![]() In binary search we take a sorted list of elements and start looking for an element at the middle of the list. The following program is an example of divide-and-conquer programming approach where the binary search is implemented using python. This algorithmic approach works recursively and conquer &s merge steps works so close that they appear as one. When the smaller sub-problems are solved, this stage recursively combines them until they formulate a solution of the original problem. Generally, at this level, the problems are considered 'solved' on their own. This step receives a lot of smaller sub-problems to be solved. At this stage, sub-problems become atomic in nature but still represent some part of the actual problem. ![]() ![]() This step generally takes a recursive approach to divide the problem until no sub-problem is further divisible. Sub-problems should represent a part of the original problem. This step involves breaking the problem into smaller sub-problems. The solution of all sub-problems is finally merged in order to obtain the solution of an original problem.īroadly, we can understand divide-and-conquer approach in a three-step process. Those "atomic" smallest possible sub-problem (fractions) are solved. When we keep on dividing the subproblems into even smaller sub-problems, we may eventually reach a stage where no more division is possible. In divide and conquer approach, the problem in hand, is divided into smaller sub-problems and then each problem is solved independently. Python Data Structure & Algorithms Useful Resources.Python Data Structure and Algorithms Tutorial.
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