As the saying goes, "Algorithms are the soul of programming." Whether it's Java, Python, or PHP, they can't cross the threshold of algorithms.
Many small partners see the variety of programming languages that some companies require when recruiting, and they have a misunderstanding. They think that learning computers is learning various programming languages, or that learning the latest languages, technologies, and standards is the best way to pave the way.
Although programming languages should be learned, it is more important to learn computer algorithms and theories, because computer languages and development platforms are changing with each passing day, but those algorithms and theories are always changing. Such as data structure, algorithm, compilation principle, computer architecture, relational database principle and so on.
These basic courses can be called "internal skills", while the new language, technology, and standards are more like "external skills." Those who follow the trend all day only know how to move. Without the skill, it is impossible to become a master.
It is understood that the requirements for technical interviews of many large companies are: good technology, solid computer foundation, proficiency in algorithms and data structures, language is not important, proficiency is very important. In every round of technical interviews, it is possible to test the code, not only the algorithm, but the algorithm will definitely be tested.
Why are big companies interviewing algorithms?
Here we introduce the opinions of a Meituan interviewer
Meituan senior engineer Windy:
Through the investigation of algorithmic interview questions, I hope that candidates can not only demonstrate their programming skills, but also demonstrate their communication skills and deduction skills (how to construct ideas) by understanding the questions in detail. The most critical programming ability, candidates can show their thinking about the boundary of the problem, compare the performance and efficiency of different methods, and give a variety of ways to solve the problem.
What is the most important thing about learning algorithms?
In the process of learning algorithms, one can solve the problem, and the other is useful to oneself, which is the biggest driving force. And those abstract competition questions that have little to do with the programmer's daily work, it is difficult to raise the interest of most people in learning. It is best to cut in through some cases applied in the work, and use the fragmented time entry algorithm to enhance technical competitiveness. Once you are interested, you can try to optimize the algorithm as much as possible and apply it to a complete project.
Is there a general idea for algorithm implementation?
The purpose of people designing various algorithms is to solve practical problems. Although various algorithms are implemented in various ways, there are some general methods or ideas in algorithm design patterns. In summary, these common algorithm design methods include iterative method, exhaustive search method, branch and bound method (pruning method), recursion method, recursion method, backtracking method, divide and conquer method, greedy method and dynamic programming method.
How to learn algorithms?
In order to help everyone learn the algorithm well, I asked the ByteDance interviewer for two super nice algorithm interview notes. Now they are free to share with everyone. After the friends who need it forward the article, click on the portal ! !
Data structure and algorithm notes
The contents of this note are all purely hand-written. The code of the sorting algorithm/data structure may not be the optimal solution. The implementation of the code is written in a way that is easier to understand. Almost every code has a corresponding comment, which should be understandable.
Six, Hill sort
Seven, heap sort
Zuo Shen "Programmer Code Interview Guide"
The books involve more than 240 questions about algorithm and data structure programming, and the individual has achieved the best solution. Most of the questions are frequently interviewed.
Directory (the algorithm is divided into four levels: general, school, lieutenant, and scholar to indicate the degree of difficulty)
Chapter 4 Recursion and Dynamic Programming
Recursion and dynamic programming of the Pebonacci series of problems (will ★★★★)
The minimum path sum of the matrix (Wei ★ ★)
The minimum amount of currency to exchange money (Wei ★ ★)
The number of ways to exchange money (Wei ★ ★)
The longest increasing subsequence (school ★★★)
The Tower of Hanoi Problem (School ★★★)
The longest common subsequence problem (Wei★★)
The longest common substring problem (school ★★★)
Minimum editing cost (small ★★★)
Interleaved composition of strings (school ★ ★ ★)
Dungeons and Dragons game problems (Wei ★ ★)
Number of character strings converted to letter combinations (Wei ★ ★)
The number of components that the expression obtains the expected result (school ★ ★ ★)
The problem of a lined card game (Wei ★ ★)
Jumping game (person ★)
The longest consecutive sequence in the array (Wei ★ ★)
Queen N Problem (School★★★)
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