recognising patterns, understanding systems, solving problems. It's about choosing the right tools for the job (languages, libraries, algorithms, whatever) and being able to make proper use of them.
In all the jobs I've had, it's about adaptibility and flexibility; you might have to learn a new language or pick up somebody else's poorly documented code tomorrow, and a good programmer will be able to take this in their stride.
I've been coding professionally for nearly 10 years now; there's all sorts of code I use semi-regularly which I look up the options for at least some of the time. There are too many commands with too many options in too many languages for me to remember each and every last one in detail and Google is quite good enough at getting the information I want.
That said - there are some bits of routine code which I use all the time but can count on one hand the number of times I've written - the exact syntax for populating a dataset in .Net for example. One of the skills I've most come to value over this time and which saves me the most time is spotting when some code can be quickly and easily moved into utility libraries. If it's fiddly but routine, consider this approach to save yourself hassle and improve your overall code quality.
In the context of this question ; java, c++, javascript the languages are still evolving. I can't say about other languages.
The language standard/specification changes over time
Libraries are added to supplement the language constructs e.g Boost, Google Collections, Apache Commons, jQuery
Applications will rarely be bound to a single aspect of a language
Across organizations/projects, coding standards change
A project I worked upon recommended against using primitives
When unfamiliar with the constructs used, I put in pseudo-code flagged with //TODO first .. then go in and find the actual API to use.
IMO, the answer to your question is - there is no definite answer.
As a Java programmer the sheer size of the runtime library makes it impossible to remember everything. Swing is big, there is an XSLT engine (which contains TWO languages), the Concurrent support evolves and grows.
The direct access to the Javadoc API from within Eclipse combined with code completion makes it possible to find the information you cannot remember but you know is there, quickly and efficiently.
I have found the javaalmanac.com (which has been reworked into the more convoluted http://www.exampledepot.com/egs/index.html) invaluable in presenting short, concise and above all correct programs doing just one small thing. Strongly recommended.
Most weeks I program in Java, C#, Python, PHP, JavaScript, SQL, Smarty, Django Templating and occasionally C++ and Objective C. I'm a student so this is partially school work and partially my part-time job. Instead of learning syntax I've learned what concepts to look for.
Seeing patterns and concepts is key, once you know the concepts and what to look for the syntax is secondary.
I find that even when I am just being exposed to a language I can accomplish a lot just by looking for 'what ought to be there'
Why should you be able to remember all of this stuff? Personally I embrace the fact that I can't remember all of this stuff and simply try and remember where to find the information that I need. I find that much more useful. This takes the form of blogging, taking notes, keeping large amounts of 'sample' code and reusable libraries and writing about code that I find useful and interesting; oh and lots of books, some of which I hardly ever 'need' and some of which I hardly ever really read but they've been skimmed and I know where they live.
Technologies come and go and there's just no way I could have kept all of the things that I may one day find useful in my head; so I page them out and just keep the index in memory... For example; 9 years ago I was doing some stuff with Java and CORBA and whatever. There's no way that I could drop back into that now without the notes that I wrote up for my website back when I was doing it: http://www.lenholgate.com/blog/2001/02/corba---enumeration.html. Likewise I have code that I use on a daily basis that has been kicking around since 1997 or earlier. I don't remember how to type it in, I have it in a file with tests (if I'm lucky) and docs (if I'm even luckier).
Whilst I realise that most of what I'm talking about is 'big stuff' I also often have to go and look at some of my old code to simply work out how to structure a typedef...
Of course the day to day stuff will come with time and practice; but you need to work out that you have to page some of it out in a form that you can reload later very quickly. Embrace the fact that your memory is never going to be able to hold it all and outsource it :)
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 7 years ago.
Improve this question
When writing a mathematical proof, one goal is to continue compressing the proof. The proof gets more elegant but not necessarily more readable. Compression translates to better understanding, as you weed out unnecessary characters and verbosity.
I often hear developers say you should make your code foot print as small as possible. This can very quickly yield unreadable code. In mathematics, it isn't such an issue since the exercise is purely academic. However, in production code where time is money, having people try to figure out what some very concise code is doing doesn't seem to make much sense. For a little more verbose code, you get readability and savings.
At what point do you stop compressing software code?
I try to reach a level of verbosity where my program statements read like a sentence any programmer could understand. This does mean heavily refactoring my code such that it's all short pieces of a story, so each action would be described in a separate method (an even further level might be to another class).
