Quantitative Software Management was founded in 1978 by Lawrence H. Putnam, a world-renowned expert in the software measurement industry. Since its inception, QSM’s mission has been to develop effective solutions for software estimating, project control, productivity improvement analysis, and risk mitigation. With world headquarters in Washington DC, and regional offices in Massachusetts, England, and The Netherlands, QSM has established itself as the leading total solution provider of choice for software developers in high performance mission-critical environments. Its leading comprehensive suite of products, entitled Software Lifecycle Management (SLIM) is the household brand for decision makers in Fortune 500 companies such as IBM, MOTOROLA, and EDS, as well as government and military organizations such as the U.S. Department of Defense.
World Headquarters
2000 Corporate Ridge, Suite 900 McLean, Virginia 22102
Tel: (800) 424-6755 Fax: (703) 749-3795 www.qsm.com
AP P E N D I X A MO D E L BU I L D E R S – CO M M E R C I A L SO F T W A R E DE S C R I P T I O N S
PA R A M E T R I C ES T I M A T I N G HA N D B O O K
AP P E N D I X A MO D E L BU I L D E R S – CO M M E R C I A L SO F T W A R E DE S C R I P T I O N S
PA R A M E T R I C ES T I M A T I N G HA N D B O O K
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Appendix A-34 International Society of Parametric Analysts
r2 Estimator™
The r2Estimator is a Microsoft Windows®-based software decision-support tool offered by r2Estimating, LLC that implements the Ross Software Estimating Framework (rSEF). It helps users
• Estimate how much a project will cost, how long it will take, how many people will be required and when, and how many defects will be
delivered.
• Estimate a project according to the relationships used in other software estimating models (facilitates crosschecking and validating existing estimates).
• Hierarchically structure projects according to the scope of each project element and families of elements.
• Interactively and dynamically examine all the possible outcomes of a project in terms of the confidence (probability of success) associated with each estimated value.
• Share and justify findings with a rich set of charts and reports. Feature Summary
The r2Estimator
• Implements the rSEF set of equations that determine duration, effort, cost, staffing, and defects as a function of size, efficiency, management stress, and defect vulnerability.
• Manages a user-extensible set of development project categories, each of which "coarse-tunes" the model for the type of software development being proposed by describing a specific instantiation of the rSEF equations based on either:
● Regression analysis applied to some historical data set (e.g., r2 Database Avionics Software – ESLOC, ISBSG Database 4GL on Mainframe Platform – IFPUG UFP, etc.); or
● The mathematical behavior of some commercially-available model for which the parameters and equations are in the public domain (e.g., COCOMO 81, COCOMO II, Jensen, Norden-Putnam-Rayleigh, etc.). • Manages a user-extensible set of development profiles within each
category, each of which "fine-tunes" the model within that particular category (e.g., Flight Controls as a profile within the r2 Database Avionics Software – ESLOC category).
• Includes COCOMO II parameter GUI for determining rSEF equation parameters as part of COCOMO II emulation.
• Includes Jensen Model parameter GUI for determining rSEF equation parameters as part of Jensen Model emulation.
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International Society of Parametric Analysts Appendix A-35
• Allows the user to specify uncertainty associated with the independent variables (size, efficiency, and defect vulnerability) by triangular distribution [Lowest, Most Likely, Highest].
• Determines probability distributions associated with the dependent
variables (duration, effort, cost, and defects) by Monte Carlo simulation at all levels of the project.
• Supports a hierarchical project structure (WBS) with drag and drop GUI that includes the following element types:
● Project Summary Element ● Summary Element
● Decomposition Element ● Construction Element ● Integration Element
● User Defined Task Element ● Cost Only Element
● Event (milestone) Element
• Allows the user to specify, for each element (except Cost Only and Event elements), the staffing profile shape as being either piecewise linear or Rayleigh with shaping control over each function including non-zero start and finish staff levels.
• Includes multiple notes logging (sequence, author, date, message text) for each element in the hierarchy.
