Programming II (CS300)

Transcription

1 1 Programming II (CS300) Chapter 01: Procedural Programming MOUNA KACEM Fall 2018

2 Procedural Programming 2 Introduction Procedural Programming: General Overview Procedural Programming: Top-Down Design Method Computational Thinking Programming Tips Keep in Mind

3 Introduction 3 Algorithm An algorithm is a method or process followed to solve a problem Function Input Process Output If the algorithm is viewed as a function, then it represents the implementation for the function that transforms an input to a corresponding output

4 Introduction 4 Function Input Process Output Algorithm Input: An algorithm has zero or more inputs (acquire data) read from an external source either before that the algorithm starts or as the algorithm runs Output: An algorithm has one or more outputs (results). The output values are specifically determined by the input. Process: A computational process (performing arithmetic computations, comparisons, testing logical conditions, and so on.) that given a set of values as an input produces some value or a set of values as an output

5 Introduction 5 Algorithm A sequence of computational steps that transform the input into the output A recipe for solving a computational problem whose steps (instructions) should be concrete and completely understood An algorithm is like a food recipe: a step-by-step procedure (a list of instructions) to complete a task Algorithm Food recipe Step-by-step procedure Input: acquire data Output: desired result Step-by-step procedure Input: Ingredients Output: Cake

6 Introduction 6 Program An instantiation (or implementation) of an algorithm in a computer programming language (such as C/C++, Java, Python, etc.) A program must Be Correct: i.e. converting each input to the correct output Be of finite length: An algorithm should be composed of a finite number of steps and each step must be doable in a finite amount of time Unambiguous: Each step of an algorithm must be precisely defined and it must be no ambiguity as to which step will be performed next Terminate for all inputs: i.e. an algorithm should not go into an infinite loop.

7 Procedural Programming - General Overview 7 Procedural Programming Standard approach used in traditional Computer programming languages such as C, Pascal, Fortran, and Basic Creates a step by step program that guides the application through a sequence of instructions Each instruction is executed in order Procedural Programming focuses on processes (operations, conditions and actions)

8 Procedural Programming: Top-Down Design Method 8 Top-Down Design Method A solution method for problem solving where The problem is broken down into smaller sub-problems, The sub-problems in turn are broken down into smaller sub-problems continuing until Each sub-problem is straight forward enough to be solved individually in a few steps The smaller solutions are assembled (composed) into a big solution This method is called also Functional decomposition, Modular development, or Divide and Conquer

9 Procedural Programming: Top-Down Design Method 9 Graphical illustration of the Top-Design Method Decomposition of the Problem into smaller sub-problems Level 0 Top Level Level 1 Level 2 Level N... Statement of the Problem Sub-problem1 Sub-problem2 S-P 1.1 S-P 1.2 S-P 1.3 S-P 2.1 S-P 2.2 The number of levels (functional decomposition) continues until the sub-problem is one that can be solved directly Composition of the global solution

10 Procedural Programming: Top-Down Design Method 10 Benefits of the Top-Design Method (1) Make the Problem solving easier Smaller problems or tasks are more easier to understand than a big problem It is easier to solve small problems than solving big/complex ones If a problem can't be solved directly, decompose it into smaller tasks. There is usually a smaller problem that can be solved easier. Just Find it Make the Problem solving faster (team-work) A team of programmers can be used to solve the big problem faster Each sub-problem is independent of other sub-problems and can be solved individually Possibility to design, write and test each module independently Different programmer can be working on different modules at the same time

11 Procedural Programming: Top-Down Design Method 11 Benefits of the Top-Design Method (2) Make it easier to ensure correctness Error can be detected and fixed in a logical manner Easier to isolate the cause of an error, localize the error (within a module or a function), and fix it Ensure reusability The process of top-down design leads to a modular implementation: reusable modules. These modules can be used in future applications Solutions to smaller problems (tasks) are more likely to be re-used elsewhere (in other programs) than solutions to bigger problems Libraries of software modules can be built to solve different tasks For example, you need to use a linked list data structure to solve your problem. The routine to manage and manipulate a linked list can be mostly available to re-use

12 Procedural Programming: Top-Down Design Method 12 Graphical illustration of the Top-Design Method Decomposition of the Problem into smaller sub-problems Level 0 Top Level Level 1 Level 2 Level N... Statement of the Problem Sub-problem1 Sub-problem2 S-P 1.1 S-P 1.2 S-P 1.3 S-P 2.1 S-P 2.2 The number of levels (functional decomposition) continues until the sub-problem is one that can be solved directly Composition of the global solution

13 Procedural Programming: Top-Down Design Method 13 Main issue of the Top-Design Method The Top-Down design method starts with a specification of the system (statement of the problem) at the top level If the main problem is not well-defined (not defined correctly), changes made at the top level (the main program or procedure) will cascade to the subprocedures, and the sub-sub-procedures, and so on Any major change at an upper level may impact all the procedures (solutions to related sub-problems) in that branch of hierarchy

14 Procedural Programming: Top-Down Design Method 14 Practice Example Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect

15 Procedural Programming: Top-Down Design Method 15 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Problem Analysis Input: an integer N Precondition: N should be positive Process Determine the divisors of the number N Check if the divisors add up to the number N Output if N is perfect else Display N is perfect or return true Display N is not perfect or return false

16 Procedural Programming: Top-Down Design Method 16 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Continuing Problem Analysis: Problem Decomposition Sub-problem 1 Read a positive integer N as input Sub-problem 2 Determine if N is perfect and display the result

