UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) Load Bearing Walls: Early Sizing Estimation In The NOSTROMO Tool (U) Dan Strickland Dynetics Program Software Support Ashley Mathis THAAD Project Office System Software Engineering Brandon Gautney Dynetics Program Software Support DISTRIBUTION STATEMENT A – Approved for public release; distribution is unlimited. 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 2 Overview (U) Background Area of Opportunity Heuristic Model Subcomponent Weight Complexity Weight NOSTROMO Concept NOSTROMO Additions 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 3 Background (U) PSY-CHIC

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 4 Boehm Horn Curve (U) [Ref (1) - SOFTWARE COST ESTIMATION WITH COCOMO II (P 10) - BOEHM 2000] Size (and effort) should converge over time relative to development phase During Concept of Operation, estimates can be 50% to 200% of the actual final size 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 5 4x 2x 1.5x 1.25x 0.25x 0.5x x Concept of Operations Requirements Spec Preliminary Design Spec. Detailed Design Spec. Qualified Software Area of Opportunity (U) Area between Concept of Operations and Requirements Specification when early size estimation is key Early sizing method needs to have accuracy within this area 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 6 Roetzheim Heuristic Model (U) Project Scope Table Project Class Table Project Type Table Project taxonomies are a method for estimating Function Points (FP) Function Points are a language independent approach for estimating software development effort Roetzheim, William. “Estimating and Managing Project Scope for New Development.”Cross Talk April T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 7 Heuristic Model Results Projects Parameters Results Most large, complex programs use SLOC as system of delivery for their sizing metrics “Backfiring” is a method for converting FPs to an estimated corresponding number of Software Lines of Code (SLOC) 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 8 Heuristic Model Results (cont’d) Projects 2 & 3 are within acceptable boundaries of the Area of Opportunity. Project estimated totals are within 14% of the actual size. 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 9 Subcomponents (U) Project Parameters 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 10 Heuristic Model With Subcomponents Results Heuristic Model performance improves when coupled with Subcomponent Weight. Projects 2 & 3 are within acceptable boundaries of the Area of Opportunity. Project estimated totals are within 13% of the actual size. 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 11 Complexity (U) Problem Complexity Code Complexity Data Complexity Jones, Capers T. Estimating Software Cost. New York: McGraw Hill, T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 12 Heuristic Model With Complexity Results Project Parameters Results 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 13 Heuristic Model With Complexity Results (cont’d) Heuristic Model performance is slightly improved when coupled with Complexity Weight. Projects 2 & 3 are within acceptable boundaries of the Area of Opportunity. Project estimated totals are within 5% of the actual size. 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 14 Project Parameters Complete Heuristic Model - Combined Heuristic Model with Subcomponent Weight and Complexity Weight 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 15 Complete Heuristic Model Results - Combined Heuristic Model with Subcomponent Weight and Complexity Weight Heuristic Model performance improves when coupled with Subcomponent Weight and Complexity Weight. Projects 2 & 3 are within acceptable boundaries of the Area of Opportunity. Project estimated totals are within 3% of the actual size. 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 16 Original NOSTROMO Concept (U) NOSTROMO first takes normal COCOMO II inputs NOSTROMO accounts for uncertainty in the settings NOSTROMO uses Monte Carlo to simulate hundreds of COCOMO II estimates using the inputs and uncertainties NEWT – NOSTROMO Entry Writing Tool – a Delphi polling tool that captures Uncertainty NEWT DATA PAGE REPORTS NOSTROMO Notional Obscurity STatistical Risk Observation MOdel 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 17 New NOSTROMO Concept (U) NEWT DATA PAGE REPORTS NOSTROMO DEFAULT UNCERTAINTY COMBINATION AGC CALCULATOR NOSTROMO offers: multiple methods for inputting Uncertainty combination of subcomponents AGC methodology Pessimistic SLOC estimation Early Size Estimation PESSIMISM EARLY SIZE ESTIMATION 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 18 NOSTROMO Input Sheet – Notional Data (U) Software Item Name Scale Factors Code Size Cost Drivers Iterations Putnam Productivity Function Buttons Conditional Formatting Pessimism Toggle Early Size Estimation 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 19 NOSTROMO Early Size Estimation Worksheet – Notional Data (U) Allows the user the option to use the Weighted Subcomponents and Weighted Complexity with the Heuristic Model in NOSTROMO to calculate Function Points. Heuristic Model estimates the number of Function Points and Backfires them into SLOC. Allows the user to copy the results into NOSTROMO Input Sheet. 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 20 NOSTROMO Outputs – Notional Data (U) 410 KSLOC – Estimated SLOC410 KSLOC – ESLOC vs. Effort 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 21 Demonstration 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 22 Future NOSTROMO Additions and Efforts (U) Addition of Exception Conditions from Ray Madachy’s Expert COCOMO Transition to an application environment (MS-Access or.NET) Expansion of the NOSTROMO tool to address other COCOMO Family models with uncertainties COSYSMO – especially relevant in development of complex DoD systems COSOSIMO – System of Systems models are becoming increasingly prevalent in DoD efforts COQUALMO – Defect Prediction Models Expansion of the NOSTROMO methodology and tool into Readiness Level models Software Readiness Levels (SWRL) Technology Program Management Model (TPMM) 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 23 Conclusion (U) Early and accurate estimation of software size metrics provides a method of true software cost estimation Estimating software size accurately during the Area of Opportunity will increase the fidelity of the estimate When analogous data is unavailable or unreliable, use of a heuristic model can produce accurate metrics for size New NOSTROMO methodology incorporates code size estimate heuristic model to provide better answers earlier 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 24 BACKUP 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 25 Distributions of Uncertainty (U) Setting n-1 Setting n Setting n+1 Level 1 - Certain Level 2 - Low Uncertainty - Normal Level 3 - Medium Uncertainty - Triangle Level 4 - High Uncertainty - Uniform NOSTROMO assumes ceiling and floor limits of the highest and lowest default values for each COCOMO II Scale Factor and Cost Driver NOSTROMO changes the distribution and sets the high and low points based on the level of uncertainty with each factor 07T

UNCLASSIFIED Approved for Public Release 07-MDA-2965 (26 OCT 07) 26 NOSTROMO Application (U) Microsoft Excel worksheet with attached macros and Visual Basic code Currently on version (as of 10/17/07) Does not use outside applications for Monte Carlo simulation (standard random number generation from Visual basic) Limited testing performed on a proof-of-concept application Suggest limiting Monte Carlo run size to runs Generates two pages of output – Data and Charts Data page contains all outputs from Monte Carlo simulation, charting data, and histograms Charts page contains Confidence Intervals for output of COCOMO II and Putnam models, charts, and histograms NOSTROMO – Data Sheet and CM Control Sheet are Developer pages and should not be removed 07T