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Domain-Oriented Modeling, Estimation and Improvement for Aerospace. Jairus Hihn Jet Propulsion Laboratory, California Institute of Technology. November 2, 2011 26 th International Forum on COCOMO and Systems/Software Cost Modeling. Background. JPL is a FFRDC for NASA operated by Caltech

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Jairus hihn jet propulsion laboratory california institute of technology

Domain-Oriented Modeling, Estimation and Improvement for Aerospace

Jairus HihnJet Propulsion Laboratory, California Institute of Technology

November 2, 2011

26th International Forum on COCOMO

and

Systems/Software Cost Modeling


Background
Background Aerospace

  • JPL is a FFRDC for NASA operated by Caltech

  • JPL is a highly decentralized organization that allows great autonomy to its project managers at all levels

  • JPL’s Engineering and Science Directorate (3000 people) has twice been certified at CMMI ML 3 (2007, 2010)

    • Approximately 1000 people ($253M/year budget) in the software community

  • This raises the question

    • How do we do it

    • How do we measure it?

  • We turn process sins into virtues


Data sources
Data Sources Aerospace

  • Data Sources

    • Metrics Collection at Key Milestones

    • Software Inventory (2006, 2007, 2009 and 2011)

    • Process performance measures (Tailoring Record, Work Product Checklist)

    • Defect tracking systems (PRS, ISA, AAMS, local databases)

    • SQI Surveys and Contact Log

    • Product and Process Quality Assurance Activities

    • Customer Feedback

  • Communicate results as widely as possible

    • State of Software Report

    • Noontime seminars

    • Section manager meetings

3


Measuring process performance
Measuring Process Performance Aerospace

  • Overall performance is used to establish baselines

  • Identifying the least performed activities provides a short list from which stakeholders can be engaged to discuss process improvement opportunities.

  • Metrics use is one of the least performed activities


Jpl cost and planning models
JPL Cost and Planning Models Aerospace

  • Collect data at major milestones for mission critical and mission support software

    • Labor intensive requiring numerous interviews

      • MSL flight software required 30-35 interviews

  • Enables us to

    • Calibrate cost models

    • Develop effort by role

      • use to do schedule models but they no longer work

    • Effort growth from PDR

    • Cost to repair defects

    • Size growth

  • Enables cost research

    • Data mining models developed with Tim Menzies (WVU)


Baselines and trends
Baselines and Trends Aerospace

Project Flight Software

  • How are we doing?

    • Trends Suggest Improvements in process discipline

    • Projects following a disciplined process exhibit below average budget growth and higher productivity rates

6


Nasa software cost improvement task
NASA Software Cost improvement Task Aerospace

Year 1: Establish Process and Product Baseline

  • Product: Report that documents current state of practice at NASA with set of improvement recommendations and recommended metrics.

    Year 2:

  • Core team works to facilitate the implementation of high priority recommendations across the Agency through a tailorable Agency-wide process. Institute a cost metrics repository to gather information on cost estimate accuracy and cost estimation processes.

    Year 3:

  • Initiate a series of annual reports on NASA software cost estimation accuracy and cost estimation practices.

    • Continue to monitor and make recommendations