Data mining: concepts and techniques
Data mining: concepts and techniques
Spice: The Theory and Practice of Software Process Improvement and Capability Determination
Spice: The Theory and Practice of Software Process Improvement and Capability Determination
Metrics and Models in Software Quality Engineering
Metrics and Models in Software Quality Engineering
An Instrument for Assessing Software Measurement Programs
Empirical Software Engineering
Data Mining of Software Development Databases
Software Quality Control
Guest Editors' Introduction: Global Software Development
IEEE Software
Metrics for Managing Customer View of Software Quality
METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
Computers in Industry - Special issue: Process/workflow mining
Beyond data warehousing: what's next in business intelligence?
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
iBOM: A Platform for Intelligent Business Operation Management
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
The Impact of Institutional Forces on Software Metrics Programs
IEEE Transactions on Software Engineering
Service-Oriented Agility: An initial analysis for the use of Agile methods for SOA development
SCC '05 Proceedings of the 2005 IEEE International Conference on Services Computing - Volume 02
Development of SOA-Based Software Systems - an Evolutionary Programming Approach
AICT-ICIW '06 Proceedings of the Advanced Int'l Conference on Telecommunications and Int'l Conference on Internet and Web Applications and Services
A Guide To The Project Management Body Of Knowledge (PMBOK Guides)
A Guide To The Project Management Body Of Knowledge (PMBOK Guides)
Mining metrics to predict component failures
Proceedings of the 28th international conference on Software engineering
Designing concurrent, distributed, and real-time applications with UML
Proceedings of the 28th international conference on Software engineering
A Hybrid Approach to Cleansing Software Measurement Data
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Business process mining: An industrial application
Information Systems
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
SPDW: A Software Development Process Performance Data Warehousing Environment
SEW '06 Proceedings of the 30th Annual IEEE/NASA Software Engineering Workshop
Using Software Repositories to Investigate Socio-technical Congruence in Development Projects
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
A generic solution for warehousing business process data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Predictive business operations management
International Journal of Computational Science and Engineering
Earned value project management, second edition
Earned value project management, second edition
Understanding developer and manager perceptions of function points and source lines of code
Journal of Systems and Software
Issues on Estimating Software Metrics in a Large Software Operation
SEW '08 Proceedings of the 2008 32nd Annual IEEE Software Engineering Workshop
Web Services: Concepts, Architectures and Applications
Web Services: Concepts, Architectures and Applications
A metric definition, computation, and reporting model for business operation analysis
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Hi-index | 0.00 |
Among the key factors for the success of a metrics program are the regularity of metrics collection, a seamless and efficient data collection methodology, and the presence of non-intrusive automated data collection tools. This paper presents the software process data warehousing architecture SPDW+ as a solution to the frequent, seamless, and automated capturing of software quality metrics, and their integration in a central repository for a full range of analyses. The striking features of the SPDW+ ETL (data extraction, transformation, and loading) approach are that it addresses heterogeneity issues related to the software development context, it is automatable and non-intrusive, and it allows different capturing frequency and latency strategies, hence allowing both analysis and monitoring of software metrics. The paper also provides a reference framework that details three orthogonal dimensions for considering ETL issues in the software development process context, used to develop SPDW+ ETL. The advantages of SPDW+ are: (1) flexibility to meet the requirements of the frequent changes in SDP environments; (2) support for monitoring, which implies the execution of frequent and incremental loads; (3) automation of the complex and time-consuming task of capturing metrics, making it seamless; (4) freedom of choice regarding management models and support tools used in projects; and (5) cohesion and consistency of the information stored in the metrics repository which will be used to compare data of different projects. The paper presents the reference framework, illustrates the key role played by the metrics capturing process in a metrics program using a case study, and presents the striking features of SPDW+ and its ETL approach, as well as an evaluation based on a prototype implementation.