PS&J Software Six Sigma

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Est. 1986

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Products and Services > CMMI > Implementing a CMMI Software Metrics Framework

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Implementing a CMMI Software Metrics Framework

Length:       4 days

Learning Methods:     Lecture and exercises

Location:    Client Site

Includes:    Lecture notes, textbooks, software

Description:  Implementing a CMMI Software Metrics Framework is designed for an organization just starting out with CMMI or a CMM level 2 -3 organization making the transition to CMMI. Explains how to define, implement, and use a software metrics framework consistent with the requirements of the CMMI.  Illustrates the use of software metrics for estimation, decision support project management, process management, and quality management.  Reviews the issues associated with automated data collection and analysis, data security, and data privacy.

Tailoring:    On request

Who should attend this course:

  • Managers

  • Software Team Leads

  • Software Quality Engineers

  • Software Engineering Process Group members

Learning objectives:

  • how the measurement related issues associated with transitioning from the CMM to the CMMI

  • the issues associated with implementing a CMMI measurement framework

  • how to collect and analyze software measurements

  • how to relate process performance measures to business results

  • how to use measurements for estimating, project management, and product quality management

  • how to use measurements for real time decision support

  • how to implement an automated software metrics collection and analysis system

  • how to comply with the measurement related requirements of CMMI

Topics:

Introduction

CMM, CMMI, and Measurement

  • Measurement in the CMM

  • Measurement in the CMMI

  • Transitioning from CMM to CMMI

Measurement, Goals, and Management

GQM Paradigm

Structuring Tasks for Measurement

Defining a Measurement Framework

  • Measuring Effort

  • Measuring Defects

  • Measuring Product Size

  • Derived metrics

  • Measuring Change

  • Measuring Customer Satisfaction

Dealing with Variation

Data Analysis Techniques

  • Histograms and Distribution

  • Functions

  • Pareto Analysis

  • Stratification

Process Modeling

  • Characterizing Process Performance

  • Predicting Process Performance

  • Estimating with Historical Data

Controlling Process Performance

  • Process Stability

  • Run charts and control charts

  • Recognizing trends, shifts, and outliers

  • Managing with Data

  • Product Quality Management

Continuous Improvement

  • Making Effective Improvements

  • Measuring results

  • Calculating ROI

  • Inspection Case Study

Automating Metrics Collection and Analysis

  • Efficient Data Collection

  • Real Time Decision Support

  • Data Security and Privacy

Summary

 

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