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Philip J. Guo

Philip Jia Guo

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affiliation: University of California, San Diego, Department of Cognitive Science, CA, USA
affiliation: University of Rochester, Department of Computer Science, NY, USA
affiliation: MIT, Computer Science and Artificial Intelligence Lab, Cambridge, MA, USA
affiliation: edX, Cambridge, MA, USA
affiliation: Stanford University, Department of Computer Science, CA, USA

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2020 – today

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2023
[j15]
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Philip J. Guo:
Six Opportunities for Scientists and Engineers to Learn Programming Using AI Tools Such as ChatGPT. Comput. Sci. Eng. 25(3): 73-78 (2023)
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Kendall Nakai, Philip J. Guo:
Uncovering the Hidden Curriculum of University Computing Majors via Undergraduate-Written Mentoring Guides: A Learner-Centered Design Workflow. ICER (1) 2023: 63-77
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Sam Lau, Philip J. Guo:
From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot. ICER (1) 2023: 106-121
[c74]
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Thomas D. LaToza, Esther Guerra, Philip J. Guo:
Foreword. VL/HCC 2023: xii-xiv
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Daniel Spikol, Olga Viberg, Alejandra Martínez-Monés, Philip J. Guo:
Proceedings of the Tenth ACM Conference on Learning @ Scale, Copenhagen, Denmark, July 20-22, 2023. ACM 2023 [contents]
2022
[j14]
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Georgios Sakkas, Madeline Endres, Philip J. Guo, Westley Weimer, Ranjit Jhala:
Seq2Parse: neurosymbolic parse error repair. Proc. ACM Program. Lang. 6(OOPSLA2): 1180-1206 (2022)
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Ian Drosos, Philip J. Guo:
The Design Space of Livestreaming Equipment Setups: Tradeoffs, Challenges, and Opportunities. Conference on Designing Interactive Systems 2022: 835-848
[c72]
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Sam Lau, Justin Eldridge, Shannon Ellis, Aaron Fraenkel, Marina Langlois, Suraj Rampure, Janine Tiefenbruck, Philip J. Guo:
The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses. L@S 2022: 201-211
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Kendall Nakai, Philip J. Guo:
Scaling Up Access to the Hidden Curriculum: A Design Methodology for Creating Undergraduate Mentoring Guides. L@S 2022: 413-417
[c70]
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Sam Lau, Deborah Nolan, Joseph Gonzalez, Philip J. Guo:
How Computer Science and Statistics Instructors Approach Data Science Pedagogy Differently: Three Case Studies. SIGCSE (1) 2022: 29-35
[c69]
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Sean Kross, Philip J. Guo:
Five Pedagogical Principles of a User-Centered Design Course that Prepares Computing Undergraduates for Industry Jobs. SIGCSE (1) 2022: 168-174
[c68]
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Sam Lau, Philip J. Guo:
Codehound: Helping Instructors Track Pedagogical Code Dependencies in Course Materials. SPLASH-E 2022: 1-6
2021
[j13]
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Sean Kross, Philip J. Guo:
Orienting, Framing, Bridging, Magic, and Counseling: How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 311:1-311:28 (2021)
[c67]
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Julia M. Markel, Philip J. Guo:
Inside the Mind of a CS Undergraduate TA: A Firsthand Account of Undergraduate Peer Tutoring in Computer Labs. SIGCSE 2021: 502-508
[c66]
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Philip J. Guo:
Ten Million Users and Ten Years Later: Python Tutor's Design Guidelines for Building Scalable and Sustainable Research Software in Academia. UIST 2021: 1235-1251
[c65]
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Ian Drosos, Philip J. Guo:
Streamers Teaching Programming, Art, and Gaming: Cognitive Apprenticeship, Serendipitous Teachable Moments, and Tacit Expert Knowledge. VL/HCC 2021: 1-6
[i1]
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Sean Kross, Philip J. Guo:
Orienting, Framing, Bridging, Magic, and Counseling: How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia. CoRR abs/2105.05849 (2021)
2020
[c64]
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Ian Drosos, Titus Barik, Philip J. Guo, Robert DeLine, Sumit Gulwani:
Wrex: A Unified Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists. CHI 2020: 1-12
[c63]
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Philip J. Guo, Julia M. Markel, Xiong Zhang:
Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website. L@S 2020: 301-304
[c62]
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Amy Rae Fox, Philip J. Guo, Clemens Nylandsted Klokmose, Peter Dalsgaard, Arvind Satyanarayan, Haijun Xia, James D. Hollan:
Towards a dynamic multiscale personal information space: beyond application and document centered views of information. Programming 2020: 136-143
[c61]
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Priyan Vaithilingam, Julia M. Markel, Philip J. Guo:
Papercode: Generating Paper-Based User Interfaces for Code Review, Annotation, and Teaching. UIST (Adjunct Volume) 2020: 77-79
[c60]
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Sam Lau, Ian Drosos, Julia M. Markel, Philip J. Guo:
The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry. VL/HCC 2020: 1-11