• Displays three synchronized interactive Ross charts (probabilistic bivariate tradeoff for each of effort versus duration, cost versus duration, and
defects versus duration) for all Construction Elements. Each Ross chart includes:
● Tradeoff curve with limit regions ● Drag-able solution symbol ● Dynamic confidence range bars ● Drag-able desired probability symbols ● Drag-able goal symbols
● Hover metrics display on all drag-able items
● Right-click pop-up data entry dialog boxes for all drag-able items ● Scalable axes
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Appendix A-36 International Society of Parametric Analysts
• Displays an interactive Gantt chart for each non-Construction element showing its parent and all of its parent's offspring. Each Gantt chart includes:
● Drag-able element schedule bars ● Confidence range bars
● Drag-able desired probability indices ● Drag-able goal indices
● Hover metrics display on all drag-able items
● Right-click pop-up data entry dialog boxes for all drag-able items ● Scalable axes
• Displays a staffing chart for all non-construction elements, date-
synchronized with its associated Gantt chart. Each staffing chart includes: ● Required staffing curve
● Available staffing curve ● Scalable axes
• Displays tab-organized metrics reports and charts including: ● Project results
● Element metrics ● Element inputs ● Notes
● Duration CDF (confidence probability versus duration value) ● Effort CDF (confidence probability versus effort value) ● Cost CDF (confidence probability versus cost value)
● Delivered defects CDF (confidence probability versus delivered defects value)
● Staffing
• Produces graphics that are copy-able to other Microsoft Windows applications.
• Produces user-definable XML-formatted metrics reports.
• Produces and maintains XML-formatted Project Files and Default Files. • Provides export of a Project File’s WBS to Microsoft Project®
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International Society of Parametric Analysts Appendix A-37
Ross Charts Solution Symbol Expectation Confidence Limit Desired Probability Goal Commitment Cumulative Distribution Range Possible Outcomes Range color changes
from red to green when goal is met with desired
probability
Example Ross Chart (Cost versus Duration)
r2Estimator implements a new chart called a Ross Chart that is a graphical display of the confidence (probability of success) and goal satisfaction of two correlated random variables. Ross Charts consist of:
• A two-dimensional Cartesian axis and coordinate system;
• A line or curve representing the correlation (relationship) between the two random variables;
• Indication(s) of the relationship’s limit(s) (reasonable range);
• Interactive dynamic solution symbol on the relationship curve representing a specific instance (solution) of the relationship;
• Dynamic projection lines from the solution symbol to each axis;
• Dynamic cumulative distribution range symbol on the axis-ends of each projection line, each range symbol indexed in increments of 10% confidence probability and representing its corresponding random variable’s cumulative distribution function (CDF);
• Interactive dynamic confidence limit (risk tolerance) symbol on each cumulative distribution range symbol;
• Interactive dynamic goal symbol on each axis representing the goal/commitment value associated with the corresponding variable.
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Appendix A-38 International Society of Parametric Analysts
Ross Software Estimating Framework
The Ross Software Estimating Framework (rSEF) is a set of general software effort, duration, and defects estimating relationships that are based on the notion that software construction is the application of effort (labor) over some duration (period of elapsed calendar time) that produces a desired software product (size) and undesired byproducts (defects). The fundamental rSEF relationships are
Software Productivity Law
( )αE ( )αt Size
Effort Duration
Efficiency
× =
Defect Propensity Law ( ) ( ) E t Effort Defects Defect Vulnerability Duration ϕ ϕ − = Management Stress Law
( )
Effort Management Stress
Durationγ
=
Brooks’ Law (Limit) – Minimum Time
( ) ( ) max min max min t Effort Management Stress Duration Effort Management Stress Duration γ γ ≥ ∴ =
Parkinson’s Law (Limit) – Minimum Effort ( ) ( ) min min min min E Effort Management Stress Duration Effort Management Stress Duration γ γ ≤ ∴ =
rSEF Parameters Included in Category Specification • Effort Exponent αE
• Duration Exponent αt
• Defect Effort Exponent ϕE
• Defect Duration Exponent ϕt
• Gamma γ
• Minimum Management Stress Mmin
• Nominal (Typical) Management Stress Mnom • Maximum Management Stress Mmax
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• Efficiency Scale Vector ηˆ (Efficiency values from -3 standard deviations to +3 standard deviations in increments of 0.5 standard deviations)
• Defect Vulnerability Scale Vector ˆδ (Defect Vulnerability values from -3 standard deviations to +3 standard deviations in increments of 0.5 standard deviations)
rSEF Parameters Included in Profile Specification • Efficiency 3-point Estimate η= ⎣⎡ηLowest,ηMost Likely,ηHighest⎤⎦ Defect Vulnerability 3-point Estimate δ= ⎣⎡δLowest,δMost Likely,δHighest⎤⎦
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Appendix A-40 International Society of Parametric Analysts