Issue No. 01 - January/February (1999 vol. 11)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/69.755633
<p><b>Abstract</b>—Construction and maintenance of large, high-quality software projects is a complex, error-prone, and difficult process. Tools employing software database metrics can play an important role in efficient execution and management of such large projects. In this paper, we present a generic framework to address this problem. This framework incorporates database and knowledge-base tools, a formal set of software test and evaluation metrics, and a suite of advanced analytic techniques for extracting information and knowledge from available data. The proposed combination of critical metrics and analytic tools can enable highly efficient and cost-effective management of large and complex software projects. The framework has potential for greatly reducing venture risks and enhancing the production quality in the domain of large software project management.</p>
Knowledge-based tools for software project management, efficiency and robustness in large-scale software development, knowledge abstraction from raw data, software metrics databases, test and evaluation, cost-effective project management.
M. F. Khan, T. L. Kunii, Y. Shinagawa and R. A. Paul, "Software Metrics Knowledge and Databases for Project Management," in IEEE Transactions on Knowledge & Data Engineering, vol. 11, no. , pp. 255-264, 1999.