Choosing Static vs. Dynamic Languages for Your Startup
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Everyone is thinking why in the world would anyone pick static, when you can be dynamic? Usually the thought process is, "what language am I most proficient in, that can do the job." Totally not a bad way to go about it. Now does this choice affect anything else? Testing? Speed of development? Robustness?
Dynamic vs. Static
Dynamic languages are languages that don’t necessarily need variables to be declared before they are used. Examples of dynamic languages are Python, Ruby, and PHP. So in dynamic languages the following is possible:
num = 10
We have successfully assigned a value to variable without declaring it before hand. Simple enough, try doing this in Java (you can’t). This can *increase* development speed, without having to write boilerplate code. This can somewhat be a double edge sword, since dynamic languages types are checked during runtime, there is no way to tell if there is a bug in code until it is run. I know you can test, but you can’t test for everything. You can’t test for everything. Here is an example albeit trivial.
def get_first_problem(problems): for problem in problems: problam = problem + 1 return problam
Now if you are raging to some serious dubstep, its easy enough to miss that small typo, you go screw it and do it live, and deploy to production. Python will simply create the new variable and not a single thing will be said.
Only you can stop bugs in production!
Static languages are languages that variables need to be declared before use and type checking is done at compile time. Examples of static languages include Java, C, and C++. So in static languages the following is enforced
static int awesomeNumber; awesomeNumber = 10;
Many argue this increases robustness as well as decrease chances of Runtime Errors. Since the compiler will catch those horrible horrible mistakes you made throughout your code. Your methods contracts are tighter, downside to this is crap ton of boilerplate code.
Weak and Strong Typing can be often be confused with dynamic and static languages. Weak typed languages can lead to philosophical questions like what does the number 2 added to the word ‘two’ give you? Things like this are possible with a weak typed language.
a = 2 b = "2" concatenate(a, b) // Returns "22" add(a, b) // Returns 4
Traditionally languages may place restriction on what transaction may occur for example in a strong typed language adding a string and integer will result in a type error as shown below.
>>> a = 10 >>> b = 'ten' >>> a + b Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: unsupported operand type(s) for +: 'int' and 'str' >>>
Regardless of where you land on this discussion, claiming one is better than the other would lead to flame war, but there are places where each is strong.
Dynamic languages are good for fast quick development cycles and prototyping, while static languages are better suited to longer development cycles where trivial bugs could be extremely costly (telecommunication systems, air traffic control).
For example if some giant company called Moo Corp. spent millions of dollars on QA and Testing and a bug somehow gets into the field, to fix it would mean another round of testing. When sitting in that chair the choice is clear static languages FTW, its a hard job but someone has to milk the cows.
Test, test, and test.
Just a little food for thought, for when you are starting your next project. You never know what limitations you maybe placing on yourself and your team.
What do you do consider when selecting a programming language for a project?
Published at DZone with permission of Mahdi Yusuf, DZone MVB. See the original article here.
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