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Browse CoursesAlgorithms are step-by-step procedures or formulas for solving problems. In computer science, they serve as the blueprint for executing tasks, optimizing processes, and achieving desired outcomes. Proficiency in algorithms is crucial for efficient problem-solving and is fundamental to computer science and programming.
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Algorithms are step-by-step procedures or sets of rules designed to perform specific tasks or solve particular problems. In computer science, algorithms are often expressed as sequences of instructions that can be executed by a computer.
Algorithms are fundamental to computer science as they provide systematic and efficient solutions to problems. They form the basis for software development, enabling the creation of programs that can perform tasks ranging from simple calculations to complex data processing.
Time complexity measures the amount of time an algorithm takes to complete as a function of the size of the input. It helps analyze and compare the efficiency of algorithms, guiding developers in choosing the most suitable algorithm for a given task.
Sorting algorithms are categorized based on their approach to rearranging elements in a specific order. Common types include comparison-based sorting algorithms like Bubble Sort, Merge Sort, and Quick Sort, as well as non-comparison-based algorithms like Counting Sort and Radix Sort.
Space complexity measures the amount of memory an algorithm uses as a function of the input size. It is crucial for understanding how an algorithm scales with input growth. Efficient algorithms strike a balance between time and space complexity to optimize resource utilization.