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CSE360 Tutorial 09

CSE360 Tutorial 09

Introduction to Software Engineering
Software Metrics
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  1. CSE360
    Introduction to Software Engineering
    Lecture:
    Software Measurement
    Javier Gonzalez-Sanchez
    [email protected]
    javiergs.engineering.asu.edu
    Office Hours: By appointment

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  2. Let’s Make a Parenthesis
    To talk about Quality

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  3. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 3
    Quality

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  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.

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  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

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  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.

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  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.

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  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.

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  9. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 9
    Example

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  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

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  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

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  12. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 12
    Reference
    Chapter 24

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  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..

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  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.

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  15. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 15
    Cyclomatic Complexity
    CC = Edge - Node + 2
    Or
    CC = ConditionalNodes + 1

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  16. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 16
    Cyclomatic Complexity
    i = 0; n=4;
    while (ij = i + 1;
    while (jif (A[i]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

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  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

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  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

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  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

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  20. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 20
    Example A (Week 05)

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  21. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 21
    Example B (Week 05)

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  22. Javier Gonzalez-Sanchez | CSE360 | Summer 2018 | 22
    Reference
    Chapter 24

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  23. CSE360 – Introduction to Software Engineering
    Javier Gonzalez-Sanchez
    [email protected]
    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.

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