Demo Data from EDBT 2026 / reviewers in the wild / expert
Biplab Kar
dblp:154/6485
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2
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
2 papers |
Software testing · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computing education · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data models and query languages · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing
test input generation |
0.4 | 2 | 2015 | Data generation for testing and grading SQL queries · VLDB J. 2015 The XDa-TA system for automated grading of SQL query assignments · ICDE 2015 |
Computing education
automated assessment |
0.2 | 1 | 2015 | The XDa-TA system for automated grading of SQL query assignments · ICDE 2015 |
Data models and query languages
SQL |
0.2 | 1 | 2015 | Data generation for testing and grading SQL queries · VLDB J. 2015 |
Methods — techniques the papers use, named apart from their topics
grading · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | The XDa-TA system for automated grading of SQL query assignmentsabstractGrading of student SQL queries is usually done by executing the query on sample datasets (which may be unable to catch many errors) and/or by manually comparing/checking a student query with the correct query (which can be tedious and error prone). In this demonstration we present the XDa-TA system which can be used by instructors and TAs for grading SQL query assignments automatically. Given one or more correct queries for an SQL assignment, the tool uses the XData system to automatically generate datasets that are designed specifically to catch common errors. The grading is then done by comparing the results of student queries with those of the correct queries against these generated datasets; instructors can optionally provide additional datasets for testing. The tool can also be used in a learning mode by students, where it can provide immediate feedback with hints explaining possible reasons for erroneous output. This tool could be of great value to instructors particularly, to instructors of MOOCs. Amol Bhangdiya, Bikash Chandra, Biplab Kar, Bharath Radhakrishnan, K. V. Maheshwara Reddy, Shetal Shah, S. Sudarshan 0001 |
ICDE | 3 |
| 2015 | Data generation for testing and grading SQL queries
Bikash Chandra, Bhupesh Chawda, Biplab Kar, K. V. Maheshwara Reddy, Shetal Shah, S. Sudarshan 0001 |
VLDB J. | 3 |