CRACKING CODING INTERVIEW

vishwasenthil76 — Sun, 24 May 2026 06:25:56 +0000

Technical Interview

Technical interviews are an important part of the hiring process in many technology companies. These interviews are designed not only to test coding ability but also to evaluate problem-solving skills, communication, and technical knowledge. Understanding how interviewers assess candidates helps students prepare effectively.

A) Role of Algorithm & Coding Questions

Algorithms form major part of interviews
Interview focuses on problem solving
Sometimes only one problem is discussed in an interview because time is limited (around 45 minutes)

B) Skills Evaluated by Interviewers

Analytical Skills

Problem solving ability
Solution optimization
Decision making

Coding Skills

Writing clean code
Error handling
Code organization

Technical Knowledge

Data structures
Algorithms
CS fundamentals

Experience

Projects
Technical decisions
Initiative

Communication & Culture Fit

Communication is important because employees work in teams.
Interviewers observe:

Confidence
Communication style
Teamwork
Personality fit with company culture

Evaluation is based on Ability to convert logic into code.

Interviewers observe:

Clean code writing
Proper formatting
Error handling
Readability

for Example:

Bad code:

a=[1,2,3]
for i in a:print(i)

Good code:

numbers = [1,2,3]

for num in numbers:
    print(num)

C) Why Companies Use This Process?

Problem-solving skills are valuable

Companies believe candidates who solve difficult problems can contribute effectively.

Data structures & algorithms knowledge

Topics like:

Trees
Graphs
Lists
Sorting

are considered important foundations.

Whiteboard Interviews

Focus on logic instead of syntax
Encourages communication
Tests thinking process

Interviewers do not expect perfect syntax. They observe how candidates approach solutions.

D) Interview Question Selection

No fixed question list in most companies
Interviewers choose questions individually
Questions are often similar across companies like Google, Amazon, and Meta

E) Candidate Evaluation System

Candidates are assessed by comparing performance with previous candidates who solved the same question rather than using fixed marks. Hard questions are difficult for everyone, so receiving a difficult problem does not necessarily reduce chances of success.
Candidate Evaluation Process

There is usually no strict marking scheme.

Interviewers compare candidates based on:

Speed
Solution quality
Hints required
Alternative approaches
Communication

Example:

Candidate A → solved in 10 mins independently
Candidate B → solved in 20 mins with hints

Looping Concept

vishwasenthil76 — Fri, 22 May 2026 12:50:17 +0000

In python, loops are mainly used to execute a block of code repeatedly.
There are two main types of loop:
1.While loop
2.For loop

1. While Loop

A while loop runs as long as the condition is true.

Example:

i = 1

while i <= 5:
    print(i)
    i += 1

Output:

1
2
3
4
5

flowchart of While loop:

2. For Loop

A for loop is used to repeat a block of code for every item in a sequence such as a string, list, or range.

Using For Loop with String

Example:

name = "Python"

for ch in name:
    print(ch)

Output:

P
y
t
h
o
n

flowchart of For loop:

Linear Search

In Linear Search, we iterate over all the elements of the array and check if it the current element is equal to the target element. If we find any element to be equal to the target element, then return the index of the current element. Otherwise, if no element is equal to the target element, then return -1 as the element is not found.
Linear search is also known as sequential search.

Time Complexity of Linear search:
->Best case: O(1)
->Average case: O(N)
->Worst case: O(N)

Flowchart of Linear search:

Binary search

Binary search works only on sorted data. Instead of checking every element one by one, it checks the middle element and decides whether to search on the left side or right side.
This method reduces the number of comparisons and makes searching faster.

Time Complexity of Binary search:
-> Best Case: O(1)
-> Average Case: O(log N)
-> Worst Case: O(log N)

Flowchart of Binary search:

references:
https://www.geeksforgeeks.org/python/loops-in-python/
https://www.geeksforgeeks.org/dsa/linear-search/

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CRACKING CODING INTERVIEW

Looping Concept