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  1. 1 day ago · Map data structure (also known as a dictionary , associative array , or hash map ) is defined as a data structure that stores a collection of key-value pairs, where each key is associated with a single value.

  2. 4 days ago · An array is a fundamental data structure that stores a collection of elements, typically of the same data type, in a contiguous block of memory. Arrays allow for efficient access to elements using an index, making it easy to retrieve or update values.

  3. 3 days ago · Understanding these data structures is crucial for writing clean, efficient, and maintainable code. In this article, we’ll explore some of the fundamental data structures in JavaScript, including arrays, objects, sets, and maps. 1. Arrays. Arrays are one of the most commonly used data structures in JavaScript. They are ordered collections of ...

  4. 1 day ago · The Problem With Arrays To this point, we have been using arrays as our underlying data structures for implementing linear data structures such as stacks and queues. Given that with stacks and queues we only put items into the array and remove from either the start or end of the data structure, we have been able to make arrays work. However, there are some drawbacks to using arrays for stacks and queues as well as for more general data structures.

  5. 3 days ago · An array is a data structure that allows us to store and manipulate a collection of elements of the same data type. Arrays have a fixed size, determined during initialization, which cannot be altered during runtime. In this tutorial, we’ll see how to declare an array.

  6. 5 days ago · Complexity Analysis of Selection Sort. Time Complexity: The time complexity of Selection Sort is O (N2) as there are two nested loops: One loop to select an element of Array one by one = O (N) Another loop to compare that element with every other Array element = O (N) Therefore overall complexity = O (N) * O (N) = O (N*N) = O (N2) Auxiliary ...

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  8. 5 days ago · Learn Java data structures with easy-to-understand explanations and code examples. Covers arrays, lists, stacks, queues, trees, graphs, and hash tables.