Name
Abstract | ||
|---|---|---|
We describe two prototypical elements of a World Wide Web-based system for visualization and analysis of data produced in the software development process. Our system incorporates interactive applets and visualization techniques into Web pages. A particularly powerful example of such an applet, SeeSoft^{\mathrm{TM}}, can display thousands of lines of text on a single screen, allowing detection of patterns not discernible directly from the text. In our system, Live Documents replace static statistical tables in ordinary documents by dynamic Web-based documents, in effect allowing the “reader” to customize the document as it is read. Use of the Web provides several advantages. The tools access data from a very large central data base, instead of requiring that it be downloaded; this ensures that readers are always working with the most up-to-date version of the data, and relieves readers of the responsibility of preparing data for their use. The tools encourage collaborative research, as one researcher’s observations can easily be replicated and studied in greater detail by other team members. We have found this particularly useful while studying software data as part of a team that includes researchers in computer science, software engineering, and statistics, as well as development managers. Live documents will also help the Web revolutionize scientific publication, as papers published on the Web can contain Java applets that permit readers to confirm the conclusions reached by the authors’ statistical analyses. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1023/A:1019299211575 | World Wide Web |
Keywords | Field | DocType |
World Wide,Software Engineering,Visualization Technique,Software Data Analysis,Development Manager | Web design,Web development,Data mining,World Wide Web,Web page,Computer science,Web standards,Data Web,Web modeling,Web-based simulation,Web server | Journal |
Volume | Issue | ISSN |
1 | 2 | 1573-1413 |
Citations | PageRank | References |
7 | 1.12 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephen G. Eick | 1 | 1032 | 172.21 |
| Audris Mockus | 2 | 4031 | 308.78 |
| Todd L. Graves | 3 | 707 | 53.09 |
| Alan F. Karr | 4 | 1005 | 76.93 |