EDBT 2026 Demo / reviewers in the wild / expert
Satia Herfert
dblp:178/1640
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
—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 |
Software testing · 50% Debugging and program repair · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Debugging and program repair
fault localization |
0.3 | 1 | 2017 | Automatically reducing tree-structured test inputs · ASE 2017 |
Software testing › test optimization
test input reduction |
0.3 | 1 | 2017 | Automatically reducing tree-structured test inputs · ASE 2017 |
Methods — techniques the papers use, named apart from their topics
tree transformation · 0.3greedy backtracking · 0.3delta debugging · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Automatically reducing tree-structured test inputsabstractReducing the test input given to a program while preserving some property of interest is important, e.g., to localize faults or to reduce test suites. The well-known delta debugging algorithm and its derivatives automate this task by repeatedly reducing a given input. Unfortunately, these approaches are limited to blindly removing parts of the input and cannot reduce the input by restructuring it. This paper presents the Generalized Tree Reduction (GTR) algorithm, an effective and efficient technique to reduce arbitrary test inputs that can be represented as a tree, such as program code, PDF files, and XML documents. The algorithm combines tree transformations with delta debugging and a greedy backtracking algorithm. To reduce the size of the considered search space, the approach automatically specializes the tree transformations applied by the algorithm based on examples of input trees. We evaluate GTR by reducing Python files that cause interpreter crashes, JavaScript files that cause browser inconsistencies, PDF documents with malicious content, and XML files used to tests an XML validator. The GTR algorithm reduces the trees of these files to 45.3%, 3.6%, 44.2%, and 1.3% of the original size, respectively, outperforming both delta debugging and another state-of-the-art algorithm. Satia Herfert, Jibesh Patra, Michael Pradel |
ASE | 1 |