An empirical validation of software cost estimation models
Communications of the ACM
Evaluating Software Complexity Measures
IEEE Transactions on Software Engineering
Learning from Examples: Generation and Evaluation of Decision Trees for Software Resource Analysis
IEEE Transactions on Software Engineering - Special Issue on Artificial Intelligence in Software Applications
Deriving structurally based software measures
Journal of Systems and Software - An Oregon workshop on software metrics
A mathematical perspective for software measures research
Software Engineering Journal
Methodology for Validating Software Metrics
IEEE Transactions on Software Engineering
Practical software metrics for project management and process improvement
Practical software metrics for project management and process improvement
A Pattern Recognition Approach for Software Engineering Data Analysis
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
A Practical View of Software Measurement and Implementation Experiences Within Motorola
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
A formal program complexity model and its application
Journal of Systems and Software
IEEE Transactions on Software Engineering - Special issue on software reliability
In-process improvement through defect data interpretation
IBM Systems Journal
Managing Code Inspection Information
IEEE Software
Technology Transfer at Motorola
IEEE Software
Software Process Evolution at the SEL
IEEE Software
Machine Learning Approaches to Estimating Software Development Effort
IEEE Transactions on Software Engineering
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
Evaluating software engineering methods and tools part 6: identifying and scoring features
ACM SIGSOFT Software Engineering Notes
An information theory-based approach to quantifying the contribution of a software metric
Journal of Systems and Software
Knowledge discovery in databases terminology
Advances in knowledge discovery and data mining
Software Complexity: Measures and Methods
Software Complexity: Measures and Methods
Advanced Scout: Data Mining and Knowledge Discovery in NBA Data
Data Mining and Knowledge Discovery
Lessons Learned in Building a Corporate Metrics Program
IEEE Software
Case Studies for Method and Tool Evaluation
IEEE Software
Establishing Software Measurement Programs
IEEE Software
Implementing Effective Software Metrics Programs
IEEE Software
A Case Study of Software Process Improvement During Development
IEEE Transactions on Software Engineering
Software Measurement: A Necessary Scientific Basis
IEEE Transactions on Software Engineering
Towards a Framework for Software Measurement Validation
IEEE Transactions on Software Engineering
Algebraic Models and Metric Validation
Proceedings of the BCS-FACS Workshop on Formal Aspects of Measurement
On the use of machine-assisted knowledge discovery to analyze and reengineer measurement frameworks
CASCON '95 Proceedings of the 1995 conference of the Centre for Advanced Studies on Collaborative research
Quantitative evaluation of software quality
ICSE '76 Proceedings of the 2nd international conference on Software engineering
Experiments with computer software complexity and reliability
ICSE '82 Proceedings of the 6th international conference on Software engineering
An approach to improving existing measurement frameworks in software development organizations
An approach to improving existing measurement frameworks in software development organizations
An empirical evaluation of the G/Q/M method
CASCON '93 Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: software engineering - Volume 1
An approach to improving existing measurement frameworks
IBM Systems Journal
A Ranking of Software Engineering Measures Based on Expert Opinion
IEEE Transactions on Software Engineering
Empirical Analysis of Safety-Critical Anomalies During Operations
IEEE Transactions on Software Engineering
Revisiting the problem of using problem reports for quality assessment
Proceedings of the 2006 international workshop on Software quality
A goal question metric based approach for efficient measurement framework definition
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Company-Wide Implementation of Metrics for Early Software Fault Detection
ICSE '07 Proceedings of the 29th international conference on Software Engineering
Perceived vs. measured quality of conceptual schemas: an experimental comparison
ER '07 Tutorials, posters, panels and industrial contributions at the 26th international conference on Conceptual modeling - Volume 83
A model for software rework reduction through a combination of anomaly metrics
Journal of Systems and Software
How Does a Measurement Programme Evolve in Software Organizations?
PROFES '08 Proceedings of the 9th international conference on Product-Focused Software Process Improvement
Assessing multiview framework (MF) comprehensibility and efficiency: A replicated experiment
Information and Software Technology
Metrics for BPEL process context-independency analysis
Service Oriented Computing and Applications
Identification of defect-prone classes in telecommunication software systems using design metrics
Information Sciences: an International Journal
Software process measurement in the real world: dealing with operating constraints
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
Advances in Engineering Software
A decision support framework for metrics selection in goal-based measurement programs: GQM-DSFMS
Journal of Systems and Software
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Software organizations are in need of methods to understand, structure, and improve the data they are collecting. We have developed an approach for use when a large number of diverse metrics are already being collected by a software organization [1], [2]. The approach combines two methods. One looks at an organization's measurement framework in a top-down goal-oriented fashion and the other looks at it in a bottom-up data-driven fashion. The top-down method is based on a measurement paradigm called Goal-Question-Metric (GQM). The bottom-up method is based on a data mining technique called Attribute Focusing (AF). A case study was executed to validate this approach and to assess its usefulness in an industrial environment. The top-down and bottom-up methods were applied in the customer satisfaction measurement framework at the IBM Toronto Laboratory. The top-down method was applied to improve the customer satisfaction (CUSTSAT) measurement from the point of view of three data user groups. It identified several new metrics for the interviewed groups, and also contributed to better understanding the data user needs. The bottom-up method was used to gain new insights into the existing CUSTSAT data. Unexpected associations between key variables prompted new business insights, and revealed problems with the process used to collect and analyze the CUSTSAT data. This paper uses the case study and its results to qualitatively compare our approach against current ad hoc practices used to improve existing measurement frameworks.