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Data structures and algorithms are crucial for technical interviews as they reflect a candidate's problem-solving abilities, understanding of core principles in computer science, and capability to optimize code and handle large-scale systems. Proficiency in these areas also shows adaptability to new concepts and good communication skills.
You cannot build a software product without using a data structure. And you cannot scale a product without writing optimized code(logic/algorithm).
Why data structures and algorithms?
If you're applying for a Software Development Engineer (SDE) position, it's highly probable that you'll have to take part in a DSA round at some point.
Many companies prioritize DSA, including startups, fast-paced startups, and tech giants like FAANG (FaceBook, Amazon, Apple, Netflix, and Google). It is a crucial requirement for those who are interviewing with them. They use DSA to test your problem-solving skills. This is their way to test your coding knowledge.
Companies believe that if you are a good problem solver, you're a good coder.
Despite the introduction of new programming languages each year, the DSA skill remains unchanged.
For example, they are not interested in knowing the answer/algorithm if they give you a question. They are interested in your approach to the question and thought process. The thought process is a way to analyze a problem and come up with approaches to solve a problem.
During interviews, employers expect you to showcase your problem-solving abilities by breaking the issue into smaller parts and presenting sub-optimal solutions. They are interested in your thought process when approaching a problem.
Interviewers often focus on data structures and algorithms during technical interviews for several reasons:
- Problem-solving skills.
- Core concepts
- Efficiency and scalability
- Problem-solving approach
- Adaptability and learning skills
- Technical communication
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