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Aspiring Software Engineers often work on improving their programming skills through two primary methods, Competitive Programming (CP) & Interview Prep (IP). While both techniques have similarity when it comes to problem-solving and algorithms, they have separate objectives, and therefore use different approaches to teach you how to solve problems using both methods; most learners believe that if they excel in one method, they will also excel in the other; however, this is not true. Although the two methods share some similarities, their objectives are altogether different from one another.  Introduction to Competitive Programming Competitive programming refers to the competitive environment in which participants have to solve a given/ prescribed algorithmic problem (or problems) in a limited amount of time (generally minutes). Events like coding contests/programming competitions allow participants to create sustained optimal solutions to algorithmic problems in a relatively sh...

For any aspiring software engineer who is preparing for a coding interview or competing in programming contests or pursuing a career in software engineering, the study of Data Structures and Algorithms continues to be a major area of emphasis. Many hours will go into developing your knowledge and skill development of data structures and algorithms regardless of how your career evolves in software engineering. In recent years, the use of Artificial Intelligence has had a hugely positive impact on the learning and training processes and has assisted students by providing them with their own personal coach and immediate feedback on their progress. Therefore, many people are now asking themselves if studying DSA using An AI is better than studying DSA without using An AI (the traditional method).  There are no definitive answers, as both the AI and traditional methods each have advantages and disadvantages. Traditional DSA Preparation In a traditional DSA preparation, you would typical...

Coding interviews usually serve as the doorway into getting hired by big tech companies. In order to be successful during coding interviews, many students spend months preparing for their coding interview by solving hundreds of DSA problems. However, after dedicating all of this time and energy, many students still do not perform well on their coding interview. Therefore, the question must be asked: Why do students fail at their coding interviews even if they practice solving hundreds of problems?  The answer for this is simple: While preparing for a coding interview, there is much more to preparing than just solving a large number of coding problems. Quality vs Quantity One of the main mistakes that most students make while preparing for a coding interview is that they prepare for it using a quantity-based approach to solving problems. For example, if a student solves 500 coding problems, it is of little use if they do not understand how to solve those problems or only have memori...

At the center of successfully creating software lies DSA. While many entry-level engineers will often spend time solving many different coding challenges, experienced engineers will see that the majority of interview and real-world issues will actually fall under a common pattern. By knowing how to identify these patterns, you can solve problems much quicker and write more efficient code. These are the 50 DSA patterns that you should be aware of. Patterns for Arrays & Strings Two Pointer Pattern Sliding Window Pattern Prefix Sum Pattern Suffix Sum Pattern Difference Array Pattern Kadane's Algorithm Dutch National Flag Problem Merging Intervals Pattern Cyclic Sorting Pattern Monotonic Array Processing Hashing is a means of performing fast searches through which many algorithms will experience reduced time complexity compared to other types of storage List Patterns Interview Question Examples Fast / Slow Pointer Strategy Algorithm to Reverse a List How to Combine Two Lists Cycle ...

Algorithms play an essential role in the field of computer science. They are used in many applications including searching engines, social media and other web-based systems, as well as AI and cyber security systems. Still, there are many students and software engineers who struggle to understand algorithms despite their efforts. There is empirical evidence from the cognitive sciences and education psychology that shows working harder does not lead to learning. One should employ effective methods of learning which were proved to be successful during intensive scientific research to improve understanding and retention. Why Is It So Difficult To Learn Algorithms? Learning coding is more than just memorization of the solutions. It is more about critical thinking, identification of the problem, abstract thinking and its practical application. Many people study by simply watching tutorials and memorizing solutions to the problem. However, this approach does not work at all. According to rese...

Technology recruitment industry is constantly evolving. There are no more such coding interviews where companies will value everything else except your ability to solve problems. However, by 2026, top companies will evaluate various skills that become increasingly characteristic of software engineering profession. Understanding what they actually value might play a vital role for your career development. 1. Problem-solving Skills Problem-solving is the core of all coding interviews. Companies want to see how you tackle a given task, recognize the limitations and devise the most optimal strategy possible in the shortest time frame. The knowledge of DSA may still be useful but it is more important how efficiently you solve problems and the thought process behind it. 2. Solid Knowledge of Data Structures and Algorithms Companies like Google, Facebook, Amazon, and others use the concepts taught in DSA when conducting interviews of software engineers and other positions where data structure...