EDBT 2026 Demo / reviewers in the wild / expert
Yuanxiang Ji
dblp:24/10027
· DBLP profile ↗
2ranked-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 · 1Human-computer interaction and ubiquitous computing · 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 |
Software maintenance and evolution · 50% Program synthesis and code generation · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › bug triage
bug report management |
0.4 | 1 | 2020 | Stay Professional and Efficient: Automatically Generate Titles for Your Bug Reports · ASE 2020 |
Methods — techniques the papers use, named apart from their topics
sequence-to-sequence model · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Stay Professional and Efficient: Automatically Generate Titles for Your Bug ReportsabstractBug reports in a repository are generally organized line by line in a list-view, with their titles and other meta-data displayed. In this list-view, a concise and precise title plays an important role that enables project practitioners to quickly and correctly digest the core idea of the bug, without carefully reading the corresponding details. However, the quality of bug report titles varies in open-source communities, which may be due to the limited time and unprofessionalism of authors. To help report authors efficiently draft good-quality titles, we propose a method, named iTAPE, to automatically generate titles for their bug reports. iTAPE formulates title generation into a one-sentence summarization task. By properly tackling two domain-specific challenges (i.e. lacking off-the-shelf dataset and handling the low-frequency human-named tokens), iTAPE then generates titles using a Seq2Seq-based model. A comprehensive experimental study shows that iTAPE can obtain fairly satisfactory results, in terms of the comparison with three latest one-sentence summarization works, as well as the feedback from human evaluation. Songqiang Chen, Xiaoyuan Xie, Bangguo Yin, Yuanxiang Ji, Lin Chen 0015, Baowen Xu |
ASE | 4 |
| 2014 | Design of a Multiple Bloom Filter for Distributed Navigation RoutingabstractUnmanned navigation of vehicles and mobile robots can be greatly simplified by providing environmental intelligence with dispersed wireless sensors. The wireless sensors can work as active landmarks for vehicle localization and routing. However, wireless sensors are often resource scarce and require a resource-saving design. In this paper, a multiple Bloom-filter scheme is proposed to compress a global routing table for a wireless sensor. It is used as a lookup table for routing a vehicle to any destination but requires significantly less memory space and search effort. An error-expectation-based design for a multiple Bloom filter is proposed as an improvement to the conventional false-positive-rate-based design. The new design is shown to provide an equal relative error expectation for all branched paths, which ensures a better network load balance and uses less memory space. The scheme is implemented in a project for wheelchair navigation using wireless camera motes. Ping Jiang 0001, Yuanxiang Ji, Xiaonian Wang, Yongqiang Cheng 0001 |
IEEE Trans. Syst. Man Cybern. Syst. | 2 |