Software measurement and estimation : a practical approach / / Linda M. Laird, M. Carol Brennan

• Record Nr.: UNINA9910143577203321
• Autore: Laird Linda M. <1952->
• Pubbl/distr/stampa: Hoboken, New Jersey : , : John Wiley & Sons, , 2006; [Piscataqay, New Jersey] : , : IEEE Xplore, , [2006]
• ISBN: 1-280-46844-0; 9786610468447; 0-470-24780-0; 0-471-79253-5; 0-471-79252-7
• Descrizione fisica: 1 online resource (276 p.)
• Collana: Quantitative software engineering series ; ; 2
• Altri autori (Persone): BrennanM. Carol <1954->
• Disciplina: 005.1; 005.14
• Soggetti: Software measurement; Software engineering
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Acknowledgments -- 1. Introduction -- 1.1 Objective -- 1.2 Approach -- 1.3 Motivation -- 1.4 Summary -- References -- Chapter 1 Side Bar -- 2. What to Measure -- 2.1 Method 1: The Goal Question Metrics Approach -- 2.2 Extension to GQM: Metrics Mechanism is Important -- 2.3 Method 2: Decision Maker Model -- 2.4 Method 3: Standards Driven Metrics -- 2.5 What to Measure is a Function of Time -- 2.6 Summary -- References -- Exercises -- Project -- 3. Fundamentals of Measurement -- 3.1 Initial Measurement Exercise -- 3.2 The Challenge of Measurement -- 3.3 Measurement Models -- 3.3.1 Text Models -- 3.3.2 Diagrammatic Models -- 3.3.3 Algorithmic Models -- 3.3.4 Model Examples: Response Time -- 3.3.5 The Pantometric Paradigm - How to Measure Anything -- 3.4 Meta-Model for Metrics -- 3.5 The Power of Measurement -- 3.6 Measurement Theory -- 3.6.1 Introduction to Measurement Theory -- 3.6.2 Measurement Scales -- 3.6.3 Measures of Central Tendency and Variability -- 3.6.3.1 Measures of Central Tendency -- 3.6.3.2 Measures of Variability -- 3.6.4 Validity ; and Reliability of Measurement -- 3.6.5 Measurement Error -- 3.7 Accuracy versus Precision and the Limits of Software Measurement -- 3.7.1 Summary -- 3.7.2 Problems -- 3.7.3 Project -- References -- 4. Measuring the Size of Software -- 4.1 Physical Measurements of Software -- 4.1.1 Measuring Lines of Code -- 4.1.1.1 Code Counting Checklists -- 4.1.2 Language Productivity Factor -- 4.1.3 Counting Reused and Refactored Code -- 4.1.4 Counting Non-Procedural Code Length -- 4.1.5 Measuring the Length of Specifications and Design -- 4.2 Measuring Functionality -- 4.2.1 Function Points -- 4.2.1.1 Counting Function Points -- 4.2.2 Function Point Counting Exercise -- 4.2.3 Converting Function Points to Physical Size -- 4.2.4 Converting Function Points to Effort -- 4.2.5 Other Function Point Engineering Rules -- 4.2.6 Function Point Pros and Cons -- 4.3 Feature Points -- 4.4 Size Summary -- 4.5 Size Exercises -- 4.6 Theater Tickets Project.; References -- 5. Measuring Complexity -- 5.1 Structural Complexity -- 5.1.1 Size as a Complexity Measure -- 5.1.1.1 System Size and Complexity -- 5.1.1.2 Module Size and Complexity -- 5.1.2 Cyclomatic Complexity -- 5.1.3 Halstead's Metrics -- 5.1.4 Information Flow Metrics -- 5.1.5 System Complexity -- 5.1.5.1 Maintainability Index -- 5.1.5.2 The Agresti-Card System Complexity Metric -- 5.1.6 Object-Oriented Design Metrics -- 5.1.7 Structural Complexity Summary -- 5.2 Conceptual Complexity -- 5.3 Computational Complexity -- 5.4 Complexity Metrics Summary -- 5.5 Complexity Exercises -- 5.6 Projects -- References -- 6. Estimating Effort -- 