1. Software Engineering SM ? 1

2. Outline of this presentation What is SM The Need for SM Type of SM Size Oriented Metric Function Oriented Metric 218/10/2015

3. Software Metric A metric is a measurement of some aspect of the software product or the software process 318/10/2015

4. Software Metric We take metrics for a variety of reasons – to measure the quality of a product – to assess the productivity of the people building the product – to assess the benefits (productivity and quality) of new software tools – to form a baseline so we can estimate for new tools – to help justify requests for new tools or additional training 4 What is SM 18/10/2015

5. Software Metric Software Development in general – has excessive costs (especially in maintenance) – low productivity – poor quality – lack of standards 5 The Need for SM 18/10/2015

6. Software Metric Reasons being that we fail to: – set measurable targets – measure the real costs in projects – quantify the quality – properly evaluate new tools and techniques 6 The Need for SM 18/10/2015

7. Software Metric Size-oriented Metrics Function-oriented Metrics Technical Metrics Human-oriented Metrics Productivity Metrics Quality Metrics 7 Types of Metric

8. Software Metric Size-oriented Metrics – direct measures of the output and quality of the SE process Function-oriented Metrics – indirect measures of the output and quality of the SE process 8 Types of Metric

9. Software Metric Technical Metrics – focus on the character of the software, e.g. coupling and cohesion Human-oriented Metrics – information about the method by which people build and use systems 9 Types of Metric

10. Software Metric Productivity Metrics – focus on the output of the software engineering process Quality Metrics – focus on the conformance of the software to the implicit and explicit user requirements (fitness for use) 10 Types of Metric

11. Software Metric Built on the past experiences of organisations Direct measures of the software Generally based on the idea of Line of Code or Source Line of Code 11 Size Oriented Metric

12. Software Metric Primary Examples: – Size of a product = Kilo Lines of Code (KLOC) – Productivity = KLOC/person-month – Quality = number of faults/KLOC – Cost = $/KLOC – Documentation = Pages of Documentation/KLOC 12 Size Oriented Metric (cont.)

13. Software Metric Comments on Line of Code Defined as one line of text in a source file Modified by a number of factors depending upon your Source Line of Code (SLOC) Counting Standard Simplest Standard – Don ’ t count blank lines – Don ’ t count comments – Count everything else 13 Size Oriented Metric

14. Software Metric Advantages on Line of Code Artifact of software development which is easily counted Many existing methods use LOC as a key input A large body of literature and data based on LOC already exists 14 Size Oriented Metric

15. Software Metric Disadvantages of Line of Code Programming language-dependent Well-designed, but shorter programs are penalised Does not easily accommodate non-procedural languages Reuse can be difficult to factor in Difficult to develop a figure for LOC early in the development 15 Size Oriented Metric

16. Software Metric Concentrate on measuring the functionality of a system Are generally independent of the programming language used The first and by far the most popular is the Function Point & Feature Point 16 FUNCTION Oriented Metric

17. Software Metric FUNCTION POINT – Developed by Albrecht in 1979 for IBM – Function points are derived using countable measures of the software requirements domain assessments of the software complexity 17 FUNCTION Oriented Metric

18. Software Metric 18 FP = COUNT-TOTAL X [ 0.65 + 0.01 x F i ] ∑ where Fi are the 14 complexity adjustment values (gives ±35%) Calculating Function Point FUNCTION Oriented Metric

19. Software Metric Calculating Count Total for Function Point based on: Number of user inputs Number of user outputs Number of user inquiries Number of files Number of external interfaces 19 FUNCTION Oriented Metric

20. Software Metric Number of user inputs – each user input which provides distinct application data to the software is counted Number of user outputs – each user output that provides application data to the user is counted, e.g. screens, reports, error messages 20 FUNCTION Oriented Metric

21. Software Metric Number of user inquiries – An on-line input that results in the generation of some immediate software response in the form of an output Number of files – each logical master file, i.e. a logical grouping of data that may be part of a database or a separate file Number of external interfaces – all machine-readable interfaces that are used to transmit information to another system are counted 21 FUNCTION Oriented Metric

22. Software Metric 22 Weighting Factor Measurement parameter Count Simple Average Complex Total Number of user Inputs x3 x4 x6 = Number of user outputs x4 x5 x7 = Number of user Inquiries x3 x4 x6 = Number of files x7 x10 x15 = Number of external interfaces x5 x7 x10 = COUNT TOTAL = + ? Calculating Count Total FUNCTION Oriented Metric

23. Software Metric We now assess the software complexity Rate each of the factors on the next 2 slides according to the following scale: – 0 - No influence – 1 - Incidental – 2 - Moderate – 3 - Average – 4 - Significant – 5 - Essential 23 Calculating Complexity Adjustment FUNCTION Oriented Metric

24. 14 Complexity Adjustment Questions 1.Does the system require reliable backup and recovery? 2.Are data communications required? 3.Are there distributed processing functions? 4.Is performance critical? 5.Will the system run in an existing, heavily utilised operational environment? 6.Does the system require on-line data entry? 7.Does the on-line data entry require the input transaction to be built over multiple screens or operations? 24 FUNCTION Oriented Metric Software Metric

25. 8.Are the master files updated on-line? 9.Are the inputs, outputs, files or inquiries complex? 10.Is the internal processing complex? 11.Is the code designed to be reusable? 12.Are conversion and installation included in the design? 13.Is the system designed for multiple installations in different organisations? 14.Is the application designed to facilitate change and ease of use by the user? 25 FUNCTION Oriented Metric 14 Complexity Adjustment Questions

26. Software Metric Advantage Programming language-independent Based on data which are known early in the project Significant bodies of data available 26 FUNCTION Oriented Metric

27. Software Metric Disadvantages Developed for business systems and therefore only valid for that domain (Feature Points which extend Function Points by also measuring algorithmic numbers solves this to some extent ) Many aspects are subjective and have not been validated Function Points have no physical meaning, it ’ s just a number 27 FUNCTION Oriented Metric

28. Software Metric 28 Small project : < 2000 Function Points Medium Project : 2,000 to 10,000 Function Points Large Project : > 10,000 Function Points FUNCTION Oriented Metric Some Figures

29. Software Metric 29 FP = COUNT-TOTAL X [ 0.65 + 0.01 x F i ] ∑ where Fi are the 14 complexity adjustment values (gives ±35%) Calculating Feature Point FUNCTION Oriented Metric

30. Software Metric Calculating Count Total for Feature Point base on Number of user inputs Number of user outputs Number of user inquiries Number of files Number of external interfaces Number of algorithm 30 FUNCTION Oriented Metric

31. Software Metric Number of algorithm – all complex algorithm in creating program and in every aspect of Inputs Outputs Inquiries Files External interfaces 31 FUNCTION Oriented Metric Calculating Count Total for Feature Point

32. Software Metric 32 Weighting Measurement parameter Count Factor Total Number of user Inputs x4 = Number of user outputs x5 = Number of user Inquiries x4 = Number of files x7 = Number of external interfaces x7 = Number of algorithm x3 = Count total + ? FUNCTION Oriented Metric Calculating Count Total for Feature Point

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