EDBT 2026 Demo / reviewers in the wild / expert
Sunita Rudraraju
dblp:11/965
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Software testing · 44% Empirical software engineering · 44% Operating systems · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
mining software repositories |
0.0 | 1 | 2004 | Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs · IEEE Trans. Software Eng. 2004 |
Software testing
software reliability |
0.0 | 1 | 2004 | Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs · IEEE Trans. Software Eng. 2004 |
Operating systems
workload characterization |
0.0 | 1 | 2004 | Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs · IEEE Trans. Software Eng. 2004 |
Methods — techniques the papers use, named apart from their topics
log analysis · 0.0failure data analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server LogsabstractWe characterize usage and problems for Web applications, evaluate their reliability, and examine the potential for reliability improvement. Based on the characteristics of Web applications and the overall Web environment, we classify Web problems and focus on the subset of source content problems. Using information about Web accesses, we derive various measurements that can characterize Web site workload at different levels of granularity and from different perspectives. These workload measurements, together with failure information extracted from recorded errors, are used to evaluate the operational reliability for source contents at a given Web site and the potential for reliability improvement. We applied this approach to the Web sites www.seas.smu.edu and www.kde.org. The results demonstrated the viability and effectiveness of our approach. Jeff Tian, Sunita Rudraraju |
IEEE Trans. Software Eng. | 2 |