Second Workshop on Software Quality
Proceedings of the 26th International Conference on Software Engineering
Third workshop on software quality
Proceedings of the 27th international conference on Software engineering
Workshop description of 4th workshop on software quality (WOSQ)
Proceedings of the 28th international conference on Software engineering
Workshop description of 4th workshop on software quality (WOSQ)
Proceedings of the 2006 international workshop on Software quality
Fifth Workshop on Software Quality
ICSE COMPANION '07 Companion to the proceedings of the 29th International Conference on Software Engineering
WoSQ '07 Proceedings of the 5th International Workshop on Software Quality
Ontology-supported quality assurance for component-based systems configuration
Proceedings of the 6th international workshop on Software quality
Sixth workshop on software quality
Companion of the 30th international conference on Software engineering
Seventh workshop on Software Quality
ICSE '09 COMPANION Proceedings of the 2009 31st International Conference on Software Engineering: Companion Volume
Information Technology and Management
SPDW+: a seamless approach for capturing quality metrics in software development environments
Software Quality Control
A novel metric of software quality: structural availability
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
Information Resources Management Journal
Hi-index | 0.01 |
Traditional software metrics, such as code coverage, McCabe complexity, etc. address the needs of a software engineer. In contrast, managers of software development organizations face a broader set of issues. For example, an executive responsible for multiple products and releases has to understand the customer views of those products and put in place, appropriate actions across the products that will be of high business value. This paper presents examples of data and metrics associated with service (i.e. product support) for fieldreported problems and customer critical situations, and customer satisfaction ratings across a comprehensive range of software product attributes. Issues arising in the data integration, analysis, and correlation of these metrics are highlighted. A systematic methodology for statistical analysis of the data that enables management to derive key, actionable drivers of change through the metrics is presented. We also present an outline of a decision support system developed at IBM for tracking and using software metrics to enable executives to make better informed decisions in supporting their products.