Copyright Jack H. Arabian 7/28/05 1 COCOMO Process Mapping And Discrete Event Simulation For Defect Costing And Scheduling Estimation Jack H. Arabian.

Slides:



Advertisements
Similar presentations
1)List and briefly describe the three project quality management processes. Quality Planning: Identify which quality standards are relevant to project.
Advertisements

Statistical Analysis at BAE NS Making Statistics Part of Decision Making in an Engineering Organization Card, Domzalski, Davies IEEE Software, May/June.
METODOLOGI SIX SIGMA PERTEMUAN 9 ( Perhitungan Statistik) OLEH: EMELIA SARI.
Desktop Business Analytics -- Decision Intelligence l Time Series Forecasting l Risk Analysis l Optimization.
Fahri BaturOctober 2013 SAP GRC AC ARA Access Risk Analysis Requirements Gathering Workshop.
Chapter 5 Some Important Discrete Probability Distributions
Copyright 2000, Stephan Kelley1 Estimating User Interface Effort Using A Formal Method By Stephan Kelley 16 November 2000.
Stepan Potiyenko ISS Sr.SW Developer.
Chapter 3 Simulation Software
Applying COCOMO II Effort Multipliers to Simulation Models 16th International Forum on COCOMO and Software Cost Modeling Jongmoon Baik and Nancy Eickelmann.
Decision Support Systems for Supply Chain Management Chap 10 王仁宏 助理教授 國立中正大學企業管理學系 ©Copyright 2001 製商整合科技中心.
SIMULATION. Simulation Definition of Simulation Simulation Methodology Proposing a New Experiment Considerations When Using Computer Models Types of Simulations.
University of Southern California Center for Software Engineering CSE USC ©USC-CSE 3/11/2002 Empirical Methods for Benchmarking High Dependability The.
UNCLASSIFIED Schopenhauer's Proof For Software: Pessimistic Bias In the NOSTROMO Tool (U) Dan Strickland Dynetics Program Software Support
Business Driven Technology Unit 3 Streamlining Business Operations Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution.
DECISION SUPPORT FOR RE-PLANNING OF SOFTWARE PRODUCT RELEASES S. M. Didar-Al-Alam Dept. of Computer Science University of Calgary, Calgary, AB, Canada.
Chapter 12: Simulation and Modeling Invitation to Computer Science, Java Version, Third Edition.
MIS 175 Spring 2002 Chapter 101 Management Information Systems Transaction Processing Systems (TPS) –Support operation –Management and control –Routine,
12 Steps to Useful Software Metrics
Using Simulation in Understanding the Dynamic of Business Processes By Phinsuda Tarmy MBA 731 Fall 2007.
Monte Carlo Simulation 1.  Simulations where random values are used but the explicit passage of time is not modeled Static simulation  Introduction.
BVBI Infotech Pvt Ltd  Marketing And Sales : Practical drawbacks without Mobility  Sales Force not having up to date product information during Customer.
Computer Simulation A Laboratory to Evaluate “What-if” Questions.
Filename/###, #1 assured communications™ 28-Aug-15 What does an IE Do? An Industrial Engineer can study various fields which include: –Quality –Manufacturing.
1 Software Quality Engineering CS410 Class 5 Seven Basic Quality Tools.
McGraw-Hill/Irwin Copyright © 2011 The McGraw-Hill Companies, All Rights Reserved Chapter 14 Enterprise Resource Planning Systems.
CSIS3600 Systems Analysis and Design System Implementation and Testing.
CLEANROOM SOFTWARE ENGINEERING.
Callis ApS, Copyright © Reviewer Training Material Callis Reviewer version 1.1.
Chapter 1 Introduction to Simulation
1 Validation & Verification Chapter VALIDATION & VERIFICATION Very Difficult Very Important Conceptually distinct, but performed simultaneously.
Joint tracking in friction stir welding Paul Fleming Vanderbilt University Welding Automation Laboratory.
Chapter 14: Inspection  Basic Concept and Generic Process  Fagan Inspection  Other Inspection and Related Activities.
Joint tracking in Friction Stir Welding Paul Fleming Vanderbilt University Welding Automation Laboratory.
1 Management Information Systems Transaction Processing Systems (TPS) –Support operation –Management and control –Routine, normal operations Management.
Welcome to Lean Six Sigma Green Belt Training
1 OM2, Supplementary Ch. D Simulation ©2010 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible.
CS532 Term Paper Applying Six Sigma Methodology In Software Engineering Sourabh Bandyopadhyay.
1 Advanced topics in OpenCIM 1.CIM: The need and the solution.CIM: The need and the solution. 2.Architecture overview.Architecture overview. 3.How Open.
Software Requirements Engineering: What, Why, Who, When, and How
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Chap 5-1 Chapter 5 Some Important Discrete Probability Distributions Basic Business Statistics.
Chapter 1 Business Driven Technology MANGT 366 Information Technology for Business Chapter 1: Management Information Systems: Business Driven MIS.
Management Theory Instructor Abdel Fatah Afifi MA&T, MBA, ACPA, PCT.
QA Methodology By Rajib Roy Independent Consultant Qcon.
Copyright © 2008, SAS Institute Inc. All rights reserved. Interactive Analysis and Data Visualization Using JMP −Dara Hammond, Federal Systems Engineer.
Lecture Introduction to Software Development SW Engg. Development Process Instructor :Muhammad Janas khan Thursday, September.
TEPM 6304: Quality Improvement in Project Management Project Quality Management & Course Overview.
Process Improvement Methodologies References (sources of graphics): (1)Fiore, Clifford, Accelerated Product Development: Combining Lean and Six Sigma for.
Modeling and simulation of systems Simulation languages Slovak University of Technology Faculty of Material Science and Technology in Trnava.
McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved. 1.
Modeling and Simulation of Survey Collection Using Paradata Presented by: Kristen Couture Co-authored by: Yves Bélanger Elisabeth Neusy.
McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
1 Software Engineering: A Practitioner’s Approach, 7/e Chapter 2 Process: A Generic View Software Engineering: A Practitioner’s Approach, 7/e Chapter 2.
To what extent should management be involved in Lean implementations? 1 Sam Tomas.
© 2002 Six Sigma Academy Eliminate Waste Reduce Variability Growth Six Sigma Elements Six Sigma is a business philosophy that employs a client-centric,
Jonathan Atzmon, ISE/ETM Dr. Joan Burtner, Advisor Last Revised 03/03/15 Atzmon ETM , Simulation in Healthcare, Spring 2015, Dr. Joan Burtner 1.
Software Engineering1  Verification: The software should conform to its specification  Validation: The software should do what the user really requires.
Monte-Carlo based Expertise A powerful Tool for System Evaluation & Optimization  Introduction  Features  System Performance.
Rational Unified Process Fundamentals Module 4: Core Workflows II - Concepts Rational Unified Process Fundamentals Module 4: Core Workflows II - Concepts.
Data Collection & Analysis ETI 6134 Dr. Karla Moore.
Copyright , Dennis J. Frailey CSE Software Measurement and Quality Engineering CSE8314 M00 - Version 7.09 SMU CSE 8314 Software Measurement.
T EST T OOLS U NIT VI This unit contains the overview of the test tools. Also prerequisites for applying these tools, tools selection and implementation.
OXFORD SOFTWARE ENGINEERING Software Engineering Services & Consultancy Slide 1.1 © OSEL 2005 Page 1 of 30 Analysis of Defect (and other) Data SPIN London,
Modelling & Simulation of Semiconductor Devices Lecture 1 & 2 Introduction to Modelling & Simulation.
What’s New for the MES Product Suite Tom Hechtman & Jason Coope.
IMPLEMENTING LEAN SIX SIGMA IN THE PALESTINE POULTRY COMPANY
Project Management PTM721S
Deploying and Configuring SSIS Packages
Simulation Department of Industrial Engineering Anadolu University
Presented By: Darlene Banta
Presentation transcript:

