CSE360 Tutorial 09

Introduction to Software Engineering
Software Metrics
(202206)

Transcript

1. CSE360 Introduction to Software Engineering Lecture: Software Measurement Javier Gonzalez-Sanchez javiergs@asu.edu javiergs.engineering.asu.edu Office Hours: By appointment
2. Let’s Make a Parenthesis To talk about Quality
3. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 3 Quality
4. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 4 Software Metrics • Knowing what is inside your source code is the first step in assessing the quality of the software product. • Knowing the quantity of work performed in generating the source code is the first step in determining the productivity of your software team.
5. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 5 Software Metrics Metrics Size LOC eLOC lLOC Understandability Comments Whitespaces Complexity Average, Max, Min LOC Interface Complexity Cyclomatic Complexity
6. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 6 Size Metrics • LOC – Lines of Code Metric. Including lines of a single brace or parenthesis • LOC are used to create time and cost estimates. • LOC are a tracking tool to measure the degree of progress on a module or project. • An experienced developer can gage a LOC estimate based upon knowledge of past productivity on projects.
7. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 7 Size Metrics • eLOC – effective Lines of Code Metric. Only code statements • An effective line of code or eLOC is the measurement of all lines that are not comments, blanks or standalone braces or parenthesis. These can inflate LOC metrics by 20 to 40 percent. • This metric more closely represents the quantity of work performed.
8. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 8 Size Metrics • lLOC – logical Lines of Code Metric. • These statements are terminated with a semi- colon. The control line for the "for" loop contain two semi-colons but accounts for only one semi colon.
9. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 9 Example
10. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 10 Understandability Metrics • Comment Line and Comment Percent Metric • The degree of commenting within the source code measures the care taken by the programmer to make the source code and algorithms understandable. • Poorly commented code makes the maintenance phase of the software life cycle an extremely expensive adventure. • Comments can occur by themselves on a physical line or be co-mingled with source code. The sum of the lines of code, comments and blank lines often exceeds the physical line count. This is expected a when comments are co-mingled with source code. • Comment Percent = Comment Line Count / (LOC) x 100
11. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 11 Understandability Metrics • Blank Line and White Space Percent Metric • The number of blank lines within source code determines the readability of the product. White space accents the logical grouping of constructs and variables. Programs which use few blank lines are difficult to read and more expensive to maintain. • It counts the spaces and characters within the source code. The white space percentage metric is another measure of readability for the source product. • White Space Percentage = (Number of spaces / Number of spaces and characters) * 100
12. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 12 Reference Chapter 24
13. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 13 Function Metrics • Average LOC per Function Metric. An accepted industry standard of 200 LOC per function is desired as the average LOC per function • Maximum LOC per Function Metric. • Minimum LOC per Function Metric. A minimum LOC per function of 2 or less can indicate functions that may have been prototype but not yet complete..
14. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 14 Function Metrics • Cyclomatic Complexity. It is a quantitative measure of the number of linearly independent paths • Paths occurs when a "while", "for", "if", "case" and "goto" keywords appear within the function. • if the source code contained no control flow statements (conditionals or decision points), the complexity would be 1 • If the code had one single-condition IF statement, there would be 2 paths through the code: one where the IF statement evaluates to TRUE and another one where it evaluates to FALSE • Two nested single-condition IFs, or one IF with two conditions, would produce a complexity of 3.
15. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 15 Cyclomatic Complexity CC = Edge - Node + 2 Or CC = ConditionalNodes + 1
16. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 16 Cyclomatic Complexity i = 0; n=4; while (i<n-1) { j = i + 1; while (j<n) { if (A[i]<A[j]) swap(A[i], A[j]); } i=i+1; } // CC = 9 - 7 + 2 = 4 // CC = 3 + 1 = 4 (Condition nodes are 1,2 and 3 nodes) // A set of possible execution path of a program // 1, 7 // 1, 2, 6, 1, 7 // 1, 2, 3, 4, 5, 2, 6, 1, 7 // 1, 2, 3, 5, 2, 6, 1, 7
17. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 17 Cyclomatic Complexity Complexity Number Meaning 1-10 Structured and well written code High Testability Cost and Effort is less 10-20 Complex Code Medium Testability Cost and effort is Medium 20-40 Very complex Code Low Testability Cost and Effort are high >40 Not at all testable Very high Cost and Effort
18. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 18 Example A (Week 05) • 3 files • 24 methods • 394 lines • 326 LOC • 285 eLOC • 182 lLOC • 20 Lcomments • Comments 5.1% • Blank lines 12.2% • Spaces: 21.0% (79% code) • Max CC: 6 • Average CC: 1.46 • Total P: 18 • Max P: 3 • Average P: 0.75 • Total R: 25 • Max R: 2 • Average R: 1.04
19. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 19 Example B (Week 05) • 5 files • 21 methods • 522 lines • 412 LOC • 356 eLOC • 276 lLOC • 72 Lcomments • Comments 13.8% • Blank lines 7.3% • Spaces: 26.7% (73.3% code) • Max CC: 7 • Average CC: 2.24 • Total P: 34 • Max P: 7 • Average P: 1.62 • Total R: 21 • Max R: 1 • Average R: 1
20. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 20 Example A (Week 05)
21. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 21 Example B (Week 05)
22. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 22 Reference Chapter 24
23. CSE360 – Introduction to Software Engineering Javier Gonzalez-Sanchez javiergs@asu.edu Summer 2017 Disclaimer. These slides can only be used as study material for the class CSE360 at ASU. They cannot be distributed or used for another purpose.