Problem solving Wk1 Introduction to Problem-Solving I.pptx.pdf

DEPARTMENT OF COMPUTER SCIENCE Introduction to problem solving i DR JEREMIAH O. BANDELE PhD Electrical/Electronic Engineering University of Noingham  DEPARTMENT OF COMPUTER SCIENCE Learning objectives At the end of this lesson, you should be able to: Describe the concep...

DEPARTMENT OF COMPUTER SCIENCE Introduction to problem solving i DR JEREMIAH O. BANDELE PhD Electrical/Electronic Engineering University of Noingham  DEPARTMENT OF COMPUTER SCIENCE Learning objectives At the end of this lesson, you should be able to: Describe the concept of problem-solving in computer science. Discuss various computational problem types. Outline the four steps to problem-solving. Develop a solution plan by applying computer programming concepts. Problem-solving in computer science The essence of computer science is problem-solving. Problems can be real world problems or abstract problems. To solve these problems with a computer, a systematic approach is required. We need a systematic approach because the computer also processes information in a systematic manner. How do computers solve problems ? Before a computer can be used to solve problems, the problems must be programmed (by a programmer) into a form that the computer understands. Before a programmer can carry out this task, the programmer must first understand how the problem can be solved by a human. So why do we need the computer since a human can solve the problem? The computer is able to handle larger problem volumes faster and more efficiently. How do computers solve problems ? After the problem to be solved is programmed as inputs, the inputs are passed to the computer using input devices such as keyboard, mouse, joystick and an external memory device. How do computers solve problems ? The computer processes the input in its central processing unit (CPU). How do computers solve problems ? The computer provides the result with output devices such printer, monitor, loudspeaker and sound card. Computational problem Problems with step-by-step solutions are computational problem. With computational problems, the inputs, problem limitations and output conditions are well defined. We will now discuss four types of computational problems: Decision problems: These are problems where the solution can either be YES or NO Search problems: These are problems where the solution is a value or values with a particular property. Computational problem types We will now discuss four types of computational problems: Decision problems Search problems Optimization problems Counting problems Computational problem TYPES Decision problems: These are problems where the solution can either be YES or NO Search problems: These are problems where the solution is a value or values with a particular property. Computational problem types Optimization problems: These are problems where the best possible solution is accepted as the solution. Counting problems: These are problems where the solution is determining the number of values with a particular property. Four steps to problem-solving Understand the problem Create a solution step-by-step plan Carry out the solution plan Evaluate and refactor the solution understanding the problem Before trying to solve any computational problem, a thorough understanding of the problem is essential Answers must also be provided to questions such as: What are the inputs? What are the processes involved? What is the output? What can the computer accept as input? With the help of input devices, computers will accept anything that can be converted to a digital form as inputs. These can include the following; Numbers Letters Pictures Music Videos Sound waves Retinal scans Wi-fi signals What can the computer accept as input? After the CPU processes the inputs, the computer uses output devices to create various outputs. These can include the following; Printed documents On-screen data Visuals Audio Digital music files Digitized speech Charts and graphs Images Creating a step-by-step solution plan After the problem is well understood, the next step is to create a step-by-step solution plan. A step-by-step plan usually involves a process of breaking down the main problem into smaller problems until the problems are small enough to be solved. Solving all the small problems automatically solves the main problem Creating a step-by-step solution plan Creating a solution plan to problems involves preparing algorithms and representing them with pseudocodes and flowcharts. Algorithm An algorithm is a procedure of steps used to solve a given problem. The steps must be ordered, unambiguous and complete so that it can easily be converted into a computer program. Algorithm Example 1: Write an algorithm that calculates the final grade of a student. The algorithm should also show whether the student has passed or failed. Note that the average of five grades is used as the final grade and the pass mark is 45. Pseudocode A pseudocode is the textual representation of an algorithm. Pseudocodes are written in a form that makes them easily convertible into programming statements. Even though that look like the actual program, they cannot be compiled or executed by the computer. Pseudocode Example 2: Write a pseudocode for the algorithm written in example 1. Flowchart A flowchart is the graphical representation of an algorithm. The flowchart is a graphical representation of the sequence of operations in a computer program. Flowcharts use symbols to describe actions such as start, stop, input, process, merge and decision. Flowchart Example 3: Create a flowchart for the algorithm written in example 1. START Input G1,G2,G3,G4,G5 Grade = (G1+G2+G3+G4+G5)/5 Is Grade > 44 Print Print “FAIL” “PASS” STOP FURTHER READING RESOURCES Bransford, J. D., & Stein, B. S. (1993). The IDEAL problem solver. Treffinger, D. J., Isaksen, S. G., & Stead-Dorval, K. B. (2006). Creative problem solving: An introduction. Prufrock Press Inc. Goodrich, M. T., & Tamassia, R. (2015). Algorithm design and applications (Vol. 363). Hoboken: Wiley. FURTHER READING RESOURCES Shaffer, C. A. (1997). A practical introduction to data structures and algorithm analysis. Upper Saddle River, NJ: Prentice Hall. Chaudhuri, A. B. (2020). Flowchart and algorithm basics: The art of programming. Mercury Learning and Information. Chaudhuri, A. B. (2005). The Art of Programming Through Flowcharts & Algorithms. Firewall Media. REFERENCES "Flying Magazine". Flying: 36–June 1963. ISSN 0015-4806. "Human Powered Flight Group Webpage". Royal Aeronautical Society. 2011. Retrieved 18 January 2021. Bransford, J. D., & Stein, B. S. (1993). The IDEAL problem solver. Treffinger, D. J., Isaksen, S. G., & Stead-Dorval, K. B. (2006). Creative problem solving: An introduction. Prufrock Press Inc.. Thank You