Demo Data from EDBT 2026 / reviewers in the wild / expert
Eva May
dblp:149/2747
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 |
Program verification · 77% Program analysis · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification › invariant generation
loop invariant generation |
0.2 | 1 | 2015 | Inferring Loop Invariants by Mutation, Dynamic Analysis, and Static Checking · IEEE Trans. Software Eng. 2015 |
Program analysis
dynamic analysis |
0.1 | 1 | 2015 | Inferring Loop Invariants by Mutation, Dynamic Analysis, and Static Checking · IEEE Trans. Software Eng. 2015 |
Methods — techniques the papers use, named apart from their topics
static checking · 0.2mutation · 0.2dynamic analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Inferring Loop Invariants by Mutation, Dynamic Analysis, and Static CheckingabstractVerifiers that can prove programs correct against their full functional specification require, for programs with loops, additional annotations in the form of loop invariants-properties that hold for every iteration of a loop. We show that significant loop invariant candidates can be generated by systematically mutating postconditions; then, dynamic checking (based on automatically generated tests) weeds out invalid candidates, and static checking selects provably valid ones. We present a framework that automatically applies these techniques to support a program prover, paving the way for fully automatic verification without manually written loop invariants: Applied to 28 methods (including 39 different loops) from various java.util classes (occasionally modified to avoid using Java features not fully supported by the static checker), our DYNAMATE prototype automatically discharged 97 percent of all proof obligations, resulting in automatic complete correctness proofs of 25 out of the 28 methods-outperforming several state-of-the-art tools for fully automatic verification. Juan P. Galeotti, Carlo A. Furia, Eva May, Gordon Fraser 0001, Andreas Zeller |
IEEE Trans. Software Eng. | 3 |