17 Procedural Programming: Top-Down Design Method 17 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Continuing Problem Analysis: Problem Decomposition Sub-problem 1 Read a positive integer N as input Sub-problem 2 Determine if N is perfect and display the result Sub-problem2 Decomposition: Determine the sum of the divisors of the number N Check if the divisors add up to the number N and display the result

18 Procedural Programming: Top-Down Design Method 18 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Solving Sub-problem 1: Read a positive integer N as input Step1: Output a prompt asking for a positive number Step2: Input/Read the number called N Step3: Check if N is positive otherwise ask again for a valid input (Step 3 is a loop executed zero or more time; stop condition: input value N is positive) => Step3: while loop

19 Procedural Programming: Top-Down Design Method 19 Problem: Design an algorithm to determine if a given integer is perfect Coding a Solution for Sub-problem 1: Read a positive integer N as input

20 Procedural Programming: Top-Down Design Method 20 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Recall: Problem Decomposition Sub-problem 1 Read a positive integer N as input Sub-problem 2 Determine if N is perfect and display the result Sub-problem2 Decomposition: Determine the sum of the divisors of the number N Check if the divisors add up to the number N and display the result

21 Procedural Programming: Top-Down Design Method 21 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Solving Sub-problem 2.1: Determine the sum of the divisors of the number N Step1: Set the Sum to 1 (since 1 certainly divides N) Step2: Set div to 2 Step3: while div is less than or equal to N/2 if div is a divisor of N add div to the Sum add 1 to div => Step 3 is a for loop

22 Procedural Programming: Top-Down Design Method 22 Problem Description: An integer N is "perfect" if N is equal to the sum of the positive integers K such that K < N and K is a divisor of N. Design an algorithm to determine if a given integer is perfect Solving Sub-problem 2.2: Check the result Step1: if Sum equals N Output: Display N is perfect else Output: Display N is not perfect

23 Procedural Programming: Top-Down Design Method 23 Problem: Design an algorithm to determine if a given integer is perfect Coding a Solution for Sub-problem 2: Determine if N is perfect and display the result

24 Procedural Programming: Top-Down Design Method 24 Problem: Design an algorithm to determine if a given integer is perfect Composing a Solution for the Problem: Determine if given number N is perfect

25 Procedural Programming 25 Introduction Procedural Programming: General Overview Procedural Programming: Top-Down Design Method Computational Thinking Programming Tips Keep in Mind

26 Computational Thinking 26 Computational Thinking Processes involved in formulating problems and their solutions in a way that can be effectively performed by a computer Computational thinking is not thinking about computers. It is about looking at a problem in a way that a computer can help us to solve it A collection of diverse skills and techniques to help programmers solve problems using a computer effectively Logical reasoning Defining the best way to solve the problem Decomposition Abstraction Patterns and generalization

27 Computational Thinking 27 Logical reasoning Logical reasoning is fundamental in computer programming Be careful: Computers are not natural logical thinkers. Logical reasoning is about constructing arguments and being able to explain Why does something happen? Why is something the way it is? why something isn t quite as it should be?

28 Computational Thinking 28 Logical reasoning Logical reasoning involves the ability to Analyze problems and logically organize data Break problems into smaller ones, Figure out how repeatable processes can save time and improve quality, Organize problems into the right size Test and debug a problem, search for errors/bugs, and fix them

29 Computational Thinking 29 Defining the best way to solve the problem There are different solutions Analyze the different solutions: which is the best one in terms of correctness, fastest way to solve the problem and using the least amount of resources (time and memory space) Promote re-usability: which solution can be used to solve other problems

30 Computational Thinking 30 Decomposition Breaking-down a problem into smaller sub-problems or tasks, easier to understand and to solve Top-Down Design Method

31 Computational Thinking 31 Abstraction Abstraction is simplifying things Allows a better management of the complexity of problem solving Simplifying things Identifying what is important without worrying about the details (determine what details to highlight and what details to ignore) Removing unnecessary details High-level view: abstract over details

32 Computational Thinking 32 Patterns and Generalization Generalization Looking for a general approach to a class of problems Identifying patterns allows Make predictions Create rules Provide a reliable solution (model) to solve a general problem Spotting and using similarities

33 Procedural Programming 33 Introduction Procedural Programming: General Overview Procedural Programming: Top-Down Design Method Computational Thinking Programming Tips Keep in Mind

34 Programming Tips 34 Refine your program Use methods to increase the readability of your code and makes it easier to expand or change Format your code Code formatting is necessary to understand your code more easily Comment your code Good comments make your program more easier to understand, expand and re-use Test your program Test your program against a well-chosen set of input data and observe the input-output relationships

35 Programming Tips: Program Development Process 35 Analyze the problem statement Design a solution Edit source code Compile/link source code Find error in source code (check syntax) Test your program execution with another set of input Compiletime errors? No Test the program execution Run-time errors? No yes yes Find cause of execution or intent/logic error check code check input data rethink analysis/design Success with this input! or

36 Keep in Mind 36 An algorithm is a repeatable set of steps that can transform inputs into a predictable, consistent output Top-Down Design Method breaking a main algorithm into parts (modules, procedures, functions) that are more manageable and easier to solve. The smaller solutions are assembled into a big solution

37 Keep in Mind 37 Do not forget: You need to develop a solution to a task only once and then re-use it where-ever you need it Computational thinking is the key for organizing thoughts to solve problems efficiently using a computer Use logical reasoning while debugging a program