Meaning I would not reduce my number of characters just because it can be expressed in fewer. That's what code-golf competitions are for.
My rule is say what you mean. One common way I see people go wrong is "strength reduction." Basically, they replace the concept they are thinking with something that seems to skip steps. Unfortunately, they are leaving concepts out of their code, making it harder to read.
For example, changing
for (int i = 0; i < n; i++)
foo[i] = ...
to
int * p = foo, q = foo+n;
while ( *p++ = ... < q );
is an example of a strength reduction that seems to save steps, but it leaves out the fact that foo is an array, making it harder to read.
Another common one is using bool instead of an enum.
enum {
MouseDown,
MouseUp
};
Having this be
bool IsMouseDown;
leaves out the fact that this is a state machine, making the code harder to maintain.
So my rule of thumb would be, in your implementation, don't dig down to a lower level than the concepts you are trying to express.
You can make code smaller by seeing redundancy and eliminating it, or by being clever. Do the former and not the latter.
Here's a good article by Steve McConnell - Best Practices http://www.stevemcconnell.com/ieeesoftware/bp06.htm
I think short/concise are two results from well written code. There are many aspects to make code good and many results from well written code, realize the two are different. You don't plan for a small foot print, you plan for a function that is concise and does a single thing extremely well - this SHOULD lead to a small foot print (but may not). Here's a short list of what I would focus on when writing code:
single focused functions - a function should do only one thing, a simple delivery, multi featured functions are buggy and not easily reusable
loosely coupled - don't reach out from inside one function to global data and don't rely heavily on other functions
precise naming - use meaningful precise variable names, cryptic names are just that
keep the code simple and not complex - don't over use language specific technical wow's, good for impressing others, difficult to easily understand and maintain - if you do add something 'special' comment it so at least people can appreciate it prior to cursing you out
evenly comment - to many comments will be ignored and outdated to few have no meaning
formatting - take pride in how the code looks, properly indented code helps
work with the mind of a code maintenance person - think what it would be like to maintain the code you're writting
do be afraid or to lazy to refactor - nothing is perfect the first time, clean up your own mess
One way to find a balance is to seek for readability and not concise-ness. Programmers are constantly scanning code visually to see what is being done, and so the code should as much as possible flow nicely.
If the programmer is scanning code and hits a section that is hard to understand, or takes some effort to visually parse and understand, it is a bad thing. Using common well understood constructs is important, stay away from the vague and infrequently used unless necessary.
Humans are not compilers. Compilers can eat the stuff and keep moving on. Obscure code is not mentally consumed by humans as quickly as clearly understood code.
At times it is very hard to produce readable code in a complicated algorithm, but for the most part, human readability is what we should look for, and not cleverness. I don't think length of code is really a measure of clearness either, because sometimes a more verbose method is more readable than a concise method, and sometimes a concise method is more readable than a long one.
Also, comments should only supplement, and should not describe your code, your code should describe itself. If you have to comment a line because it isn't obvious what is done, that is bad. It takes longer for most experienced programmers to read an English explanation than it does to read the code itself. I think the book Code Complete hammers this one home.
As far as object names go, the thinking on this has gone through an evolution with the introduction of new programming languages.
If you take the "curly brace" languages, starting with C, brevity was considered the soul of wit. So, you would have a variable to hold a loan value named "lv", for instance. The idea was that you were typing a lot of code, so keep the keystrokes to a minimum.
Then along came the Microsoft-sanctioned "Hungarian notation", where the first letters of a variable name were meant to indicate its underlying type. One might use "fLV", or some such, to indicate that the loan value was represented by a float variable.
With Java, and then C#, the paradigm has become one of clarity. A good name for a loan value variable would be "loanValue". I believe part of the reason for this is the command-completion feature in most modern editors. Since its not necessary to type an entire name anymore, you might as well use as many characters as is needed to be descriptive.
This is a good trend. Code needs to be intelligible. Comments are often added as an afterthought, if at all. They are also not updated as code is updated, so they become out of date. Descriptive, well-chosen, variable names are the first, best and easiest way to let others know what you were coding about.
I had a computer science professor who said "As engineers, we are constantly creating types of things that never existed before. The names that we give them will stick, so we should be careful to name things meaningfully."
There needs to be a balance between short sweet source code and performance. If it is nice source and runs the fastest, then good, but for the sake of nice source it runs like a dog, then bad.
