WEBVTT

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In this video, we will understand why searching is needed in computing.

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Describe how linear and binary search work.

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Choose the right search method for different data sets.

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Why searching matters?

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Searching is a fundamental operation in computers.

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We use it constantly, looking up a contact, locating a file, or finding items in a large inventory system.

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But the speed of a search depends on how the data is organized.

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If items are unsorted, we may need to check each one.

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If the data is sorted, we can skip large portions at once.

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To make searching efficient, we choose the right algorithm for the right situation.

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Linear search.

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Linear search is the simplest method.

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We start from the first element and check each item one by one until the target is found.

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It works well with small or unsorted data sets.

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But as the data set grows larger, the number of checks grows too.

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Worst case performance is O of N, meaning more data equals more time.

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However, it requires no extra memory, so its space complexity is O of 1.

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Binary search.

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Binary search is much faster, but only if the data is sorted.

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Instead of checking each item, it repeatedly divides the list into halves.

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We compare the middle element to the target and eliminate half the list each step.

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This gives O log N time complexity, making it ideal for large data sets.

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Binary search is used in databases, phone directories, and many real-time systems.

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Choosing the right algorithm.

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Linear search is best when data is unsorted.

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The list is small, the data updates frequently.

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Binary search is best when data is sorted.

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Speed is important. The data set is large and mostly unchanged.

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Searching helps us find information quickly.

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Linear search is simple for small or unsorted data, while binary search is faster for large-sorted data.

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Choosing the right method improves performance.