VLDB 2026 Research / reviewers in the wild / expert
Anda Liang
dblp:355/8100
· DBLP profile ↗
4ranked-venue papers
1as first author
4since 2021 · last 2025
0009-0007-4429-2884ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Who's Pushing the Code? An Exploration of GitHub ImpersonationabstractGitHub is one of the largest open-source software (OSS) communities for software development and collaboration. Impersonation in the OSS communities refers to the malicious act of assuming another user's identity, often aiming to gain unauthorized access to code, manipulate project outcomes, or spread misinformation. With several recent real-world attacks resulting from impersonation, this issue is becoming more and more concerning within the OSS community. We present the first exploration of the impact of impersonation in GitHub. Specifically, we conduct structured interviews with 17 real-world OSS contributors about their perception of impersonation and corresponding mitigations. Our study reveals that, in general, GitHub users lack awareness of impersonation and underestimate the severity of its implications. After witnessing a demo of impersonation, they show significant concern for the OSS community. Meanwhile, we also demonstrate that the current best practices (i.e., commit signing) that might mitigate impersonation must be improved to encourage use and adoption. We also present and discuss participant perceptions of potential ways to mitigate GitHub impersonation. We collect a dataset comprising 12.5 million commits to investigate the current status of impersonation. Interestingly, we find out that currently impersonation cannot be easily detected. We observe that existing commit histories treat impersonation behavior identically to pull request events, resulting in a lack of detection methods for impersonation. Yueke Zhang, Anda Liang, Pamela J. Wisniewski, Fengwei Zhang, Kevin Leach, Yu Huang 0015 |
ICSE | 2 |
| 2024 | A Controlled Experiment in Age and Gender Bias When Reading Technical Articles in Software EngineeringabstractOnline platforms and communities are a critical part of modern software engineering, yet are often affected by human biases. While previous studies investigated human biases and their potential harms against the efficiency and fairness of online communities, they have mainly focused on the open source andQ & Aplatforms, such asGitHubandStack Overflow, but overlooked the audience-focused online platforms for delivering programming and SE-related technical articles, where millions of software engineering practitioners share, seek for, and learn from high-quality software engineering articles (i.e.,technical articlesfor SE). Furthermore, most of the previous work has revealed gender and race bias, but we have little knowledge about the effect of age on software engineering practice. In this paper, we propose to investigate the effect of authors’ demographic information (gender and age) on the evaluation of technical articles on software engineering and potential behavioral differences among participants. We conducted a survey-based and controlled human study and collected responses from 540 participants to investigate developers’ evaluation of technical articles for software engineering. By controlling the gender and age of the author profiles of technical articles for SE, we found that raters tend to have more positive content depth evaluations for younger male authors when compared to older male authors and that male participants conduct technical article evaluations faster than female participants, consistent with prior study findings. Surprisingly, different from other software engineering evaluation activities (e.g., code review, pull request, etc.), we did not find a significant difference in the genders of authors on the evaluation outcome of technical articles in SE. Anda Liang, Emerson R. Murphy-Hill, Westley Weimer, Yu Huang 0015 |
IEEE Trans. Software Eng. | 1 |
| 2023 | HealthBridge: A Decentralized and Interoperable Healthcare App for Rare Disease CommunitiesabstractTraditional centralized database systems share many weaknesses, including the overhead of sharing medical documentation, data fragmentation, and susceptibility to centralized data attacks. Those problems would especially influence rare disease patient communities given their higher need for medical data interoperability and security. In this paper, we present an alternative approach to managing healthcare data that is tailored to the rare disease community. Specifically, we design and implement HealthBridge, a decentralized and interoperable mobile application with distributed ledger technology. The underlying permissioned network utilizes Hyperledger Fabric and has a modular design, empowering efficient data transactions directly between trusted entities with predefined smart contracts that regulate access permissions. For the application design, we focus on the needs of the rare disease community, prioritizing ease of use without compromising data security. In particular, our application provides a delegate feature, aimed at supporting rare disease patients with additional needs. Through this feature, if needed, patients can grant pre-defined access permissions to delegates through smart contracts. While the overall implementation of HealthBridge is still in the developmental stages, it presents a proof of concept and a promising system to support the underfunded rare disease community in terms of healthcare interoperability through a permissioned blockchain network. Anda Liang, Wyn Van Devanter, Peng Zhang 0034 |
BIBM | 3 |
| 2023 | A Blockchain-Based Architecture for Interoperable Healthcare Data ExchangeabstractPatients and healthcare providers often face challenges when dealing with creating, reading, updating, sharing, and deleting operations on individual healthcare data due to incompatible electronic medical record systems and the inability to provide necessary data. These challenges can drastically prolong both a patient's diagnosis time and the time until the operation. There are many informational discrepancies when attempting to provide adequate healthcare background - especially with new providers when a full healthcare history is required. To aid in increasing interoperability, we propose a decentralized data-sharing approach. While current centralized solutions own patients’ healthcare data, we seek to put data back in the hands of the patients using blockchain as a decentralized database. In essence, our data-sharing architecture and set of rules leverage a permissioned blockchain network, Hyperledger Fabric, to give each patient on the network the ability to own and control the flow of their healthcare data. Niranjan Sahi, Anda Liang, Sean Mchale, Wyn Van Devanter, Peng Zhang 0034 |
BIBM | 2 |