Strive to refactor until the code itself reads well. You'll discover your own mistakes in the process, the code will be easier to grok for the "next guy", and you won't be burdened by maintaining (and later forgetting to change) in comments what you're already expressed in code.
When that fails... sure, leave me a comment.
And don't tell me "what" in the comment (that's what the code is for), tell me "why".
As opposed to long/rambling? Sure!
But it gets to the point where it's so short and so concise that it's hard to understand, then you've gone too far.
Yes. Always.
DRY: Don't Repeat Yourself. That will give you a code that is both concise and secure. Writing the same code several times is a good way to make it hard to maintain.
Now that does not mean you should make a function of any blocks of code looking remotely alike.
A very common error (horror ?) for instance is factorizing code doing nearly the same thing, and to handle the differences between occurences by adding a flag to function API. This may look inocuous at first, but generates code flow hard to understand and bug prone, and even harder to refactor.
If you follow common refactoring rules (looking about code smells) your code will become more and more concise as a side effect as many code smells are about detecting redundancy.
On the other hand, if you try to make the code as short as possible not following any meaningfull guidelines, at some point you will have to stop because you just won't see any more how to reduce code.
Just imagine if the first step is removing all useless whitespaces... after that step code in most programming languages will become so hard to read you won't have much chance to find any other possible enhancement.
The example above is quite caricatural, but not so far from what you get when trying to optimise for size without following any sensible guideline.
There's no exact line that can be drawn to distinguish between code that is glib and code that is flowery. Use your best judgment. Have others look at your code and see how easily they can understand it. But remember, correctness is the number 1 goal.
The need for small code footprints is a throwback from the days of assembly language and the first slightly high level languages... there small code footprints where a real and pressing need. These days though, its not so much of a necessity.
That said, I hate verbose code. Where I work, we write code that reads as much as possible like a natural language, without any extra grammar or words. And we don't abbreviate anything unless its a very common abbreviation.
Company.get_by_name("ABC")
makeHeaderTable()
is about as terse as we go.
In general, I make things obvious and easy to work with. If concision/shortness serves me in that end, all the better. Often short answers are the clearest, so shortness is a byproduct of obvious.
There are a couple points to my mind that determine when to stop optimizing:
Worth of spending time performing optimizations. If you have people spending weeks and not finding anything, are there better uses of those resources?
What is the order of optimization priority. There are a few different factors that one could care about when it comes to code: Execution time, execution space(both running and just the compiled code), scalability, stability, how many features are implemented, etc. Part of this is the trade off of time and space, but it can also be where does some code go, e.g. can middleware execute ad hoc SQL commands or should those be routed through stored procedures to improve performance?
I think the main point is that there is a moderation that most good solutions will have.
The code optimizations have little to do with the coding style. The fact that the file contains x spaces or new lines less than at the beginning does not make it better or faster, at least at the execution stage - you format the code with white characters that are unsually ignored by the compiler. It even makes the code worse, because it becomes unreadable for the other programmers and yourself.
It is much more important for the code to be short and clean in its logical structure, such as testing conditions, control flow, assumptions, error handling or the overall programming interface. Of course, I would also include here smart and useful comments + the documentation.
There is not necessarily a correlation between concise code and performance. This is a myth. In mature languages like C/C++ the compilers are capable of optimizing the code very effectively. There is cause need in such languages to assume that the more concise code is the better performing code. Newer, less performance-optimized languages like Ruby lack the compiler optimization features of C/C++ compilers, but there is still little reason to believe that concise code is better performing. The reality is that we never know how well code will perform in production until it gets into production and is profiled. Simple, innocuous, functions can be huge performance bottlenecks if called from enough locations within the code. In highly concurrent systems the biggest bottlenecks are generally caused by poor concurrency algorithms or excessive locking. These issues are rarely solved by writing "concise" code.
The bottom line is this: Code that performs poorly can always be refactored once profiling determines it is the bottleneck. Code can only be effectively refactored if it is easy to understand. Code that is written to be "concise" or "clever" is often more difficult to refactor and maintain.
Write your code for human readability then refactor for performance when necessary.
My two cents...
Code should be short, concrete, and concentrated. You can always explain your ideas with many words in the comments.
You can make your code as short or compact as you like as long as you comment it. This way your code can be optimized but still make sence. I tend to stay in the middle somewhere with descriptive variables and methods and sparce comments if it is still unclear.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 4 years ago.
Improve this question
We all know to keep it simple, right?
