Software measurement is a new way of managing software development. By collecting critical measurements during the system development process, QA, project managers, even management level can track and control development variables. Collecting the appropriate measures cuts development costs through accurate estimating, requirements management and control of scope and risks.

Nowadays, more and more organizations are focusing process improvement. But few can relate hard data regarding the benefits they have derived from investment for such activity.
Measurement is just needed to provide objective analysis and quantitative baseline (a snapshot of the organization's productivity levels, quality levels, schedules, and costs at the time of the assessment). It can answer questions, for example:

• Field-reported defects
• Cost variance
• Schedule variance
• Functional variance

Then how to implement a effective measurement program and how to use them is problem. Normally following generic process is useful for understanding and solving problem:
Raw data - Information - Knowledge - Actions - Results
To translate raw data into meaningful information, metrics and models are needed. To translate information into knowledge, we need analysis of the metrics and models in the context of the team's experience. To formulate effective actions, we further need analysis and information on cause-and-effect relationships and good decisions. To support action implementation and to evaluate the results, we again need data, measurements, metrics, and models.

Basili's Goal/Question/Metrics approach is widely used as measurement paradigm. We can regard it as top to bottom method. But metrics and measurement must progress and mature with the development process of the organization. If the development process is in the innitial stage of the maturity spectrum, a heavy focus on metrics may be counterproductive. So, in such situation, Goal/Question/Metrics approach seems not flexible. Herewith, we propose bottom to top method -

• Analyze existing data organization had and easily collected, for example, the size of product, the defect data during system test and field.
• Consider applying metrics using above raw data according to industry practice, for example, system test effectiveness.
• Raise the related question to help client make decision, for example, what test strategy would make us more effective to avoid field defects?
• Consider oppotunity to raise and apply more metrics.

Kasse Initiatives, LLC, Evolving a Measurement Program for Systems and Software Engineering Process Improvement , CMMI 2003, Denver, Colorado

Ray Madachy, QUANTITATIVE PROCESS MANAGEMENT AND SOFTWARE QUALITY MANAGEMENT, USC Computer Science

SOFTWARE MEASUREMENT GUIDEBOOK Revision 1, SOFTWARE ENGINEERING LABORATORY SERIES, SEL-94-102, NASA

Robert E. Park, Wolfhart B. Goethert, William A. Florac, Goal-Driven Software Measurement - A Guidebook, CMU/SEI-96-HB-002

Christiane Gresse, Barbara Hoisl, Jurgen Wust, A Process Model for GQM-Based Measurement, STTI-95-04-E, Software-Technologie-Transfer-Initiative Kaiserslautern

Daskalantonakis, M. K., A Practical View of Software Measurement and Implementation Experiences Within Motorola, IEEE Transaction on Software Engineering, Vol. SE-18, 1992, pp. 998-1010

S. H. Kan, V. R. Basili, L. N. Shapiro, Software quality: An overview from the perspective of total quality management, IBM System Journal, Software Quality, Volume 33, Number 1, Page 4 (1994).

Jon T. Huber Efficiency and Effectiveness Measures To Help Guide the Business of Software Testing. Application of Software Measurement, 1999, HP.

S. H. Kan, J. Parrish, and D. Manlove In-process metrics for software testing. IBM System Journal, Technology for e-business, Volume 40, Number 1, 2001.

Ryan, L. Software usage metrics for real-world software testing. Spectrum, IEEE, April 1998, pp. 64-68.

Kulik, Peter J., A Practical Approach to Software Metrics, IEEE IT Professional, Jan/Feb 2000
Kulik, Peter J., Software Metrics State of the Art -2000

L. Rosenberg, Ph.D., Developing An Effective Metrics Program

Hakan Olin, Peter Eriksson, Metrics Tools

Robert W. Ferguson, A Project Risk Metric

S. H. Kan, Modeling and software development quality IBM SYSTEMS JOURNAL, VOL 30, NO 3, 1991 [about Rayleigh Model Framework]

