SEALANT: a detection and visualization tool for inter-app security vulnerabilities in Android. - Youn Kyu Lee; Peera Yoodee; Arman Shahbazian; Daye Nam; Nenad Medvidovic (ASE, 2017)

EVA: a tool for visualizing software architectural evolution. - Daye Nam; Youn Kyu Lee; Nenad Medvidovic (ICSE (Companion Volume), 2018)

Toward predicting architectural significance of implementation issues. - Arman Shahbazian; Daye Nam; Nenad Medvidovic (MSR, 2018)

How Do Organizations Publish Semantic Markup? Three Case Studies Using Public Schema.org Crawls. - Daye Nam; Mayank Kejriwal (Computer, 2018)

API Design Implications of Boilerplate Client Code. - Daye Nam (ASE, 2019)

MARBLE: Mining for Boilerplate Code to Identify API Usability Problems. - Daye Nam; Amber Horvath; Andrew Macvean; Brad A. Myers; Bogdan Vasilescu (ASE, 2019)

The Long Tail: Understanding the Discoverability of API Functionality. - Amber Horvath; Sachin Grover; Sihan Dong; Emily Zhou; Finn Voichick; Mary Beth Kery; Shwetha Shinju; Daye Nam; Mariann Nagy; Brad A. Myers (VL/HCC, 2019)

Predictive synthesis of API-centric code. - Daye Nam; Baishakhi Ray; Seohyun Kim 001; Xianshan Qu; Satish Chandra 001 (MAPS@PLDI, 2022)

Towards Characterizing Trust in Generative Artificial Intelligence among Students. - Matin Amoozadeh; David Daniels; Stella Chen; Daye Nam; Aayush Kumar; Michael Hilton; Mohammad Amin Alipour; Sruti Srinivasa Ragavan (ICER (2), 2023)

Improving API Knowledge Discovery with ML: A Case Study of Comparable API Methods. - Daye Nam; Brad A. Myers; Bogdan Vasilescu; Vincent J. Hellendoorn (ICSE, 2023)

In-IDE Generation-based Information Support with a Large Language Model. - Daye Nam; Andrew Macvean; Vincent J. Hellendoorn; Bogdan Vasilescu; Brad A. Myers (CoRR, 2023)

Trust in Generative AI among students: An Exploratory Study. - Matin Amoozadeh; David Daniels; Daye Nam; Stella Chen; Michael Hilton; Sruti Srinivasa Ragavan; Mohammad Amin Alipour (CoRR, 2023)

Exploring Documentation Usage via Page-view Log Analysis. - Daye Nam; Andrew Macvean; Brad A. Myers; Bogdan Vasilescu (CoRR, 2023)

Understanding Documentation Use Through Log Analysis: A Case Study of Four Cloud Services. - Daye Nam; Andrew Macvean; Brad A. Myers; Bogdan Vasilescu (CHI, 2024)

Using an LLM to Help With Code Understanding. - Daye Nam; Andrew Macvean; Vincent J. Hellendoorn; Bogdan Vasilescu; Brad A. Myers (ICSE, 2024)

Student-AI Interaction: A Case Study of CS1 students. - Matin Amoozadeh; Daye Nam; Daniel Prol; Ali Alfageeh; James Prather; Michael Hilton; Sruti Srinivasa Ragavan; Amin Alipour (Koli Calling, 2024)

Trust in Generative AI among Students: An exploratory study. - Matin Amoozadeh; David Daniels; Daye Nam; Aayush Kumar; Stella Chen; Michael Hilton; Sruti Srinivasa Ragavan; Mohammad Amin Alipour (SIGCSE (1), 2024)

User-Centered Intelligent Information Support for Programmers - Daye Nam (2024)

How Much Does AI Impact Development Speed? an Enterprise-Based Randomized Controlled Trial. - Elise Paradis; Kate Grey; Quinn Madison; Daye Nam; Andrew Macvean; Vahid Meimand; Nan Zhang; Benjamin Ferrari-Church; Satish Chandra 001 (SEIP@ICSE, 2025)

From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactions. - Ali Alfageeh; Sadegh AlMahdi Kazemi Zarkouei; Daye Nam; Daniel Prol; Matin Amoozadeh; Souti Chattopadhyay; James Prather; Paul Denny 001; Juho Leinonen 001; Michael Hilton; Sruti Srinivasa Ragavan; Mohammad Amin Alipour (CoRR, 2025)

Prompting LLMs for Code Editing: Struggles and Remedies. - Daye Nam; Ahmed Omran; Ambar Murillo; Saksham Thakur; Abner Araujo; Marcel Blistein; Alexander Frömmgen; Vincent J. Hellendoorn; Satish Chandra 001 (CoRR, 2025)