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How can you explain data structures to someone with no computer science background?

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Data structures are one of the most fundamental concepts in computer science. They are the ways of organizing and storing data in a computer, such as arrays, lists, stacks, queues, trees, graphs, and so on. Data structures can affect the efficiency, performance, and readability of your code, and they are often tested in coding interviews. But how can you explain data structures to someone who has no computer science background? Here are some tips and analogies that might help.

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Bijan Pourghorbani

PhD in Software Engineering | Data scientist | Machine Learning Engineer

1 Use familiar examples

One way to introduce data structures is to use examples from everyday life that are similar to how data structures work. For example, you can compare an array to a bookshelf, where each book has a fixed position and size, and you can access any book by its index number. Or you can compare a list to a chain of paper clips, where each clip can hold any amount of data, and you can add or remove clips from anywhere in the chain. Using familiar examples can help the listener visualize and understand the basic properties and operations of data structures.

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Bijan Pourghorbani

PhD in Software Engineering | Data scientist | Machine Learning Engineer
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Familiar Example is a concrete method for any subject. For this purpose we can use daily queue to describe array and queue. A stack of plates is also a good example to illustrate stack data structure. In addition, business pyramid can express the concept of tree and we can even provide exponential growth and the concept of complexity with its help. although network is complex concept, but we can explain it by using social network such as Whatsapp.

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2 Explain the trade-offs

Another way to explain data structures is to highlight the trade-offs between different choices. For example, you can explain that arrays are fast and easy to access, but they have a fixed size and are hard to resize or rearrange. On the other hand, lists are flexible and dynamic, but they require more space and time to traverse or search. You can also compare the advantages and disadvantages of different types of lists, such as singly-linked, doubly-linked, or circular lists. Explaining the trade-offs can help the listener appreciate the complexity and diversity of data structures.

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3 Show some code

A third way to explain data structures is to show some code examples that illustrate how data structures are implemented and used in programming languages. You can use pseudocode or a simple language like Python to demonstrate the syntax and logic of creating and manipulating data structures. For example, you can show how to create an array using brackets and commas, how to access or modify an element using its index, how to loop through an array using a for loop, and so on. You can also show how to create a list using nodes and pointers, how to insert or delete a node, how to reverse or sort a list, and so on. Showing some code can help the listener connect the abstract concepts with concrete examples.

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4 Relate to problems

A fourth way to explain data structures is to relate them to real-world problems that can be solved or improved by using data structures. For example, you can explain how stacks can be used to implement undo and redo functions in a text editor, how queues can be used to manage waiting lines or tasks in a printer, how trees can be used to store hierarchical data or perform searches, how graphs can be used to model networks or relationships, and so on. Relating data structures to problems can help the listener see the relevance and usefulness of data structures.

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5 Simplify and summarize

A fifth way to explain data structures is to simplify and summarize the main points and concepts. You can use diagrams, tables, charts, or mnemonics to help the listener remember and organize the information. You can also use analogies, metaphors, or stories to help the listener relate and recall the examples. You can also review the key terms, definitions, properties, and operations of data structures, and highlight the similarities and differences between them. Simplifying and summarizing can help the listener reinforce and retain the knowledge of data structures.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Roni Lazimi

Software Engineer II at Disney Streaming
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First, we need to talk about something known as an Abstract Data Type (ADT). That sounds complicated, but an ADT is simply something like a Queue, or a Stack, or any other kind of collection you'd see in real life. Without know any code at all, you know what these collections do. Stacks can be added to or removed from the top of for example. Now data structures exist to capture those ideas into code. That is the precise definition of a data structure: an ADT captured as code. Capturing these ideas in code is useful because it can let us do things like mimic a queue in an online shop for example. There are several different ways for ADTs to be coded, each with different tradeoffs, and each is known as a Data Structure.

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How can you explain data structures to someone with no computer science background?

1

2

3

4

5

6

1 Use familiar examples

2 Explain the trade-offs

3 Show some code

4 Relate to problems

5 Simplify and summarize

6 Here’s what else to consider

Computer Science

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How can you explain data structures to someone with no computer science background?

1

2

3

4

5

6

1 Use familiar examples

2 Explain the trade-offs

3 Show some code

4 Relate to problems

5 Simplify and summarize

6 Here’s what else to consider

Computer Science

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