Demo Data from SIGIR 2026 / reviewers in the wild / expert
Haoren Zhao
dblp:282/5896
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—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 synthesis and code generation · 50% Debugging and program repair · 50% | |
| Network and information security
1 paper |
Network security · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Debugging and program repair
automated program repair |
0.4 | 1 | 2020 | FlashRegex: Deducing Anti-ReDoS Regexes from Examples · ASE 2020 |
Program synthesis and code generation › DSL-based synthesis
regular expression synthesis |
0.4 | 1 | 2020 | FlashRegex: Deducing Anti-ReDoS Regexes from Examples · ASE 2020 |
Network security › attack strategy
denial-of-service attack |
0.1 | 1 | 2020 | FlashRegex: Deducing Anti-ReDoS Regexes from Examples · ASE 2020 |
Methods — techniques the papers use, named apart from their topics
neighborhood search · 0.9boolean satisfiability · 0.9programming-by-example · 0.4programming by example · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | FlashRegex: Deducing Anti-ReDoS Regexes from ExamplesabstractRegular expressions (regexes) are widely used in different fields of computer science such as programming languages, string processing and databases. However, existing tools for synthesizing or repairing regexes were not designed to be resilient to Regex Denial of Service (ReDoS) attacks. Specifically, if a regex has super-linear (SL) worst-case complexity, an attacker could provide carefully-crafted inputs to launch ReDoS attacks. Therefore, in this paper, we propose a programming-by-example framework, FlashRegex, for generating anti-ReDoS regexes by either synthesizing or repairing from given examples. It is the first framework that integrates regex synthesis and repair with the awareness of ReDoS-vulnerabilities. We present novel algorithms to deduce anti-ReDoS regexes by reducing the ambiguity of these regexes and by using Boolean Satisfiability (SAT) or Neighborhood Search (NS) techniques. We evaluate FlashRegex with five related state-of-the-art tools. The evaluation results show that our work can effectively and efficiently generate anti-ReDoS regexes from given examples, and also reveal that existing synthesis and repair tools have neglected ReDoS-vulnerabilities of regexes. Specifically, the existing synthesis and repair tools generated up to 394 ReDoS-vulnerable regex within few seconds to more than one hour, while FlashRegex generated no SL regex within around five seconds. Furthermore, the evaluation results on ReDoS-vulnerable regex repair also show that FlashRegex has better capability than existing repair tools and even human experts, achieving 4 more ReDoS-invulnerable regex after repair without trimming and resorting, highlighting the usefulness of FlashRegex in terms of the generality, automation and user-friendliness. Yeting Li, Zhiwu Xu 0001, Jialun Cao, Haiming Chen 0001, Tingjian Ge, Shing-Chi Cheung, Haoren Zhao |
ASE | 7 |