Introduction to C Programming CE00312-1

1. Introduction to C ProgrammingCE00312-1 Lecture 5 Program Design in C

2. Design theory • Difference between functional and object-oriented programming paradigm and design of resulting code. • Top-down design • Stepwise refinement • Functional decomposition

3. Design of Processes • functional analysis used to design resulting code • Break down design into logical blocks • ðStepwise refinement • ðFunctional decomposition

4. Functional Analysis Get up Go to University For as long as there is a lecture to attend Go to lecture Take notes attentively and enthusiastically! Eat tea Go to town For as long as you have money and are thirsty Buy a drink Go home If you have spare money go by taxi Else walk Go Function College Function Food Function Go out Function Go home Function

5. Design Notation • Top Down design • Problem decomposition expressed as combinations of sequence, selection, iteration both Inter-function and intra-function • Level of abstraction or degree of modularity determined by complexity of problem and design notation used • Object Design • Uses object modeling to determine level of abstraction • Problem decomposition determined by object definition • Processes expressed as behaviour of objects

6. Top-Down design • Take main functions • Systematically break into smaller chunks • Use a method to ‘represent’ solution • Stop when resulting modules are small enough to be easily implemented (but not too cumbersome) • ‘Clever’ chunking results in reusable modules

7. Top Down design notation • Representative of problem • Diagrammatic notation; • sequence, selection, iteration • JSP • Nassi-Scneidermann • Pseudo Code/ Structured English • Embeds descriptive language into basic construct syntax

8. Pseudocode/Structured English While valid input If mark entry enter name enter mark Case {mark 0 - 39 “refer” mark 40 – 59 “pass” mark 60 – 79 “merit” mark 80 – 100 “Distinction”} else “Error” output name and grade Else Clear

9. Jackson Structured Design Inputs Output

10. While user input If Not Clear Enter details Clear R P M D E Output mark & name Nassi-Schneidermann

11. Testing • Purpose of testing • Designing test cases and test case data with corresponding input and expected output • Black and White box testing • Difference between these two categories of test; when test data can be designed and purpose.

12. Black Box testing • Black Box testing consists of • Categories • Functional Tests • Invalid Tests • Boundary Tests • Special Tests

13. White Box testing • Categories • Path Analysis • Complex Conditions

14. Testing Example • Consider the example used as one of the week 2 practical exercises; • reading in percentage scores greater than 0 and printing out the corresponding letter grade. This is repeated until a negative value is read in. At this stage, the total number of values in each grade range is printed. An error message is printed for any input value greater than 100.

15. Black Box Tests1.Functional Tests • F1: Read in a percentage score and print the corresponding letter grade • F2: Produce an error message if a positive number greater than 100 is input • F3: Print out the number of input values in each of the letter grade ranges • F4: Terminate input when a negative value is read in.

16. 2. Invalid Tests • I1: A positive number greater than 100 should produce an error message

17. 3. Boundary Tests • B1: Input largest valid value • B2: Input smallest invalid positive value • B3: Input lowest valid positive value • B4: Input largest invalid negative value • B5: Input lowest value in ‘A’ range • B6: Input highest value in ‘B’ range • B7: Input lowest value in ‘B’ range • B8: Input highest value in ‘C’ range • B9: Input lowest value in ‘C’ range • B10: Input highest value in ‘D’ range • B11: Input lowest value in ‘D’ range • B12: Input highest value in ‘F’ range

18. 4. Special Test Cases • S1: First input value is negative • S2: No values are input in a particular letter grade range

19. White Box Tests • Can only be designed after the code has been written. • Complex Conditions • None in this example • Path Analysis

20. Path Analysis P7 P1 Not P2 P2 Not P3 P3 Not P4 P4 P5 Not P5 P6 Not P6

21. Path Analysis • P1: Initial sequence • P2: Value greater than 100 • Not P2: Positive value less than or equal to 100 • P3: A’ grade • Not P3: value below an ‘A’ grade • P4: ‘B’ grade • Not P4: value below a ‘B’ grade • P5: ‘C’ grade • Not P5: value below a ‘C’ grade • P6: ‘D’ grade • Not P6: ‘F’ grade • P7: Print out total number of values in each grade range

22. F1: 90 -2 F2: 110 –2 F3: 67 78 89 90 93 53 54 65 72 73 -3 F4: As for F1 I1: As for F2 B1: 100 -1 B2: 101 -1 B3: 0 -1 B4: -1 B5: As for F1 B6: 89 -1 B7: 80 -1 B8: 79 -1 B9: 70 -2 B10: 69 -1 B11: 60 -1 B12: 59 –1 S1: As for B4 S2: 90 89 78 -1 P1: As for F1 P2: As for F2 P3: As for F1 Not P3: As for B12 P4: As for B7 Not P4: As for B12 P5: As for B9 Not P5: As for B12 P6: As for B12 Not P6: As for F3 P7: As for F1 Test Data

23. Complex Conditions Consider the following if condition if (age<18 || age >=65) Resulting complex conditions: age<18 age>=65 C1: True True C2: True False C3: False True C4: False False C1: impossible C2: age = 16 C3: age = 70 C4: age = 21

24. The number of complex conditions is equal to 2N, where N is the number of parts to the condition.  e.g.  if ( age <18 || age >=65) && (gender==’m’ || gender==’f’) ð • 24 = 16 conditions

25. Truth Table age<18 age>=65 gender==’m’ gender==’f’ False False False False False False False True False False True False False False True True False True False False False True False True False True True False False True True True Repeated with column 1 containing True and columns 2, 3 and 4 unchanged. e.g. C3: age=21, gender=’m’ C4: impossible (gender can’t be both ‘f’ and ‘m’) C6: age = 70, gender=’f’ C9: age = 16 gender =’z’