#004 Simple but Tricky JavaScript Interview Questions | Equality Check | Techsimple

🚀 Welcome to another exciting episode of Techsimple! Are you gearing up for a JavaScript interview and want to sharpen your skills with some simple yet mind-bending questions? Look no further! In this video, we've handpicked a collection of JavaScript interview questions that might seem straightforward at first, but can truly put your knowledge to the test.

In this video, we will cover:
🧠 Common JavaScript concepts that are often discussed in interviews.
🤯 Tricky scenarios and edge cases that will challenge your problem-solving skills.
🔥 Expert tips and explanations to help you understand the solutions thoroughly.

Whether you're a beginner looking to get started with JavaScript interviews or an experienced developer wanting to fine-tune your skills, this video has something for everyone. Prepare to level up your JavaScript game and ace those interviews!

In most programming languages, including JavaScript, the expression 0.1 + 0.7 === 0.8 would evaluate to false. Let me break down why this is the case:

Floating-Point Representation: Computers use a binary representation to store floating-point numbers (numbers with decimal points). In this binary representation, some numbers cannot be precisely represented. This leads to rounding errors when performing arithmetic operations.

0.1 and 0.7 in Binary: When you represent 0.1 and 0.7 in binary, they become recurring fractions, similar to how 1/3 in decimal is 0.333... with an infinite number of threes. The binary representations of 0.1 and 0.7 are not exact, leading to small rounding errors.

0.1 in binary is approximately 0.000110011001100110011...
0.7 in binary is approximately 0.10110011001100110011...
Addition in Binary: When you add these binary representations, you get a binary representation that is approximately 0.0010110011001100110011... This is not precisely equal to the binary representation of 0.8.

Equality Check (===): The === operator in JavaScript checks for both value and type equality. In this case, since the binary representation of the result of 0.1 + 0.7 is not exactly equal to the binary representation of 0.8, the equality check returns false.

To avoid issues with floating-point precision in programming, it's common to use techniques like comparing numbers within a small tolerance range, such as: