"Data Structures and Algorithms are of course important: considered broadly, they are the two ingredients that make up all programs. But in my opinion, "DSA" as an abstract field of study is over-emphasized. I understand why people focus on DSA: it's a concrete thing to learn about, there are web sites devoted to testing you on it, and most importantly, because job interviews often involve DSA coding questions."
"But I hope companies hiring entry-level engineers aren't asking them to reverse linked lists or balance trees. Asking about techniques that can be memorized ahead of time won't tell them anything about how well you can work. The stated purpose of those interviews is to see how well you can figure out solutions, in which case memorization will defeat the point."
DSA is often over-emphasized relative to its practical use in everyday software engineering. People focus on DSA because it is concrete, supported by many websites, and prominent in hiring processes. Memorizing algorithmic tricks for interviews can defeat the purpose of assessing problem-solving ability. Real-world software seldom requires implementing contest-style algorithms; knowing basics and trade-offs matters more. Data structures organize data—learn arrays, linked lists, hash tables, and trees and their trade-offs. Algorithms are ways to manipulate data; understand algorithmic thinking and complexity. Investing time in testing and practical engineering skills yields better long-term value than rote DSA drilling.
Read at Nedbatchelder
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