Copyright Jack H. Arabian 7/28/05 1 COCOMO Process Mapping And Discrete Event Simulation For Defect Costing And Scheduling Estimation Jack H. Arabian

Copyright Jack H. Arabian 7/28/05 2 COCOMO  Introduction  Requirements  Procedure  Outcome  Analysis  Live Demo  Future Work

Copyright Jack H. Arabian 7/28/05 3 COCOMO Technique: Process mapping combined with Discrete Event Simulation New opportunities to create true System of Systems (SoS) models Predict future outcomes by creating scenarios For engineering processes To detect defects To predict/estimate costs and scheduling. Introduction

Copyright Jack H. Arabian 7/28/05 4 COCOMO Requirements Examine/document engineering defect detection process. Collect/collate the parameters of each step Use statistical distributions for non-constant, time- varying parameters. Calculate cost and schedule to compare with past performance. Time-simulate the process with known “as-is” parameters Create required scenarios with “what-if” parameters

Copyright Jack H. Arabian 7/28/05 5 COCOMO Simplified Process Map Import Generated KSLOC Detect Defects Count & Document In-Phase Defects Out of Phase Defects Identified and Processed in Later Phases Collect/ Collate All Defects Solve Defect Problem Implement and Review Release Estimate Future Costs and Schedule Generalized Software Defects Detection Cost and Schedule Estimation Process In-Phase Defect Out-of-Phase Defect To Phases Following

Copyright Jack H. Arabian 7/28/05 6 COCOMO Completed Process Map (Expandable for legibility)

Copyright Jack H. Arabian 7/28/05 7 COCOMO Typical Sub-Model

Copyright Jack H. Arabian 7/28/05 8 COCOMO This Activity has this dialogue box Multiple tabs for categories of information Multiple tabs for categories of information Variable time, “Q” for different scenarios Sub-Model Activity

Copyright Jack H. Arabian 7/28/05 9 COCOMO  Introduction  Requirements  Procedure  Outcome  Analysis  Live Demo  Future Work

Copyright Jack H. Arabian 7/28/05 10 COCOMO Scenario Outcome/Analysis

Copyright Jack H. Arabian 7/28/05 11 COCOMO Live Demo Demonstration of process mapping and simulation shows dynamic, graphic animation of the flow of defects from one phase to another. A dashboard during each run displays relevant variables in real time to show performance in defect prediction and estimation capabilities for software development cost and schedule.

Copyright Jack H. Arabian 7/28/05 12 COCOMO This model is generic to many processes Hardware defects in a manufacturing production line Quality Assurance and Six Sigma practices Business (order process, Help desk) Finance (transactions) Healthcare (claims processing) Aerospace (radar tracking, checklist, countdown, communications, command and control) Shipbuilding (welding, supply chain). Future Work

Copyright Jack H. Arabian 7/28/05 13 COCOMO Thank you Q&A