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
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
IEEE Transactions on Software Engineering - Special issue on software reliability
In-process improvement through defect data interpretation
IBM Systems Journal
Software Process Evolution at the SEL
IEEE Software
Machine Learning Approaches to Estimating Software Development Effort
IEEE Transactions on Software Engineering
Knowledge discovery in databases terminology
Advances in knowledge discovery and data mining
Software Metrics: A Rigorous Approach
Software Metrics: A Rigorous Approach
Advanced Scout: Data Mining and Knowledge Discovery in NBA Data
Data Mining and Knowledge Discovery
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
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
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
Validation of an Approach for Improving Existing Measurement Frameworks
IEEE Transactions on Software Engineering
A simulation-based dynamic evaluation methodology for enterprise process performance
MS'06 Proceedings of the 17th IASTED international conference on Modelling and simulation
A methodology for dynamic enterprise process performance evaluation
Computers in Industry
Software measurement programs in SMEs - defining software indicators: a methodological framework
PROFES'07 Proceedings of the 8th international conference on Product-Focused Software Process Improvement
Towards innovation measurement in the software industry
Journal of Systems and Software
A decision support framework for metrics selection in goal-based measurement programs: GQM-DSFMS
Journal of Systems and Software
Hi-index | 0.01 |
Software organizations are in need of methods for understanding, structuring, and improving the data they are collecting. This paper discusses an approach for use when a large number of diverse metrics are already being collected by a software organization. The approach combines two methods. One looks at an organization's measurement framework in a top-down fashion and the other looks at it in a bottom-up fashion. The top-down method, based on the goal-question-metric (GQM) paradigm, is used to identify the measurement goals of data users. These goals are then mapped to the metrics being used by the organization, allowing us to: (1) identify which metrics are and are not useful to the organization, and (2) determine whether the goals of data user groups can be satisfied by the data that are being collected by the organization. The bottom-up method is based on a data mining technique called attribute focusing (AF). Our method uses this technique to identify useful information in the data that the data users were not aware of. We describe our experience in analyzing data from a software customer satisfaction survey at IBM to illustrate how the AF technique can be combined with the GQM paradigm to improve measurement and data use inside software organizations.