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		<title>Data structure and algorithm</title>
		<link>https://mitindia.in/data-structure-algorithm/</link>
		
		<dc:creator><![CDATA[SKB]]></dc:creator>
		<pubDate>Sun, 20 Nov 2016 07:36:04 +0000</pubDate>
				<category><![CDATA[C Programming]]></category>
		<category><![CDATA[C++]]></category>
		<category><![CDATA[algorithm]]></category>
		<category><![CDATA[cpp]]></category>
		<category><![CDATA[data structure]]></category>
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					<description><![CDATA[<p>Data Structures A data structure is a logical method of representing data in memory. Data structure is strictly described as an instance of an Abstract Data Type (ADT). An Abstract Data Type is defined as a mathematical model of a user-defined type along with the operations performed on that model. Data Structure Strengths Weaknesses Array [&#8230;]</p>
<p>The post <a href="https://mitindia.in/data-structure-algorithm/">Data structure and algorithm</a> appeared first on <a href="https://mitindia.in"></a>.</p>
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										<content:encoded><![CDATA[<h3>Data Structures<img decoding="async" class="alignright" src="http://image.slidesharecdn.com/lecture1-m-131122062232-phpapp02/95/lecture-1-data-structures-and-algorithms-1-638.jpg?cb=1385105034" alt="Image result for data structures and algorithms" width="177" height="133" /></h3>
<ul>
<li>A data structure is a logical method of representing data in memory.</li>
<li>Data structure is strictly described as an instance of an Abstract Data Type (ADT).</li>
<li>An Abstract Data Type is defined as a mathematical model of a user-defined type along with the operations performed on that model.</li>
</ul>
<table border="1" width="650">
<tbody>
<tr>
<td width="169"><strong>Data Structure</strong></td>
<td width="334"><strong>Strengths</strong></td>
<td width="254"><strong>Weaknesses</strong></td>
</tr>
<tr>
<td width="169">Array</td>
<td width="334">Fast access if index is known</td>
<td width="254">Slow search, fixed size</td>
</tr>
<tr>
<td width="169">Stack</td>
<td width="334">Features last in – first out access</td>
<td width="254">Slow access to other elements</td>
</tr>
<tr>
<td width="169">Queue</td>
<td width="334">Features first in – first out access</td>
<td width="254">Slow access to other elements</td>
</tr>
<tr>
<td width="169">Linked list</td>
<td width="334">Quick insertion and deletion</td>
<td width="254">Slow search</td>
</tr>
<tr>
<td width="169">Binary tree</td>
<td width="334">Quick insertion, deletion and search when tree is balanced</td>
<td width="254">Deletion procedure is complex</td>
</tr>
<tr>
<td width="169">Hash table</td>
<td width="334">Fast insertion and access if key is known</td>
<td width="254">Inefficient memory usage, slow access if key is not known</td>
</tr>
<tr>
<td width="169">Heap</td>
<td width="334">Fast insertion, deletion and access to largest element</td>
<td width="254">Slow access to other elements</td>
</tr>
<tr>
<td width="169">Graph</td>
<td width="334">Simulates real world problems</td>
<td width="254">Some algorithms are slow and complex</td>
</tr>
</tbody>
</table>
<h5>Algorithm</h5>
<p>An algorithm can be described as sequence of steps or instructions required to solve a given problem.</p>
<p>It is a finite set of instructions written to accomplish a particular task.</p>
<p>When designing an algorithm, one must ensure that the</p>
<p>algorithm adheres to the following criteria:</p>
<p>Input: Some input data (can be empty in some cases) externally supplied to the algorithm</p>
<p>Output: At least one output is produced</p>
<p>Finiteness: The algorithm must terminate after finite number of steps</p>
<p>Definiteness: The instructions must be clear and unambiguous</p>
<p>Effectiveness: Every instruction must be basic enough to be carried out on paper</p>
<p><strong>Following are certain points to be considered</strong></p>
<p>while writing an algorithm :</p>
<p>Representing an algorithm.</p>
<p>Designing an algorithm.</p>
<p>Analyzing an algorithm.</p>
<p><strong>Algorithm Analysis</strong></p>
<p>Algorithm Analysis involves comparing different algorithms written for a specific problem. All the algorithms are compared for their space and time complexities.</p>
<p>Space complexity: It refers to the amount of storage the algorithm consumes.</p>
<p>Time complexity: It is the time required by the algorithm for execution.</p>
<p><strong>Following are the different types of time complexities:</strong></p>
<p>Best-case time complexity: It is the measure of minimum time required for an algorithm to execute for a known input size.</p>
<p>Average case time complexity: Average time complexity is the measure of time an algorithm will require to execute, for a typical input data size. This method requires statistical calculations.</p>
<p>Worst-case time complexity: It is the measure of maximum time required for an algorithm to execute for a known input size.</p>
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