How to improve data structure skills?

How to improve data structure skills?

5 min read
How to improve data structure skills Learning dat

Learning data structures and algorithms is a core foundation for code writing. Being competent in these fields can help you effectively program and demonstrate strong problem-solving skills to prospective employers.

If advancing your career and getting a better position in the programming industry is your New Year's resolution then keep reading because this text is for you! In this article, we are about to explore why data structures and algorithms are important and how to enhance those skills.

Purpose of structures and algorithms

Data structures and algorithms play a crucial role in addressing practical challenges. As an illustration, while developing a website, utilizing a binary tree might be necessary to establish the hierarchical structure of web pages.

These components serve as a mechanism for gathering and organizing data in a manner that facilitates efficient operations. They help us in structuring raw data in an orderly way, ensuring convenient accessibility for various applications. On the other hand, algorithms are predefined procedures or sequences of steps imparted to a system to solve a problem or accomplish a specific task.

Importance of data structures and algorithms

By investing in learning data structures and algorithms, you demonstrate a proactive problem-solving approach.

Proficiency in applying these principles can make your career prospects faster within the programming field and distinguish you as a candidate by setting you apart from other candidates, increasing your chances of getting the role you seek.

Let’s go through some of the methods that will help you to master data structures effectively.

Foundation for advancement

The initial step toward enhancing your proficiency in algorithms and data structures is to build a strong foundation. Be sure that you understand the basics.

For instance, in comprehending tree structures, it is imperative that fundamental terminologies are clear, like branches, siblings, and left and right subtrees.

You can start by delving into essential data structures such as arrays, linked lists, binary trees, hash tables, graphs, stacks, queues, and heaps. Acquire insight into how data is represented in computers, laying the groundwork with rudiments of digital logic design, boolean algebra, computer arithmetic, and cache design.

Additionally, familiarize yourself with diverse algorithms such as the pigeonhole principle, square root decomposition, set theory, bitwise operations, graph theory, dynamic programming, or greedy algorithms.

To explore more about topics of study you can visit numerous blogs and articles, video tutorials, or forums that can help you dive into various use cases and proper terminology like Joberty Blog or Joberty Community.

Work on logic building

When we discuss the enhancement of programming skills, the emphasis lies on cultivating logical ability while writing code. Often, individuals prematurely abandon the process of constructing a program's logic, hastening toward solutions. To master your data structure and then coding skills you must pay attention to the logic behind the process of solving the mystery of code.

Some ways to improve this segment are to take time to understand what is the problem, write the question on paper, and draft pseudocode as a means to align with the problem's requirement. This practice aids in pre-visualizing the program's logic before coding. Additionally, studying fellow programmers' code to become aware of diverse problem-solving methodologies and approaches proves beneficial. Significantly, consistent practice is crucial in this domain.

Master each data structure

Learn to integrate various data structures into your programming language of choice. It is often a question but there isn't a single "best" language for data structures. You can choose any programming language like C++, Java, or Python.

Large companies are typically more open to multiple languages, with object-oriented languages like Java being preferable. Smaller companies or startups, on the other hand, might have specific language preferences based on their needs.

When it comes to interviews, some developers recommend picking a language you're good/comfortable at and sticking with it. In case you lack a preferred language, mentioned C/C++, Java, or Python are generally good choices.

Increase your problem-solving ability

The question of how many problems need to be solved to achieve proficiency in data structures is a common one. The exact number is difficult to determine, but it's important to prioritize quality over quantity.

Although there's no strict limit on the number of problems to solve, a beneficial strategy involves progressing from simpler to more difficult problems to strengthen your understanding. A suggested approach may involve 15 easy problems, followed by 10 problems of moderate complexity, and finally, tackling a minimum of five challenging problems.

Throughout the problem-solving journey, you might find that some days you are stuck with certain problems while on other days you are super efficient. This variation is normal. Note to mark the problems that posed difficulties and return to them after 10-20 days to try to solve them again. Such an approach helps improve your problem-solving skills and your self-confidence as well.

Work on spaced repetition

Mastering problem-solving relies on consistent practice and the application of spaced repetition. It is a memory technique involving revisiting and recalling concepts at optimal intervals until they are completely learned.

How does it work?

After initially solving a problem, revisit it in a few days, then again after a couple of weeks, and subsequently, in a month. Gradually extending the intervals between practice sessions aids in enhancing retention.

A suggested method involves solving the problem after four days, followed by another attempt within 10 days, and finally revisiting it after a month. Over time, this pattern will naturally develop into a habit, ensuring concepts are reviewed at ideal spacing intervals.

Notice the patterns

Approaching new problems involves applying previously learned concepts in different combinations and you've already tackled a sufficient number of problems across various subjects. Through extensive practice, you'll start recognizing patterns.

For instance, after working on five problems utilizing binary search, you can extract this code segment. Memorize it and practice through spaced repetition. This refined code can later be implemented to address future problems and challenges.

Adopting this strategy offers several advantages, including your ability to swiftly write error-free code, adapt it to new situations, and restructure the code to new problems quickly.

Practice more and in multiple ways

Frequent revision of concepts and practicing diverse test questions reinforces your understanding. A lot of interactive online platforms offer questions and coding contests, where you challenge yourself and learn from others' practice too. HackerRan, CodeChef, or LeetCodeare are among the most popular.

Engaging in coding contests offers real-world experience and cultivates comfort in the digital coding realm. At the same time, it tests your skills under various criteria like syntax accuracy, problem comprehension, or time efficiency.

Having a coding partner is another practicing approach that can fulfill your coding journey in mastering your skills.

Try also to practice beyond computer screens and challenge yourself with pen-and-paper coding. This uncovers your coding strengths and weaknesses, encouraging you to plan your code and learn the correct language syntax and data structure grasp. Besides that, many interviews require whiteboard practice which demands preparation.

Testing your knowledge

During problem-solving, it's common to encounter challenges such as surpassing time limits, incorrect solutions, and runtime errors. These issues often arise due to the lack of thorough testing of algorithm efficiency, accuracy, time complexity, etc.

Testing your data structures and algorithms skills and knowledge holds equal significance to the process of learning them. Engaging in online quizzes and evaluations through different online platforms can help you review concepts and obtain constructive feedback.

Technical interviews for different roles in software development frequently incorporate inquiries related to data structures and algorithms, so it's beneficial to evaluate your code using the sample test cases provided by the interviewer. To hone your skills, platforms like Interview Cake or Pramp, offer the opportunity to practice and simulate such interviews.


Understanding data structures empowers us to use and manage data efficiently, resulting in well-organized and responsive programs. Given their essential role, do not hesitate to keep learning these skills. They help you to navigate complex coding scenarios with creativity and efficiency.

Do you have experience in learning data structure skills? Share your thoughts on this topic with the Joberty community and good luck in 2024!


[10:27 AM]