6.1 Effort Estimation - Where are we? -- 6.2 Software Estimation Methodologies and Models -- 6.2.1 Expert Estimation -- 6.2.1.1 Work and Activity Decomposition -- 6.2.1.2 System Decomposition -- 6.2.1.3 The Delphi Methods -- 6.2.2 Using Benchmark Size Data -- 6.2.2.1 Lines of Code Benchmark Data -- 6.2.2.2 Function Point Benchmark Data -- 6.2.3 Estimation by Analogy -- 6.2.3.1 Traditional Analogy Approach -- 6.2.3.2 Analogy Summary -- 6.2.4 Proxy Point Estimation Methods -- 6.2.4.1 Meta-Model for Effort Estimation -- 6.2.4.2 Function Points -- 6.2.4.2.1 COSMIC Function Points -- 6.2.4.3 Object Points -- 6.2.4.4 Use Case Sizing Methodologies -- 6.2.4.4.1 Use Case Points Methodology -- 6.2.4.4.2 Example: Use Case Point Methodology Example: Home Security System -- 6.2.4.4.3 Use Case Point Methodology Effectiveness -- 6.2.5 Custom Models -- 6.2.6 Algorithmic Models -- 6.2.6.1 Manual Models -- 6.2.6.2 Estimating Project Duration -- 6.2.6.3 Tool Based Models -- 6.3 Combining Estimates -- 6.4 Estimating Issues -- 6.4.1 Targets vs. Estimates -- 6.4.2 The Limitations of Estimation - Why? -- 6.4.3 Estimate Uncertainties -- 6.5 Estimating Early and Often -- 6.6 Estimation Summary -- 6.7 Estimation Problems -- 6.8 Estimation Project - Theater Tickets -- References -- 7. In Praise of Defects: Defects and Defect Metrics -- 7.1 Why study and measure defects?.; 7.2 Faults vs. failures -- 7.3 Defect Dynamics and Behaviors -- 7.3.1 Defect Arrival Rates -- 7.3.2 Defects vs. Effort -- 7.3.3 Defects vs. Staffing -- 7.3.4 Defect Arrival Rates vs. Code Production Rate -- 7.3.5 Defect Density vs. Module Complexity -- 7.3.6 Defect Density vs. System Size -- 7.4 Defect Projection Techniques and Models -- 7.4.1 Dynamic Defect Models -- 7.4.1.1 Rayleigh Models -- 7.4.1.2 Exponential and S-Curves Arrival Distribution Models -- 7.4.1.3 Empirical Data and Recommendations for Dynamic Models -- 7.4.2 Static Defect Models -- 7.4.2.1 Defect Insertion and Removal Model -- 7.4.2.2 Defect Removal Efficiency - A Key Metric -- 7.4.2.3 Static Defect Model Tools -- 7.5 Additional Defect Benchmark Data -- 7.5.1 Defect Data By Application Domain -- 7.5.2 Cumulative Defect Removal Efficiency (DRE) Benchmark -- 7.5.3 SEI Levels and Defect Relationships -- 7.5.4 Latent Defects -- 7.5.5 Other Defects Benchmarks and a Few ; Recommendations+ -- 7.6 Cost Effectiveness of Defect Removal by Phase -- 7.7 Defining and Using Simple Defect Metrics: An example -- 7.8 Some Paradoxical Patterns for Customer Reported Defects -- 7.9 Defect Summary -- 7.10 Problems -- 7.11 Projects -- 7.12 Answers to the initial questions -- References -- 8. Software Reliability Measurement and Prediction -- 8.1 Why study and measure software reliability? -- 8.2 What is reliability? -- 8.3 Faults and failures -- 8.4 Failure Severity Classes -- 8.5 Failure Intensity -- 8.6 The Cost of Reliability -- 8.7 Software Reliability Theory -- 8.7.1 Uniform and Random Distributions -- 8.7.2 The probability of failure during a time interval -- 8.7.3 F(t) - The Probability of Failure by time t -- 8.7.4 R(t) - The Reliability Function -- 8.7.5 Reliability Theory Summarized -- 8.8 Reliability Models -- 8.8.1 Types of Models -- 8.8.2 Predicting Number of Defects Remaining -- 8.8.3 Reliability Growth Models -- 8.8.4 Model Summary -- 8.9 Failure Arrival Rates -- 8.9.1 Predicting Failure Arrival Rates Using Historical Data.; 8.9.2 Engineering Rules for MTTF -- 8.9.3 Musa's Algorithm -- 8.9.4 Operational Profile Testing -- 8.9.5 Predicting Reliability Summary -- 8.10 But when do I ship? -- 8.11 System Configurations: Probability and Reliability -- 8.12 Answers to Initial Question -- 8.13 Reliability Summary -- 8.14 Reliability Exercises -- 8.15 Reliability Project -- References -- 9. Response Time and Availability -- 9.1 Response Time Measurements -- 9.2 Availability -- 9.2.1 Availability Factors -- 9.2.2 Outage Scope -- 9.2.3 Complexities in Measuring Availability -- 9.2.4 Software Rejuvenation -- 9.2.4.1 Software Aging -- 9.2.4.2 Classification of Faults -- 9.2.4.3 Software Rejuvenation Techniques -- 9.2.4.4 Impact of Rejuvenation on Availability -- 9.3 Summary -- 9.4 Problems -- 9.5 Project -- References -- 10. Measuring Progress -- 10.1 Project Milestones -- 10.2 Code Integration -- 10.3 Testing Progress -- 10.4 Defects Discovery and Closure -- 10.4.1 Defect Discovery -- 10.4.2 Defect Closure -- 10.5 Process Effectiveness -- 10.6 Summary -- References -- Problems -- 11. Outsourcing -- 11.1 The "O" Word -- 11.2 Defining Outsourcing -- 11.3 Risks Management and Outsourcing -- 11.4 Metrics and the Contract -- 11.5 Summary -- References -- Exercises -- Problems -- Chapter 11 Sidebar -- 12. Financial Measures for the Software Engineer -- 12.1 It's All About the Green -- 12.2 Financial Concepts -- 12.3 Building the Business Case -- 12.3.1 Understanding Costs -- 12.3.1.1 Salaries -- 12.3.1.2 Overhead Costs -- 12.3.1.3 Risk Costs -- 12.3.1.3.1 Identifying Risk -- 12.3.1.3.2 Assessing Risks -- 12.3.1.3.3 Planning for Risk -- 12.3.1.3.4 Monitoring Risk -- 12.3.1.4 Capital versus Expense -- 12.3.2 Understanding Benefits -- 12.3.3 Business Case Metrics -- 12.3.3.1 Return on Investment -- 12.3.3.2 Pay-Back Period -- 12.3.3.3 Cost/Benefit Ratio -- 12.3.3.4 Profit & Loss Statement -- 12.3.3.5 Cash Flow -- 12.3.3.6 Expected Value -- 12.4 Living the Business Case -- 12.5 Summary -- References -- Problems.; Projects -- 13. Benchmarking -- 13.1 What is Benchmarking -- 13.2 Why Benchmark -- 13.3 What to Benchmark -- 13.4 Identifying and Obtaining a Benchmark -- 13.5 Collecting Actual Data -- 13.6 Taking Action -- 13.7 Current Benchmarks -- 13.8 Summary -- References -- Problems -- Projects -- 14. Presenting Metrics Effectively to Management -- 14.1 Decide on the Metrics -- 14.2 Draw the Picture -- 14.3 Create a Dashboard -- 14.4 Drilling for Information -- 14.5 Example for the Big Cheese -- 14.6 Evolving Metrics -- 14.7 Summary -- References -- Problems -- Project -- Index.
• Sommario/riassunto: This book serves as a practical guide to metrics and quantitative software estimation, beginning with the foundations of measurement and metrics, and then focuses on techniques and tools for estimation ; of the required effort and the resulting quality of a software project.

Model Validation and Uncertainty Quantification, Volume 3 : Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014 / / edited by H. Sezer Atamturktur, Babak Moaveni, Costas Papadimitriou, Tyler Schoenherr

• Record Nr.: UNINA9910299731403321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
• ISBN: 87-438-0259-1; 87-7004-891-6; 3-319-04552-0
• Edizione: [1st ed. 2014.]
