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We all know and love (?) JavaScript, and we all just work with it by writing code and then executing it in our favorite runtime (namely the browser, node.js and Deno). But have you ever compiled it?
Wait, let’s back up for a second, JavaScript is a dynamic language, we all know that. It is also interpreted (well, mostly) and out of the usual runtimes, all of them use a JIT compiler to optimize it during execution.
That’s a fact.
But can it be compiled? That’s a whole different deal. Compiling a dynamic language ahead of time (what is also known as AOT or Ahead-Of-Time compilation) is possible, yes, but is it worth it?
#javascript #programming
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Who invented JavaScript, how it works, as we have given information about Programming language in our previous article ( What is PHP ), but today we will talk about what is JavaScript, why JavaScript is used The Answers to all such questions and much other information about JavaScript, you are going to get here today. Hope this information will work for you.
JavaScript language was invented by Brendan Eich in 1995. JavaScript is inspired by Java Programming Language. The first name of JavaScript was Mocha which was named by Marc Andreessen, Marc Andreessen is the founder of Netscape and in the same year Mocha was renamed LiveScript, and later in December 1995, it was renamed JavaScript which is still in trend.
JavaScript is a client-side scripting language used with HTML (Hypertext Markup Language). JavaScript is an Interpreted / Oriented language called JS in programming language JavaScript code can be run on any normal web browser. To run the code of JavaScript, we have to enable JavaScript of Web Browser. But some web browsers already have JavaScript enabled.
Today almost all websites are using it as web technology, mind is that there is maximum scope in JavaScript in the coming time, so if you want to become a programmer, then you can be very beneficial to learn JavaScript.
In JavaScript, ‘document.write‘ is used to represent a string on a browser.
<script type="text/javascript">
document.write("Hello World!");
</script>
<script type="text/javascript">
//single line comment
/* document.write("Hello"); */
</script>
#javascript #javascript code #javascript hello world #what is javascript #who invented javascript
1604008800
Static code analysis refers to the technique of approximating the runtime behavior of a program. In other words, it is the process of predicting the output of a program without actually executing it.
Lately, however, the term “Static Code Analysis” is more commonly used to refer to one of the applications of this technique rather than the technique itself — program comprehension — understanding the program and detecting issues in it (anything from syntax errors to type mismatches, performance hogs likely bugs, security loopholes, etc.). This is the usage we’d be referring to throughout this post.
“The refinement of techniques for the prompt discovery of error serves as well as any other as a hallmark of what we mean by science.”
We cover a lot of ground in this post. The aim is to build an understanding of static code analysis and to equip you with the basic theory, and the right tools so that you can write analyzers on your own.
We start our journey with laying down the essential parts of the pipeline which a compiler follows to understand what a piece of code does. We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.
Note that although the ideas here are discussed in light of Python, static code analyzers across all programming languages are carved out along similar lines. We chose Python because of the availability of an easy to use ast
module, and wide adoption of the language itself.
Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:
As you can see in the diagram (go ahead, zoom it!), the static analyzers feed on the output of these stages. To be able to better understand the static analysis techniques, let’s look at each of these steps in some more detail:
The first thing that a compiler does when trying to understand a piece of code is to break it down into smaller chunks, also known as tokens. Tokens are akin to what words are in a language.
A token might consist of either a single character, like (
, or literals (like integers, strings, e.g., 7
, Bob
, etc.), or reserved keywords of that language (e.g, def
in Python). Characters which do not contribute towards the semantics of a program, like trailing whitespace, comments, etc. are often discarded by the scanner.
Python provides the tokenize
module in its standard library to let you play around with tokens:
Python
1
import io
2
import tokenize
3
4
code = b"color = input('Enter your favourite color: ')"
5
6
for token in tokenize.tokenize(io.BytesIO(code).readline):
7
print(token)
Python
1
TokenInfo(type=62 (ENCODING), string='utf-8')
2
TokenInfo(type=1 (NAME), string='color')
3
TokenInfo(type=54 (OP), string='=')
4
TokenInfo(type=1 (NAME), string='input')
5
TokenInfo(type=54 (OP), string='(')
6
TokenInfo(type=3 (STRING), string="'Enter your favourite color: '")
7
TokenInfo(type=54 (OP), string=')')
8
TokenInfo(type=4 (NEWLINE), string='')
9
TokenInfo(type=0 (ENDMARKER), string='')
(Note that for the sake of readability, I’ve omitted a few columns from the result above — metadata like starting index, ending index, a copy of the line on which a token occurs, etc.)
#code quality #code review #static analysis #static code analysis #code analysis #static analysis tools #code review tips #static code analyzer #static code analysis tool #static analyzer
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According to an analysis, a developer creates 70 bugs per 1000 lines of code on average. As a result, he spends 75% of his time on debugging. So sad!
Bugs are born in many ways. Creating side effects is one of them.
Some people say side effects are evil, some say they’re not.
I’m in the first group. Side effects should be considered evil. And we should aim for side effects free code.
Here are 4ways you can use to achieve the goal.
Just add use strict; to the beginning of your files. This special string will turn your code validation on and prevent you from using variables without declaring them first.
#functional-programming #javascript-tips #clean-code #coding #javascript-development #javascript
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Having another pair of eyes scan your code is always useful and helps you spot mistakes before you break production. You need not be an expert to review someone’s code. Some experience with the programming language and a review checklist should help you get started. We’ve put together a list of things you should keep in mind when you’re reviewing Java code. Read on!
NullPointerException
…
#java #code quality #java tutorial #code analysis #code reviews #code review tips #code analysis tools #java tutorial for beginners #java code review
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There are more code smells. Let’s keep changing the aromas. We see several symptoms and situations that make us doubt the quality of our development. Let’s look at some possible solutions.
Most of these smells are just hints of something that might be wrong. They are not rigid rules.
This is part II. Part I can be found here.
The code is difficult to read, there are tricky with names without semantics. Sometimes using language’s accidental complexity.
_Image Source: NeONBRAND on _Unsplash
Problems
Solutions
Examples
Exceptions
Sample Code
Wrong
function primeFactors(n){
var f = [], i = 0, d = 2;
for (i = 0; n >= 2; ) {
if(n % d == 0){
f[i++]=(d);
n /= d;
}
else{
d++;
}
}
return f;
}
Right
function primeFactors(numberToFactor){
var factors = [],
divisor = 2,
remainder = numberToFactor;
while(remainder>=2){
if(remainder % divisor === 0){
factors.push(divisor);
remainder = remainder/ divisor;
}
else{
divisor++;
}
}
return factors;
}
Detection
Automatic detection is possible in some languages. Watch some warnings related to complexity, bad names, post increment variables, etc.
#pixel-face #code-smells #clean-code #stinky-code-parts #refactor-legacy-code #refactoring #stinky-code #common-code-smells