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<p><u>Binary search</u> is an efficient search algorithm based on the divide-and-conquer strategy. It utilizes the orderliness of data, reducing the search range by half each round until the target element is found or the search interval is empty.</p>
<div class="admonition question">
<p class="admonition-title">Question</p>
<p>Given an array <code>nums</code> of length <span class="arithmatex">\(n\)</span>, with elements arranged in ascending order and non-repeating. Please find and return the index of element <code>target</code> in this array. If the array does not contain the element, return <span class="arithmatex">\(-1\)</span>. An example is shown below.</p>
<p>Given an array <code>nums</code> of length <span class="arithmatex">\(n\)</span>, with elements arranged in ascending order and non-repeating. Please find and return the index of element <code>target</code> in this array. If the array does not contain the element, return <span class="arithmatex">\(-1\)</span>. An example is shown in Figure 10-1.</p>
</div>
<p><a class="glightbox" href="../binary_search.assets/binary_search_example.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="Binary search example data" class="animation-figure" src="../binary_search.assets/binary_search_example.png" /></a></p>
<p align="center"> Figure 10-1 &nbsp; Binary search example data </p>
<p>As shown in the Figure 10-2 , we first initialize pointers <span class="arithmatex">\(i = 0\)</span> and <span class="arithmatex">\(j = n - 1\)</span>, pointing to the first and last elements of the array, representing the search interval <span class="arithmatex">\([0, n - 1]\)</span>. Please note that square brackets indicate a closed interval, which includes the boundary values themselves.</p>
<p>As shown in Figure 10-2, we first initialize pointers <span class="arithmatex">\(i = 0\)</span> and <span class="arithmatex">\(j = n - 1\)</span>, pointing to the first and last elements of the array, representing the search interval <span class="arithmatex">\([0, n - 1]\)</span>. Please note that square brackets indicate a closed interval, which includes the boundary values themselves.</p>
<p>Next, perform the following two steps in a loop.</p>
<ol>
<li>Calculate the midpoint index <span class="arithmatex">\(m = \lfloor {(i + j) / 2} \rfloor\)</span>, where <span class="arithmatex">\(\lfloor \: \rfloor\)</span> denotes the floor operation.</li>
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</details>
<p>As shown in the Figure 10-3 , in the two types of interval representations, the initialization of the binary search algorithm, the loop condition, and the narrowing interval operation are different.</p>
<p>As shown in Figure 10-3, in the two types of interval representations, the initialization of the binary search algorithm, the loop condition, and the narrowing interval operation are different.</p>
<p>Since both boundaries in the "closed interval" representation are defined as closed, the operations to narrow the interval through pointers <span class="arithmatex">\(i\)</span> and <span class="arithmatex">\(j\)</span> are also symmetrical. This makes it less prone to errors, <strong>therefore, it is generally recommended to use the "closed interval" approach</strong>.</p>
<p><a class="glightbox" href="../binary_search.assets/binary_search_ranges.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="Two types of interval definitions" class="animation-figure" src="../binary_search.assets/binary_search_ranges.png" /></a></p>
<p align="center"> Figure 10-3 &nbsp; Two types of interval definitions </p>