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rohini college of engineering and technology unit i ge8151 problem solving and python programming algorithmic problem solving algorithms are procedural solutions to problems algorithmic problem solving is defined as the ...

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                               ROHINI COLLEGE OF ENGINEERING AND TECHNOLOGY  
     UNIT I (GE8151 PROBLEM SOLVING AND PYTHON PROGRAMMING) 
     ALGORITHMIC PROBLEM SOLVING 
      
       Algorithms are procedural solutions to problems. Algorithmic problem solving is defined as the 
     formulation  and  solution  of  problems  where  solution  involves  the  principles  and  techniques  to 
     construct  the  correct  algorithms.  It  means  that  solving  problems  that  require  formulation  of  an 
     algorithm for their solution. 
     Steps in designing and analyzing an algorithm 
       The steps are 
          i) Understanding the problem 
          ii) Ascertaining the capabilities of a computational device 
          iii) Choosing between exact and approximate problem solving 
          iv) Deciding on appropriate data structures. 
          v) Algorithm design techniques 
          vi) Methods of specifying an algorithm. 
          vii) Proving an algorithm’s correctness. 
          viii) Analyzing an algorithm. 
          ix) Coding an algorithm. 
       i) Understanding the problem 
          →Before designing an algorithm, you need to understand the problem completely. 
          →Read the problem description carefully. 
          → Check if it is similar to some standard problems and if a known algorithm exists. 
          →Ask Questions if you have any doubts and do a few small examples by hand. 
          →Think about special cases. 
          →Ask Questions again if needed. 
                              GE8151 PROBLEM SOLVING AND PYTHON PROGRAMMING  
                                                                      ROHINI COLLEGE OF ENGINEERING AND TECHNOLOGY  
            
                                                   Understand the problem 
                                                                                
            
                                                  Decide on: computational 
                                                           means, 
            
                                                 Algorithm design techniques 
            
            
            
                                                
                                                     Design an algorithm 
                                                      Prove correctness         
                                                                                
            
            
            
                                                    Analyze the algorithm 
            
                                                      Code the algorithm 
            
            
            
            
                              Fig 1: Steps in designing and analyzing an algorithm 
            
               ii) Ascertaining the capabilities of a computational Device 
            
                      The second step is to ascertain the capabilities of a machine. 
               Sequential algorithms: 
                       → The essence of von-Neumann machines architecture is captured by RAM; here the 
               instructions are executed one after another, one operation at a time. 
                                                                  GE8151 PROBLEM SOLVING AND PYTHON PROGRAMMING  
                               ROHINI COLLEGE OF ENGINEERING AND TECHNOLOGY  
          →Algorithms designed to be executed on such machines are called sequential algorithms. 
       Parallel algorithms: 
          → An algorithm which has the capability of executing the operations concurrently   
       is called parallel algorithms. 
          → RAM model doesn’t support this. 
       iii) Choosing between exact and approximate problem solving 
      
          →The next decision is to choose between solving the problem exactly or solving it 
       approximately. 
          →Based on this, the algorithms are classified as exact and approximation algorithms. 
       Exact algorithms: 
      
          → The algorithms that can solve the problem exactly are called exact algorithms. 
      
       Approximate algorithms: 
      
          →The algorithms that can solve the problem not exactly are called approximate 
       algorithms. 
          →There are three issues to choose an approximation algorithm. 
          →First, there are certain problems like extracting square roots, solving  non-linear 
       equations which cannot be solved exactly. 
          →Secondly, if the problem is complicated it slows the  operations.  E.g.  Traveling  
       salesman problem. 
          →Third, this  algorithm  can  be  a  part  of  a  more  sophisticated  algorithm  that  solves 
       a problem exactly. 
       iv) Deciding on appropriate data structures 
      
          →Data structures play a vital role in designing and analyzing the  algorithms. 
          →Some of the algorithm  design techniques also depend on the structuring  data specifying 
       a problem’s instance. 
                     Algorithm + Data structure = Programs 
       v) Algorithm design techniques 
      
          →An algorithm design technique is a general approach to solving problems 
       algorithmically that is applicable to a variety of problems from different areas of computing. 
                              GE8151 PROBLEM SOLVING AND PYTHON PROGRAMMING  
                                                    ROHINI COLLEGE OF ENGINEERING &TECHNOLOGY 
        
                →Learning these techniques is important for two reasons. 
                     i) First, they provide guidance for designing for new problems. 
                     ii) Second, algorithms are the cornerstones of computer science. 
           vi) Methods of specifying an algorithm 
              Once you have designed an algorithm, you need to specify it in some fashion. 
           There are two options for specifying algorithms. 
                → Pseudo code 
                → Flowchart 
             Pseudo code is a mixture of a natural language and programming language. It is more 
             precise. 
             Flowchart is a method of expressing an algorithm by a collection of connected geometric 
             shapes containing descriptions of the algorithm’s steps. 
           vii) Proving an algorithm’s correctness 
        
                →Once an algorithm has been specified, you have to prove its  correctness. 
                →You have to prove that the algorithm yields a required result for every legitimate input 
           in a finite amount of time. 
                →A common technique for proving correctness is to use mathematical induction. 
           viii) Analyzing an algorithm 
        
                → Our algorithm should possess several qualities. 
                → Analysis of algorithms and performance analysis refers to the task of determining how 
           much computing time and storage an algorithm requires. 
                →After correctness, the most important quality of an algorithm is Efficiency. 
                →There are two kinds of algorithm Efficiency. 
                     i) Time efficiency: It indicates how fast the algorithm runs. 
                     ii) Space efficiency: Indicates how much extra memory the algorithm needs. 
           ix) Coding an algorithm 
                → Algorithms are implemented as computer programs. 
                → Verification and validation is done for error correction. 
        
        
                                               GE8151-PROBLEM SOLVING AND PYTHON PROGRAMMING 
        
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...Rohini college of engineering and technology unit i ge problem solving python programming algorithmic algorithms are procedural solutions to problems is defined as the formulation solution where involves principles techniques construct correct it means that require an algorithm for their steps in designing analyzing understanding ii ascertaining capabilities a computational device iii choosing between exact approximate iv deciding on appropriate data structures v design vi methods specifying vii proving s correctness viii ix coding before you need understand completely read description carefully check if similar some standard known exists ask questions have any doubts do few small examples by hand think about special cases again needed decide prove analyze code fig second step ascertain machine sequential essence von neumann machines architecture captured ram here instructions executed one after another operation at time designed be such called parallel which has capability executing o...

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