William A. Florac, Robert Park, Anita D. Carleton, Practical Software Measurement: Measuring for Process Management and Improvement , Handbook, CMU/SEI-97-HB-003

D. McAndrews, Establishing a Software Measurement Process , Technical Report, CMU/SEI-93-TR-016

Robert E. Park, Wolfhart B. Goethert, William A. Florac, Goal-Driven Software Measurement–A Guidebook , Technical Report, CMU/SEI-96-HB-002

Wolfhart Goethert Matt Fisher , Deriving Enterprise-Based Measures Using the Balanced Scorecard and Goal-Driven Measurement Techniques , Technical Note, CMU/SEI-2003-TN-024

Sholom Cohen, Dave Zubrow, Ed Dunn, Case Study: A Measurement Program for Product Lines , Technical Note, CMU/SEI-2004-TN-023

Wolfhart Goethert, Jeannine Siviy, Applications of the Indicator Template for Measurement and Analysis , Technical Note, CMU/SEI-2004-TN-024

Robert Park, Software Size Measurement: A Framework for Counting Source Statements , Technical Report, CMU/SEI-92-TR-020

Wolfhart B. Goethert, Elizabeth K. Bailey, Mary B. Busby, Software Effort & Schedule Measurement: A Framework for Counting Staff-hours and Reporting Schedule Information , Technical Report, CMU/SEI-92-TR-021

William Florac , Software Quality Measurement: A Framework for Counting Problems and Defects , Technical Report, CMU/SEI-92-TR-022

• IEEE Std 982.1-1988, IEEE Standard Dictionary of Measures to Produce Reliable Software (ANSI)
• IEEE Std 1045-1992, IEEE Standard for Software Productivity Metrics (ANSI)

Ishikawa's Seven Basic Tools: Checklist/Check Sheet, Pareto Diagram, Histogram, Run Chart, Scatter Diagram, and Control Chart.

Phase-based Defect Removal Model, including famous Defect Origin/Where Matrix, and Phase Defect Removal and Injection Rates table.

Software Reliability Models:

• Static Model: linear-regression model, BBN, etc.
• Dynamic Model:
  • those that model the entire development process, for example, the Reileigh Model.
    
  • those that model the back-end testing phase, software reliability growth model, for example, NHPP model.

Effort/Outcome model, for example, Inspection Effort/Defect Rate Matrix

Software Measurement related Informations from

Software Metricsfrom www.projectreference.com

Software Engineering Measurement and Analysis (SEMA) from SEI

Focusing on:

• Software Cost Estimation
• Software Tracking & Control
• Software Metrics Analysis

History of Software Measurement by Horst Zuse

They use proven measurement techniques, such as functional size measurement, to demonstrate where improvement can be made and they help client to make them. Measures are customized to meet YOUR company needs using the Goal Question Metric approach (first introduced by Victor Basili). They also use the Software Engineering Institute's four recommended measures: size, duration, resources, and schedule. Their clients include government and a wide variety of industries -- working with Executives, Project Managers, QA Specialists, Estimators, Contract Specialists, and others.

Practical Software and Systems Measurement (PSM) was developed to meet today's software and system technical and management challenges. It is an information-driven measurement process that addresses the unique technical and business goals of an organization. The guidance in PSM represents the best practices used by measurement professionals within the software and system acquisition and engineering communities. PSM:

• Is sponsored by the Department of Defense and the US Army
• Provides Project Managers with objective information needed to successfully meet cost, schedule, and technical objectives
• Is based on best measurement practices of DoD, government and industry programs
• Is a flexible process
• Defines an information-driven analysis approach
• Supports current software and system acquisition and measurement policy
• Provides a basis for enterprise level management
• Is compatible with the ISO/IEC 15939 standard, Software Measurement Process

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United Kingdom Software Metrics Association

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Software Measurement Services

Longstreet Consulting:
Software measurement that is on target!

Software Metrics Sites:
Training, consulting and other services

PROMISE SOFTWARE ENGINEERING REPOSITORY:
Here you will find a collection of publicly available datasets and tools to serve researchers in building predictive software models (PSMs) and software engineering community at large.

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