I've seen complexity being measured as the number of interactions between systems, and I guess that's a very good place to start. Aside from gut feel though, what other (preferably more objective) methods can be used to determine the level of complexity of a particular design or piece of software?
What are YOUR favorite rules or heuristics?
Here are mine:
1) How hard is it to explain to someone who understands the problem but hasn't thought about the solution? If I explain the problem to someone in the hall (who probably already understands the problem if they're in the hall) and can explain the solution, then it's not too complicated. If it takes over an hour, chances are good the solution's overengineered.
2) How deep in the nested functions do you have to go? If I have an object which requires a property held by an object held by another object, then chances are good that what I'm trying to do is too far removed from the object itself. Those situations become problematic when trying to make objects thread-safe, because there'd be many objects of varying depths from your current position to lock.
3) Are you trying to solve problems that have already been solved before? Not every problem is new (and some would argue that none really are). Is there an existing pattern or group of patterns you can use? If you can't, why not? It's all good to make your own new solutions, and I'm all for it, but sometimes people have already answered the problem. I'm not going to rewrite STL (though I tried, at one point), because the solution already exists and it's a good one.
Complexity can be estimated with the coupling and how cohesive are all your objects. If something is have too much coupling or is not enough cohesive, than the design will start to be more complex.
When I attended the Complex Systems Modeling workshop at the New England Complex Systems Institute (http://necsi.org/), one of the measures that they used was the number of system states.
For example if you have two nodes, which interact, A and B, and each of these can be 0 or 1, your possible states are:
A B
0 0
1 0
0 1
1 1
Thus a system of only 1 interaction between binary components can actually result in 4 different states. The point being that the complexity of the system does not necessarily increase linearly as the number of interactions increases.
good measures can be also number of files, number of places where configuration is stored, order of compilation on some languages.
Examples:
.- properties files, database configuration, xml files to hold related information.
.- tens of thousands of classes with interfaces, and database mappings
.- a extremely long and complicated build file (build.xml, Makefile, others..
If your app is built, you can measure it in terms of time (how long a particular task would take to execute) or computations (how much code is executed each time the task is run).
If you just have designs, then you can look at how many components of your design are needed to run a given task, or to run an average task. For example, if you use MVC as your design pattern, then you have at least 3 components touched for the majority of tasks, but depending on your implementation of the design, you may end up with dozens of components (a cache in addition to the 3 layers, for example).
Finally something LOC can actually help measure? :)
i think complexity is best seen as the number of things that need to interact.
A complex design would have n tiers whereas a simple design would have only two.
Complexity is needed to work around issues that simplicity cannot overcome, so it is not always going to be a problem.
There is a problem in defining complexity in general as complexity usually has a task associated with it.
Something may be complex to understand, but simple to look at (very terse code for example)
The number of interactions getting this web page from the server to your computer is very complex, but the abstraction of the http protocol is very simple.
So having a task in mind (e.g. maintenance) before selecting a measure may make it more useful. (i.e. adding a config file and logging to an app increases its objective complexity [yeah, only a little bit sure], but simplifies maintenance).
There are formal metrics. Read up on Cyclomatic Complexity, for example.
Edit.
Also, look at Function Points. They give you a non-gut-feel quantitative measurement of system complexity.
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 4 years ago.
Improve this question
Is it better to write many small methods (or functions), or to simply write the logic/code of those small processes right into the place where you would have called the small method? What about breaking off code into a small function even if for the time being it is only called from one spot?
If one's choice depends on some criteria, what are they; how should a programmer make a good judgement call?
I'm hoping the answer can be applied generally across many languages, but if necessary, answers given can be specific to a language or languages. In particular, I'm thinking of SQL (functions, rules and stored procedures), Perl, PHP, Javascript and Ruby.
I always break long methods up into logical chunks and try to make smaller methods out of them. I don't normally turn a few lines into a separate method until I need it in two different places, but sometimes I do just to help readability, or if I want to test it in isolation.
Fowler's Refactoring is all about this topic, and I highly recommend it.
Here's a handy rule of thumb that I use from Refactoring. If a section of code has a comment that I could re-word into a method name, pull it out and make it a method.
The size of the method is directly linked to its cyclomatic complexity.
