Data Structures

Data structures and algorithms are a fundamental of computer science. For example, a red-black tree is the same whether it's implemented in Java, C++, or Python. According to some experience software engineers, you may never implement a Big-O notation in your career life. So, it's rather to understand how a binary search tree works, it will likely benefit you in the job interview, as well as your software development career. It's better to know one programming language but you have deeper knowledge in data structures and algorithms and how they work rather than knowing a few programming languages but don't know how to apply data structures or find a best solution to solve a given problem. Often time, once you know well in one programming language, you can easily pick up another language in a short time.

The software developer can apply data structures and algorithms to define and solve complex problems. Knowing the data structures exist is not enough, but knowing these details will better prepare developer to understand when it is appropriate to use one data structure over another. The most common abstractions for data collections are stacks, queues, lists, trees, maps, and hash. Lists and maps offer some valuable features, but they come with costs. And if we use the wrong one can significantly undermine the performance of the software. 

Knowledge of data structures and algorithms is an important part of software developer’s skill set because data structures and algorithms are very important when coding. To be able to develop robust, efficient and reusable code, the software developers need to know the design and analysis of efficient data structures and algorithms. They also need to know the disadvantage and advantage of the different types of data structures and algorithms. So, how do you strengthen your knowledge of data structures and algorithms? 

 

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