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Metrics An overview

Metrics An overview. What are metrics?. “ A quantitative measure of the degree to which a system, component, or process possesses a given attribute.” [IEE93] Attributes of metrics - Simple, persuasive, consistent, Independent and effective. What is measured.

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Metrics An overview

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  1. MetricsAn overview

  2. What are metrics? “ A quantitative measure of the degree to which a system, component, or process possesses a given attribute.” [IEE93] • Attributes of metrics - Simple, persuasive, consistent, Independent and effective

  3. What is measured • Processes are collection of software related activities • Products are any artifacts, deliverables or documents that result from a process activity.

  4. Types of Metrics • Metrics for Analysis • System Size • Functionality Delivered • Specification Quality • Metrics for the Design • Architectural Metrics • Component Level • Interface Design • Metrics for the Code • Halstead Metrics • Complexity Metrics • Length Metrics • Metrics for Testing • Defect metrics

  5. Analysis Model Metrics • Function – Based Metrics • Function point metric • Variables • Formula • Questions • Metrics for Specification Quality • Specificity • Completeness

  6. Design Model Metrics • Architectural Design Metrics • Object – Oriented Design Metrics • Component – Level Design Metrics • User Interface Design Metrics

  7. Architectural Metrics • Focus on characteristics of the architecture with emphasis on the structure and effectiveness of modules or components within the architecture. • Structural Complexity • S(i) = [fout(i)] ^2 • Data complexity • D(i) = v(i) / [fout(i) + 1] • System complexity • C(i) = S(i) + D(i) where fout is defined as the number of modules directly invoked by module i. v(i) = number of input and output variables in or out of i. • Design Structure Quality Index

  8. Object Metrics • Size: • Population, Volume, Length, Functionality • Complexity • Completeness • Cohesion • Coupling - an indication of “connectedness” of a module with others, global data and environment • Volatility

  9. Object-Oriented • System size • Number of function calls and objects. • Class or method size • Size of classes and methods • Coupling and inheritance • Interdependence of classes. Number and complexity of relationships. • Class or method internals • Complexity and level of documentation

  10. User Interface Metrics • Layout • Absolute and relative position of entities • Frequency of use • “Cost of transition” • Cohesion • Relative connection between on – screen to other on – screen content • Time • Time to achieve an specific action • Time to recover from error • Time to achieve a use case

  11. Source Code Metrics • Lines of code metric • Lines of code used to develop a program • Set limits on coding lines • McCabe’s cyclomatic metrics • Path control • Logical decision statements and operators • Halstead Metrics • Depend on the following measures: • Number of direct operators • Number of direct operands • Number of operator occurrences • Number of operand occurrences • Predicts • Length • Volume • Time, effort • Number of errors

  12. Testing Metrics • Information for testing metrics can be gathered thru various sources: • Function – based metrics • Cyclomatic complexity • Halstead Metrics for testing • Metrics for OO Testing • Metrics used in design provide an indication of design quality • The metrics consider aspects of encapsulation and inheritance

  13. Web Projects Since web projects can are more dynamic than most other types of projects it can be harder to measure them. • Number of static/dynamic pages • Number of internal page links • Number of executable functions (scripts, applets, etc)

  14. Product Metrics Future • Application Domain Complexity Research • Automated Product Metric Tools • ESQUT (Evaluation of Software Quality from User’s viewpoinT) • WEBMETRICS • Mathematical Product Metrics

  15. What are process metrics? Process metrics really encompasses both process and project metrics. • Process metrics are used to measure the effectiveness of a development process over multiple projects • Project metrics are used to evaluate accomplishment of a single development effort

  16. Process Metrics Process Metrics are generally used at the project management level. • Strategic in nature • Main goal is process improvement • Metrics from individuals combined to provide group/project metrics • Care must be taken to keep individual metrics private

  17. Measurement Methods Due to the variation in software, and the lack of standards, there are many types of metrics that can be used • Size-Oriented • Function-Oriented • Object-Oriented • Use-Case Oriented

  18. Size-Oriented • Metrics are normalized based on the size of the software • Focus on LOC (Lines of Code) • Errors Per KLOC (thousand lines of code) • Defects per KLOC • $ per LOC • Page of documentation per KLOC

  19. Function-Oriented • Metrics are normalized based on program functionality • Most commonly used metric is the FP (function point) • Errors per Function Point • Defects per FP • $ per FP • Pages of documentation per FP • FP per person-month

  20. Object-Oriented • number of classes reused • number of classes with defects

  21. Metrics Tools • SynQuest • NEXTRA • AMI • SPQR/20 • SOFT-ORG • SQUID M-Base • Analyst4j • Eclipse Metrics

  22. Why use Metrics? "If you can not measure it, you can not improve it.“ – Lord Kelvin • Characterize - Increase Understanding • Evaluate • Predict - Managing Software • Improve - Guiding Improvements

  23. Why use Metrics - Benefits Although it can be hard to generate metrics from software, there are many benefits • Manage complexity • Process improvement • Quality tracking • Cost estimation

  24. Why use Metrics - Obstacles "Not everything that can be counted counts, and not everything that counts can be counted.“ - Albert Einstein  • Takes time and effort away from the project • Simple project may not benefit • Projects may vary substantially • Indicators must be interpreted

  25. Why use Metrics – Bottom Line Provides the best option to standardize the development process to ensure quality and reliability

  26. Establishing a Metrics Program Software Productivity Center, Inc. suggests an 8 step approach: • Document the Software Development Process • State the Goals • Define Metrics Required to Reach Goals • Identify Data to Collect • Define Data Collection Procedures • Assemble a Metrics Toolset • Create a Metrics Database • Define the Feedback Mechanism

  27. Establishing a Metrics Program Establishing a program takes planning and time to be effective. • Need historical data from past projects to establish indicators • Goals have to be well defined to be meaningful • Those collecting measures need to be vested in the program

  28. CONCLUSIONS • Problems in products in each phase can be detected and removed at an early stage by using metrics. • Metrics provide a quantitative and predictive view of potential problems. Thus, they are a powerful tool for product development. • Metrics are still in a young stage. Research is needed to set a ground for prediction of problems.

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