Code vectors: understanding programs through embedded abstracted symbolic traces. - Jordan Henkel; Shuvendu K. Lahiri; Ben Liblit; Thomas W. Reps (ESEC/SIGSOFT FSE, 2018)

Artifact for Code Vectors: Understanding Programs Through Embedded Abstracted Symbolic Traces. - Jordan Henkel; Shuvendu K. Lahiri; Ben Liblit; Thomas W. Reps (Zenodo, 2018)

Artifact for Code Vectors: Understanding Programs Through Embedded Abstracted Symbolic Traces. - Jordan Henkel; Shuvendu K. Lahiri; Ben Liblit; Thomas W. Reps (Zenodo, 2018)

Artifact for Code Vectors: Understanding Programs Through Embedded Abstracted Symbolic Traces. - Jordan Henkel; Shuvendu K. Lahiri; Ben Liblit; Thomas W. Reps (Zenodo, 2018)

Enabling Open-World Specification Mining via Unsupervised Learning. - Jordan Henkel; Shuvendu K. Lahiri; Ben Liblit; Thomas W. Reps (CoRR, 2019)

Learning from, understanding, and supporting DevOps artifacts for docker. - Jordan Henkel; Christian Bird; Shuvendu K. Lahiri; Thomas W. Reps (ICSE, 2020)

A Dataset of Dockerfiles. - Jordan Henkel; Christian Bird; Shuvendu K. Lahiri; Thomas W. Reps (MSR, 2020)

ICSE 2020 Artifact for: Learning from, Understanding, and Supporting DevOps Artifacts for Docker. - Jordan Henkel; Christian Bird; Shuvendu K. Lahiri; Thomas W. Reps (Zenodo, 2020)

Shipwright: A Human-in-the-Loop System for Dockerfile Repair. - Jordan Henkel; Denini Silva; Leopoldo Teixeira; Marcelo d'Amorim; Thomas W. Reps (ICSE, 2021)

ICSE'21 Artifact for the paper Shipwright: A Human-in-the-Loop System for Dockerfile Repair. - Jordan Henkel; Denini Silva; Leopoldo Teixeira; Marcelo d'Amorim; Thomas W. Reps (Zenodo, 2021)

Semantic Robustness of Models of Source Code. - Jordan Henkel; Goutham Ramakrishnan; Zi Wang; Aws Albarghouthi; Somesh Jha; Thomas W. Reps (SANER, 2022)

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. - Fotis Psallidas; Yiwen Zhu; Bojan Karlas; Jordan Henkel; Matteo Interlandi; Subru Krishnan; Brian Kroth; K. Venkatesh Emani; Wentao Wu 001; Ce Zhang 001; Markus Weimer; Avrilia Floratou; et al. (SIGMOD Rec., 2022)

From Words to Code: Harnessing Data for Program Synthesis from Natural Language. - Anirudh Khatry; Joyce Cahoon; Jordan Henkel; Shaleen Deep; K. Venkatesh Emani; Avrilia Floratou; Sumit Gulwani; Vu Le 002; Mohammad Raza; Sherry Shi; Mukul Singh; Ashish Tiwari 001 (CoRR, 2023)

NL2SQL is a solved problem... Not! - Avrilia Floratou; Fotis Psallidas; Fuheng Zhao; Shaleen Deep; Gunther Hagleither; Wangda Tan; Joyce Cahoon; Rana Alotaibi; Jordan Henkel; Abhik Singla; Alex Van Grootel; Brandon Chow; et al. (CIDR, 2024)

ReAcTable: Enhancing ReAct for Table Question Answering. - Yunjia Zhang; Jordan Henkel; Avrilia Floratou; Joyce Cahoon; Shaleen Deep; Jignesh M. Patel (Proc. VLDB Endow., 2024)

An Empirically-grounded tool for Automatic Prompt Linting and Repair: A Case Study on Bias, Vulnerability, and Optimization in Developer Prompts. - Dhia Elhaq Rzig; Dhruba Jyoti Paul; Kaiser Pister; Jordan Henkel; Foyzul Hassan (CoRR, 2025)