5 Steps to Improve Your Data Structure and Algorithm Skills

Written by sandeepmishratech | Published 2022/02/22
Tech Story Tags: data-structures | data-structures-and-algorithms | programming | data-structure | algorithm-skills | data-structure-skills | learning-to-code | learning

TLDRData structure and algorithms are the most important skills to be prepared for an interview at a top product-based company. The steps outlined below will help you develop and improve your DSA skills quickly and effectively. Learn about various algorithms like the pigeonhole principle, square root decomposition, set theory, [bitwise operations, graph theory, dynamic programming, greedy algorithms, etc. Mastering algorithms makes you a competitive programmer because at this level you learn to optimize the code to have minimal execution time.via the TL;DR App

Introduction

Data structure and algorithms are the most important skills to be prepared for an interview at a top product-based company. In order to win this masterstroke and become an expert in data structures and algorithms, it requires hard-working inputs with a pinch of continuity. The steps outlined below will help you develop and improve your DSA skills quickly and effectively.

Steps to Boost Data Structure and Algorithms

1. Fundamentals

There is a famous quote “keep your head clear” which becomes the required tagline while learning data structures. For example, if you learn tree data structure, ensure that basic terminologies are clear like a branch, sibling, left subtree, right subtree, etc.

  • Implement and learn the basic functionality while learning a data structure and after that to save time the specific class for that data structure can be used.
  • Learn about various algorithms like the pigeonhole principle, square root decomposition, set theory, bitwise operations, graph theory, dynamic programming, greedy algorithms, etc.
  • Explore more about a topic you are learning. Visit as many blogs or articles to understand the various use cases and structures.
  • Practicing and doing more practice questions on a data structure will add more clearance to it.
  • Making short notes to revise timely will help you improve logic.
  • Learn how data is represented in a computer, the basics of digital logic design, boolean algebra, computer arithmetic, floating-point representation, cache design. Try and learn a little about C and Assembly programming.

2. Work on logic building

When we say to improve programming skills, it is meant to throw light on logic while writing code. Usually, people give up while designing the logic of a program, and they jump to the solutions. If the solution is not available in the desired language, it even becomes trickier to solve the mystery of the code.

  • Take a little time to understand the problem statement, then proceed with the logic.
  • Write the question on paper, then try to dry run and understand the problem.
  • Write pseudocodes and verify with the problem requirement.
  • Pick out the key constraints from the problem and the required time and space complexity.
  • Write a brute-force approach first, then start optimizing it by using different data structures.
  • Identify the corner cases where your applied algorithm can fail.
  • Don't jump straight to the solution. Retry as many times as possible. You can check your notes to see what data structure algorithm fits the issue and try to implement it.
  • Also, you can practice on a whiteboard and check the test cases.

3. Algorithms Drill

Learning data structure won't be enough, to level up, algorithms are much required to boost up your DSA skills. Before moving to algorithms, it is necessary to have data structures at your fingertips.

Mastering algorithms makes you a competitive programmer because at this level you learn to optimize the code to have minimal execution time. Below are some basic algorithms that are useful.

  • Graph algorithms: Breadth-first search (BFS), Depth-first search (DFS), Dijkstra algorithm, Floyd Warshall algorithm, Kruskal and Prim’s algorithm, topological sorting, etc.
  • Dynamic programming: Knapsack problem, the Longest common subsequence, longest increasing subsequence, subset sum problem, Partition problem, etc.
  • Searching and sorting: Binary search, merge and quick sort, KMP algorithm, counting sort, Manacher’s sorting, etc.
  • Number theory: Primality test, sieve of Eratosthenes, Segmented sieve, Wilson algorithm, Pollard rho algorithm.
  • Mathematical algorithms: Count inversions, square root decomposition, Catalan number, Hungarian algorithm, log exponentiation, etc.
  • Geometry and network flow: Convex hull, Graham scan, lie intersection, interval tree, stable marriage problem, Fulkerson algorithm, Edmon Karp algorithm, Dinic algorithm, etc.
  • Modulo algorithms: Euler totient algorithm, Modular exponentiation, Chinese remainder theorem, etc.

4. Less is More

A common mistake that most of the coders follow is to target more problems than their initial strength. When the target is not achieved, it leads to two drawbacks - demotivation and self-doubt.

Also, what happens is that in order to achieve the target the person does not go in-depth into the question and jumps straight to the conclusions.

  • Make a plan not to target too many questions in a day. Plan in such a way that you do all difficulty-level questions in a day. For example, solving 3 easy, 3 medium and 2 hard questions will help you maintain your pace and maintain continuity.
  • To complete the current target, do not jump straight into the solution. This will not improve the logical skills and will increase the dependency on the solution.
  • Make a pattern of questions in such a way that you cover more medium and hard-level questions. This will ultimately help you grind more.

5. Revise, Practice, and Participate

Revise the concepts as much as you can, and then practice variable test questions on the same. When you get a good understanding of a particular topic, participate and solve the questions on HackerRank, CodeChef, Leetcode. Engaging in participation will give you an idea of what a real-world coding round experience is.

  • Make short notes on a particular data structure with the time and space complexities of the insertion, update, deletion operations.
  • Engaging yourself in participation will make you understand the different judging parameters such as - is your syntax correct, are you able to solve in the time frame provided, are you understanding the problem statement and the required data structure to solve the question, etc.
  • Practice with online IDEs will make you comfortable with the online coding environment.
  • While participating in the contest, you will learn to optimize your code to a better space and time complexity.

Conclusion

Thus, to sum up, these five skills will help you to improve your data structures and algorithms. Maintaining continuity and also having a coding buddy would be a plus to make the coding journey smooth.


Written by sandeepmishratech | Tech Writer and Software Engineer
Published by HackerNoon on 2022/02/22