The main advantages to keep the size of the method small (which means dividing a big method into several small methods) are:
better unit testing (due to low cyclomatic complexity)
better debugging due to a more explicit stack trace (instead of one error within one giant method)
As always you can say: it depends. It's more a question of naming and defining the task of a method. Every method should do one (not more) well defined task and should do them completely. The name of the method should indicate the task. If your method is named DoAandB() it may be better to have separate methods DoA() and DoB(). If you need methods like setupTask, executeTask, FinishTask, it may be useful to combine them.
Some points that indicate, that a merge of different methods may be useful:
A method cannot be used alone, without the use of other methods.
You have to be careful to call some dependent methods in the right order.
Some points that indicate, that a splitup of the method could be useful:
Some lines of the existing method have clear independent task.
Unit-testing of the big method gets problematic. If tests are easier to write for independent methods, then split the big method up.
As an explanation to the unit-test-argument: I wrote a method, that did some things including IO. The IO-part was very hard to test, so I thought about it. I came to the conclusion, that my method did 5 logical and independent steps, and only one of them involved the IO. So I split up my method into 5 smaller ones, four of them were easy to test.
Small methods every time.
They are self documenting (er, if well named)
They break down the problem into manageable parts - you are KeepingItSimple.
You can use OO techniques to more easily (and obviously) plug in behaviour. The large method is by definition more procedural and so less flexible.
They are unit testable. This is the killer, you simply can’t unit test some huge method that performs a load of tasks
Something I learnt from The Code Complete book:
Write methods/functions so that it
implement one chunk(or unit or task)
of logic. If that requires breakdown
into sub tasks, then write a
seperate method/function for them
and call them.
If I find that the method/function
name is getting long then I try to
examine the method to see it it can
be broken down into two methods.
Hope this helps
Some rules of thumb:
Functions should not be longer than what can be displayed on screen
Break functions into smaller ones if it makes the code more readable.
I make each function do one thing, and one thing only, and I try not to nest too many levels of logic. Once you start breaking your code down into well named functions, it becomes a lot easier to read, and practically self-documenting.
I find that having many small methods makes code easier to read, maintain and debug.
When I'm reading through a unit that implements some business logic, I can better follow the flow if I see a series of method calls that describe the process. If I care about how the method is implemented, I can go look in the code.
It feels like more work but it ultimately saves time.
There is an art, I think, to knowing what to encapsulate. Everyone has some slight difference of opinion. If I could put it in words I'd say that each method should do one thing that can be described as a complete task.
The bigger the method, the harder to test and maintain. I find its much easier to understand how a large process works when its broken down into atomic steps. Also, doing this is a great first step to make your classes extensible. You can mark those individual steps as virtual (for inheritance), or move them into other objects (composition), making your application's behavior easier to customize.
I usually go for splitting functions into smaller functions that each perform a single, atomic task, but only if that function is complex enough to warrent it.
This way, I don't end up with multiple functions for simple tasks, and the functions I do extract can typically be used elsewhere as they don't try to achieve too much. This also aids unit testing as each function (as a logical, atomic action) can then be tested individually.
It depends a bit ... on mindset. Still, this is not an opinionated question.
The answer rather actually depends on the language context.
In a Java/C#/C++ world, where people are following the "Clean Code" school, as preached by Robert Martin, then: many small methods are the way to go.
A method has a clear name, and does one thing. One level of nesting, that's it. That limits its length to 3, 5, max 10 lines.
And honestly: I find this way of coding absolutely superior to any other "style".
The only downside of this approach is that you end up with many small methods, so ordering within a file/class can become an issue. But the answer to that is to use a decent IDE that allows to easily navigate forth and back.
So, the only "legit" reason to use the "all stuff goes into one method/function" is when your whole team works like that, and prefers that style. Or when you can't use decent tooling (but then navigating that big ugly function won't work either).
Personally, I lean significantly in the direction of preferring more, smaller methods, but not to the point of religiously aiming for a maximum line count. My primary criterion or goal is to keep my code DRY. The minute I have a code block which is duplicated (whether in spirit or actually by the text), even if it might be 2 or 4 lines long, I DRY up that code into a separate method. Sometimes I will do so in advance if I think there's a good chance it will be used again in the future.
On the flip side, I have also heard it argued that if your break-off method is too small, in the context of a team of developers, a teammate is likely not to know about your method, and will either write inline, or write his own small method that does the same thing. This is admittedly a bad situation.
Some also try to argue that it is more readable to keep things inline, so a reader can just read top-down, instead of having to jump around method definitions, possibly across multiple files. Personally, I think the existence of a stack trace makes this not much of an issue.