Software Efforts at the NRO Cost Group

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Software Efforts at the NRO Cost Group

• 21st International Forum on COCOMO and Software
  Cost Modeling
• November 8, 2006

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Purpose

• Explain how the NCG uses USCs code counter data
• Introduce NCGs Software Database
• Insight into Difference Application Results and
  Software Trends

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Background

• NCG maps the USC output files to a CSCI/CSC and
  Work Breakdown Structure (WBS)
• Mapping is most meaningful when mapped to the
  lowest functional level possible within the WBS
• Mapping is very labor intensive if done through
  excel spreadsheets or other manual methods

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CSCI/CSC DP/DPAP
CSCI/CSC DP/DPCC
CSCI/CSC DP/DPCU
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Software Database

• NCG created a software database which automates
  the mapping process
• Software database is primary tool for storing ALL
  NCG software related data. Database will provide
• Low level functional breakout
• Traceability to past programs
• Historical representation of development process
• Database will help us better understand trends
  for
• Code Counts
• Staffing Profiles
• Discrepancy Reports (DRs)
• Schedules

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Database Functionality

• Database allows for the importation of
• Code counter output files for any language
• Difference Application output files
• CSCI/CSC listing
• Staffing data
• DR data
• Cost and Hours
• Programmatic/Technical data
• Database allows the mapping of output file folder
  paths to a WBS and CSCI/CSC

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• Walkthrough of Software Databases Key
  Functionalities

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Unmap
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Insight into Difference Application Results and
Software Trends
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Introduction

• NCG collects datasheet information regarding
  program Complexity Attributes
• This can be defined as Program Development
  Environment data
• e.g. Number of years of experience of programmers
  
• We also collect USC output files for LOC and
  Reuse trends
• We collect Staffing Profiles
• Staffing Profiles are broken out by CSCI
• We collect Discrepancy Reports (DRs)
• DRs are broken out by Priorities and ranked in
  some manner
• Are there any useful trends if we analyze all the
  data collectively?

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CSCI 1 Example
Below is a summary of CSCI 1
Code reaches stable point
Heritage code written in C and remainder written
in C
New code looks proportional to Staffing !!!
Increase in staff to fix DRs
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CSCI 2 Example

• Below is a summary of CSCI 2

Heritage code written in C and remainder written
in C
Keep an eye on the peak staffing levels
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CSCI 3 Example

• Below is a summary of CSCI 3

Heritage code written in C and remainder written
in C
Peak staffing trend?
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CSCI 4 Example

• Below is a summary of CSCI 4

Low Modified code trend continues
Heritage code written in C and remainder written
in C
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CSCI 5 Example

• Below is a summary of CSCI 5

Any guess on why this looks different from the
previous trends?
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Reuse

• This CSCI shows the usefulness of breaking out
  New and Deleted code from the Total code counts
• What assessment can be made of this development?
• Unstable requirements?
• Re-writing same code?
• Code cleanup occurring after each New code
  delivery?

Code looks stable at this point, but in reality,
it was dynamic!!
Total counts show change, but without Diff, you
cant see why
Deleted code size is proportional to previous New
code size
Notice that there is nearly 5,000 New SLOC and
5,000 Deleted SLOC Doesnt look STABLE
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More on Reuse

• USC Diff results can provide better insight
  into how much Reuse came from heritage programs
• Example
• Program B uses Program A software as a starting
  point
• Program A metrics
• 50,841 Total Logical Code Counts
• Program B is completed and returns the following
  metrics
• 1,937,167 Total Logical Code Counts

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More on Reuse (cont.)

• Run Diff counter on the initial baseline (in
  this case, Program A) and the final baseline
  (Program B)
• Diff results show
• New Logical code 1,918,011
• Deleted Logical code 31,685
• Modified Logical code 5,701
• Unmodified Logical code 13,455
• Compute Reuse from Program A
• Unmodified (at Program B completion) / Total (at
  Program B start)
• 13,455 / 50,841 26
• 26 of Program A was DIRECT reuse into Program
  B
• This is not 26 of Program B!
• This is one way to simplify the Reuse problem

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Operators / Tokens

• Here are 8 types of operators that could be
  counted
• Logical
• ,
• Trigonometric
• Cos(), Sin(), Tan(), Cot(), Csc(), Sec()
• Log
• Log(), Ln ()
• Preprocessor
• , Sizeof()
• Math
• , -, , /, sqrt(), ,
• Assignment
• Pointers
• Conditional
• if, else, switch, case, ?
• As well as, Nesting of the loops
• Level 1 loop
• Level 2 loop

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Complexity Density Ratios

• Here are snapshots at various baselines of a CSCI
• If we only looked at the final numbers, we would
  assume nearly 450,000 Logical lines of code
• What do you make of this????

A growth of 371,868 Logical SLOC
What productive developers!
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Complexity Density Ratios (cont)

• Looking at the Complexity Density Ratio for
  different operators, we can understand more about
  the development

Code looks different
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Complexity Density Ratios (cont)

• Looking at the SW as an entity, composed of many
  different elements, the Complexity Density Ratio
  allows us to see the make up of the SW
• This can be characterized as a signature of the
  SW development!
• In the previous example, the program received SW
  from another project (not directly associated to
  the current project)
• The Complexity Density Ratio validates that the
  SW is different for the ongoing development
• This should be taken into account when trying to
  come up with any productivities
• ANALYST BEWARE!
• DONT BLINDLY USE DATA

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Summary

• The NCG continues to standardize our code
  counting efforts
• Essential for normalizing our data across
  multiple programs, multiple contractors
• The NCG works closely with USC to develop a
  complete USC Code Counting Tool Suite
• Addressing necessities such a new ways of looking
  at reuse, complexities, trends, etc.
• The NCG has invested extensive resources to use
  the USC code counter files and parse the USC
  output files
• Our goal is to establish consistency across the
  Intelligence Community
• Primarily involves our industry contractors