• Descrizione fisica: 1 online resource (419 p.)
• Collana: Conference Proceedings of the Society for Experimental Mechanics Series, , 2191-5652
• Disciplina: 624.171
• Soggetti: Multibody systems; Vibration; Mechanics, Applied; Aerospace engineering; Astronautics; Solids; Multibody Systems and Mechanical Vibrations; Aerospace Technology and Astronautics; Solid Mechanics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Calibration of System Parameters Under Model Uncertainty -- On the Aggregation and Extrapolation of Uncertainty From Component to System Level Models -- Validation of Strongly Coupled Models: A Framework for Resource Allocation -- Fatigue Monitoring in Metallic Structures Using Vibration Measurements -- Uncertainty Propagation in Experimental Modal Analysis -- Quantification of Prediction Bounds ; Caused by Model Form Uncertainty -- Composite Fuselage Impact Testing and Simulation: A Model Calibration Exercise -- Noise Sensitivity Evaluation of Autoregressive Features Extracted From Structure Vibration -- Uncertainty Quantification and Integration in Multi-level Problems -- Reliability Quantification of High-speed Naval Vessels Based on SHM Data -- Structural Identification Using Response Measurements Under Base Excitation -- Bayesian FE Model Updating in the Presence of Modeling Errors -- Maintenance Planning Under Uncertainties Using a Continuous-state POMDP Framework -- Achieving Robust Design through Statistical Effect Screening -- Automated Modal Parameter Extraction and Statistical Analysis of the New Carquinez Bridge Response to Ambient Excitations -- Evaluation of a Time Reversal Method with Dynamic Time Warping matching function for human Fall Detection Using Structural Vibrations -- Uncertainty Quantification of Identified Modal Parameters Using the Fisher Information Criterion -- Excitation Related Uncertainty in Ambient Vibration Testing of Bridges -- Experiment-based Validation and Uncertainty Quantification of Coupled Multi-scale Plasticity Models -- Model Calibration and Uncertainty Quantification of A600 Blades -- Validation Assessment for Joint Problem Using an Energy Dissipation Model -- A Bayesian Damage Prognosis Approach Applied to Bearing Failure -- Sensitivity Analysis of Beams Controlled by Shunted Piezoelectric Transducers -- A Principal Component Analysis (PCA) Decomposition Based Validation Metric for use with Full Field Measurement Situations -- FEMCalibration With FRF Damping Equalization -- Evaluating Initial Model for Dynamic Model Updating: Criteria and Application -- Evaluating Convergence of Reduced Order Models Using Nonlinear Normal Modes -- Approximate Bayesian Computation for Finite Element Model Updating -- An Efficient Method for the Quantification of the Frequency Domain Statistical Properties of Short Response Time Series of Dynamic Systems -- Quantifying Uncertainty in Modal Parameters Estimated Using Higher Order Time Domain Algorithms -- Detection of Stress-stiffening Effect on Automotive Components -- Approach to Evaluate Uncertainty in Passive and Active Vibration Reduction -- Project-oriented Validation on a Cantilever Beam Under Vibration Active Control -- Inferring structural variability using modal analysis in a Bayesian framework -- Including SN-Curve Uncertainty in Fatigue Reliability Analyses of Wind Turbines -- Robust Design of Notching Profile under Epistemic Model Uncertainties -- Optimal Selection of Calibration and Validation Test Samples Under Uncertainty -- Uncertainty Quantification in Experimental Structural Dynamics Identification of Composite Material Structures -- Analysis of Numerical Errors in Strongly Coupled Numerical Models -- Robust Expansion of Experimental Mode Shapes Under Epistemic Uncertainties.
• Sommario/riassunto: This critical collection examines a range of model validation and uncertainty quantification, from uncertainty propagation in structural dynamics to practical applications of MVUQ, as presented in early findings and case studies from the Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014. The collection includes papers in the following general technical research areas: · Uncertainty Quantification & Model Validation · Uncertainty Propagation in Structural Dynamics · Bayesian & Markov Chain Monte Carlo Methods · Practical Applications of MVUQ · Advances in MVUQ & Model Updating.