Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/69.755633 | IEEE Trans. Knowl. Data Eng. |
Keywords | Field | DocType |
evaluation metrics,large software project management,high-quality software project,software metrics knowledge,generic framework,project management,critical metrics,cost-effective management,software test,software database metrics,complex software project,large project,knowledge based systems,software metric,data mining,computer aided software engineering,cost effectiveness,software project management,software testing,software metrics,knowledge base | Data mining,Computer science,Software peer review,Software project management,Software quality,Software construction,Team software process,Software sizing,Software framework,Software development,Database | Journal |
Volume | Issue | ISSN |
11 | 1 | 1041-4347 |
Citations | PageRank | References |
11 | 0.91 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raymond A. Paul | 1 | 459 | 54.55 |
| Tosiyasu L. Kunii | 2 | 1081 | 291.64 |
| Yoshihisa Shinagawa | 3 | 1900 | 124.80 |
| Muhammad F. Khan | 4 | 11 | 0.91 |