Demo Data from EDBT 2026 / reviewers in the wild / expert
Andy Maule
dblp:75/5092
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author
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 |
Program analysis · 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 |
|---|---|---|---|---|
Program analysis
data flow analysis |
0.1 | 1 | 2008 | Impact analysis of database schema changes · ICSE 2008 |
Program analysis
static analysis |
0.1 | 1 | 2008 | Impact analysis of database schema changes · ICSE 2008 |
Data models and query languages › schema management
schema evolution |
0.0 | 1 | 2008 | Impact analysis of database schema changes · ICSE 2008 |
Methods — techniques the papers use, named apart from their topics
program slicing · 0.2context-sensitive analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Impact analysis of database schema changesabstractWe propose static program analysis techniques for identifying the impact of relational database schema changes upon object-oriented applications. We use dataflow analysis to extract all possible database interactions that an application may make. We then use this information to predict the effects of schema change. We evaluate our approach with a case-study of a commercially available content management system, where we investigated 62 versions of between 70k-127k LoC and a schema size of up to 101 tables and 568 stored procedures. We demonstrate that the program analysis must be more precise, in terms of context-sensitivity than related work. However, increasing the precision of this analysis increases the computational cost. We use program slicing to reduce the size of the program that needs to be analyzed. Using this approach, we are able to analyse the case study in under 2 minutes on a standard desktop machine, with no false negatives and a low level of false positives. Andy Maule, Wolfgang Emmerich, David S. Rosenblum |
ICSE | 1 |