Picture Puzzle In JavaScript With Source Code

The Picture Puzzle is a simple project developed using JavaScript, CSS, and Canvas. This game is an interesting game. The player has to solve the image puzzle and form the original image. The user can play the game until he/she completes the puzzle. There is timer and count set on the top. You can change the mode from easy to very hard.

Source Code: https://code-projects.org/picture-puzzle-in-javascript-with-source-code/

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#javascript

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What is JavaScript - Stackfindover - Blog

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.

Who invented JavaScript?

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.

What is JavaScript?

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.

JavaScript Hello World Program

In JavaScript, ‘document.write‘ is used to represent a string on a browser.

<script type="text/javascript">
	document.write("Hello World!");
</script>

How to comment JavaScript code?

• For single line comment in JavaScript we have to use // (double slashes)
• For multiple line comments we have to use / * – – * /

<script type="text/javascript">

//single line comment

/* document.write("Hello"); */

</script>

Advantages and Disadvantages of JavaScript

#javascript #javascript code #javascript hello world #what is javascript #who invented javascript

GitHub Arctic Code Vault: Overview

Are you an Arctic Code Vault Contributor or have seen someone posting about it and don’t know what it is. So let’s take a look at what is an Arctic Code Vault Contributor and who are the ones who gets this batch.

GitHub, the world’s largest open-source platform for software and programs has safely locked the data of huge value and magnitude in a coal mine in Longyearbyen’s Norwegian town in the Arctic region.

Back in November 2019, GitHub Arctic Code Vault was first announced.

The GitHub Arctic Code Vault is a data repository preserved in the Arctic

World Archive (AWA), a very-long-term archival facility 250 meters deep in the permafrost of an Arctic mountain. The archive is located in a decommissioned coal mine in the Svalbard archipelago, closer to the North Pole than the Arctic Circle.

Last year, GitHub said that it plans to capture a snapshot of every active

public repository on 02/02/2020 and preserve that data in the Arctic

Code Vault.

The project began on February 2, when the firm took a snapshot of all of

GitHub’s active public repositories to store them in the vault. They initially intended to travel to Norway and personally escort the world’s open-source technology to the Arctic but their plans were derailed by the global pandemic. Then, they had to wait until 8 Julyfor the Arctic Data Vault data to be deposited.

GitHub announced that the code was successfully deposited in the Arctic Code Vault on July 8, 2020. Over the past several months, GitHub worked

with its archive partners Piql to write the 21TB of GitHub repository data to 186 reels of piqlFilm (digital photosensitive archival film).

GitHub’s strategic software director, Julia Metcalf, has written a blog post

on the company’s website notifying the completion of GitHub’s Archive Program on July 8th. Discussing the objective of the Archive Program, Metcalf wrote “Our mission is to preserve open-source software for future generations by storing your code in an archive built to last a thousand years.”

The Arctic Code Vault is only a small part of the wider GitHub Archive

Program, however, which sees the company partner with the Long Now

Foundation, Internet Archive, Software Heritage Foundation, Microsoft

Research and others.

How the cold storage will last 1,000 years?

Svalbard has been regulated by the international Svalbard Treaty as a demilitarized zone. Home to the world’s northernmost town, it is one of the most remote and geopolitically stable human habitations on Earth.

The AWA is a joint initiative between Norwegian state-owned mining company Store Norske Spitsbergen Kulkompani (SNSK) and very-long-term digital preservation provider Piql AS. AWA is devoted to archival storage in perpetuity. The film reels will be stored in a steel-walled container inside a sealed chamber within a decommissioned coal mine on the remote archipelago of Svalbard. The AWA already preserves historical and cultural data from Italy, Brazil, Norway, the Vatican, and many others.

What’s in the 02/02/2020 snapshot?

The 02/02/2020 snapshot archived in the GitHub Arctic Code Vault will

sweep up every active public GitHub repository, in addition to significant dormant repos.

The snapshot will include every repo with any commits between the announcement at GitHub Universe on November 13th and 02/02/2020,

every repo with at least 1 star and any commits from the year before the snapshot (02/03/2019 – 02/02/2020), and every repo with at least 250 stars.

The snapshot will consist of the HEAD of the default branch of each repository, minus any binaries larger than 100KB in size—depending on available space, repos with more stars may retain binaries. Each repository will be packaged as a single TAR file. For greater data density and integrity, most of the data will be stored QR-encoded and compressed. A human-readable index and guide will itemize the location of each repository and explain how to recover the data.

The company further shared that every reel of the archive includes a copy

of the “Guide to the GitHub Code Vault” in five languages, written with input from GitHub’s community and available at the Archive Program’s own GitHub repository.

#github #open-source #coding #open-source-contribution #contributing-to-open-source #github-arctic-code-vault #arctic-code-vault #arctic-code-vault-contributor

Static Code Analysis: What It Is? How to Use It?

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.”

• J. Robert Oppenheimer

Outline

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.

How does it all work?

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:

Scanning

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

4 Ways You Can Get Rid of Dirty Side Effects for Cleaner Code in JavaScript

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.

1. use strict;

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

Looking Under the Hood of Apache Pulsar: How Good is the Code?

Apache Pulsar (incubating) is an enterprise-grade publish-subscribe (aka pub-sub) messaging system that was originally developed at Yahoo. Pulsar was first open-sourced in late 2016, and is now undergoing incubation under the auspices of the Apache Software Foundation. At Yahoo, Pulsar has been in production for over three years, powering major applications like Yahoo! Mail, Yahoo! Finance, Yahoo! Sports, Flickr, the Gemini Ads platform, and Sherpa, Yahoo’s distributed key-value store.

One of the primary goals of the open-source software movement is to allow all users to freely modify software, use it in new ways, integrate it into a larger project or derive something new based on the original. The larger idea being that through open collaboration, we can make a software the best version of itself. So, in the spirit of innovation and improvement, we peeked behind the curtain and ran Apache Pulsar through the free static code analysis tool Embold. The results are very interesting, both from an observer’s and a learner’s point of view.

1. Quality Gate: Embold’s Quality gate is “closed” for Pulsar mainly due to the Code Issues and Code Duplication. The overall rating score is certainly not the best, but sits at an innocuous 1.76 (5 being the best on the scale).

2. Code Issues: And so let’s move on to some of the code issues found. The critical and high Code issues count in the modules pulsar-broker and pulsar-functions are close to 150. That’s a high number worth exploring. Time to do a deep-dive.

TheadLeak: This issue is fairly common across the entire codebase. To quote an occurrence, we see that in the Compactor class, shutdown() is missing for the executor service that manages the threadpool, indicating a thread resource leak. The tool recommends call the shutdown() once done to ensure there is no thread resource leaks.

_Resource Leak: _In the RuntimeUtils class, we see that close() on the resource rd is not guarded by a finally block. This means, that if there’s an exception while reading the data, the resource will never get closed, indicating a leak.

#java #open source #software testing #code quality #anti-patterns #static analysis tools #source code analysis #apache pulsar #code duplication #code issues