2010 – 2019

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2019
[c59]
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Sean Kross, Philip J. Guo:
Practitioners Teaching Data Science in Industry and Academia: Expectations, Workflows, and Challenges. CHI 2019: 263
[c58]
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Adam Kiezun, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst, Vijay Ganesh:
Theory and practice of string solvers (invited talk abstract). ISSTA 2019: 6-7
[c57]
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Charles H. Chen, Philip J. Guo:
Improv: Teaching Programming at Scale via Live Coding. L@S 2019: 9:1-9:10
[c56]
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Priyan Vaithilingam, Philip J. Guo:
Bespoke: Interactively Synthesizing Custom GUIs from Command-Line Applications By Demonstration. UIST 2019: 563-576
[c55]
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Xiong Zhang, Philip J. Guo:
Mallard: Turn the Web into a Contextualized Prototyping Environment for Machine Learning. UIST 2019: 605-618
[c54]
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Carrie J. Cai, Philip J. Guo:
Software Developers Learning Machine Learning: Motivations, Hurdles, and Desires. VL/HCC 2019: 25-34
[c53]
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Sean Kross, Philip J. Guo:
End-User Programmers Repurposing End-User Programming Tools to Foster Diversity in Adult End-User Programming Education. VL/HCC 2019: 65-74
2018
[c52]
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Philip J. Guo:
Non-Native English Speakers Learning Computer Programming: Barriers, Desires, and Design Opportunities. CHI 2018: 396
[c51]
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April Yi Wang, Ryan Mitts, Philip J. Guo, Parmit K. Chilana:
Mismatch of Expectations: How Modern Learning Resources Fail Conversational Programmers. CHI 2018: 511
[c50]
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Sean Kross, Philip J. Guo:
Students, systems, and interactions: synthesizing the first four years of learning@scale and charting the future. L@S 2018: 2:1-2:10
[c49]
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Kandarp Khandwala, Philip J. Guo:
Codemotion: expanding the design space of learner interactions with computer programming tutorial videos. L@S 2018: 57:1-57:10
[c48]
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Alok Mysore, Philip J. Guo:
Porta: Profiling Software Tutorials Using Operating-System-Wide Activity Tracing. UIST 2018: 201-212
[c47]
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Xiong Zhang, Philip J. Guo:
Fusion: Opportunistic Web Prototyping with UI Mashups. UIST 2018: 951-962
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Kyle Thayer, Philip J. Guo, Katharina Reinecke:
The Impact of Culture on Learner Behavior in Visual Debuggers. VL/HCC 2018: 115-124
2017
[j12]
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Philip J. Guo:
How adults ages 60+ are learning to code. Commun. ACM 60(8): 10-11 (2017)
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Philip J. Guo:
Building tools to help students learn to program. Commun. ACM 60(12): 8-9 (2017)
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Jeremy Warner, Philip J. Guo:
CodePilot: Scaffolding End-to-End Collaborative Software Development for Novice Programmers. CHI 2017: 1136-1141
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Philip J. Guo:
Older Adults Learning Computer Programming: Motivations, Frustrations, and Design Opportunities. CHI 2017: 7070-7083
[c43]
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Jeremy Warner, Philip J. Guo:
Hack.edu: Examining How College Hackathons Are Perceived By Student Attendees and Non-Attendees. ICER 2017: 254-262
[c42]
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Xiong Zhang, Philip J. Guo:
DS.js: Turn Any Webpage into an Example-Centric Live Programming Environment for Learning Data Science. UIST 2017: 691-702
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Alok Mysore, Philip J. Guo:
Torta: Generating Mixed-Media GUI and Command-Line App Tutorials Using Operating-System-Wide Activity Tracing. UIST 2017: 703-714
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Hyeonsu B. Kang, Philip J. Guo:
Omnicode: A Novice-Oriented Live Programming Environment with Always-On Run-Time Value Visualizations. UIST 2017: 737-745
[c39]
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Ian Drosos, Philip J. Guo, Chris Parnin:
HappyFace: Identifying and predicting frustrating obstacles for learning programming at scale. VL/HCC 2017: 171-179
2016
[c38]
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Parmit K. Chilana, Rishabh Singh, Philip J. Guo:
Understanding Conversational Programmers: A Perspective from the Software Industry. CHI 2016: 1462-1472
[c37]
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Denae Ford, Justin Smith, Philip J. Guo, Chris Parnin:
Paradise unplugged: identifying barriers for female participation on stack overflow. SIGSOFT FSE 2016: 846-857
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Philip J. Guo:
Parse that data! Practical tips for preparing your raw data for analysis. Perspectives on Data Science for Software Engineering 2016: 169-173
2015
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Elena L. Glassman, Jeremy Scott, Rishabh Singh, Philip J. Guo, Robert C. Miller:
OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale. ACM Trans. Comput. Hum. Interact. 22(2): 7:1-7:35 (2015)
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Carrie J. Cai, Philip J. Guo, James R. Glass, Robert C. Miller:
Wait-Learning: Leveraging Wait Time for Second Language Education. CHI 2015: 3701-3710
[c35]
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Jeremy Warner, John Doorenbos, Bradley Miller, Philip J. Guo:
How High School, College, and Online Students Differentially Engage with an Interactive Digital Textbook. EDM 2015: 528-531
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Quanzeng You, Jianbo Yuan, Jiaqi Wang, Philip J. Guo, Jiebo Luo:
Snap n' shop: Visual search-based mobile shopping made a breeze by machine and crowd intelligence. ICSC 2015: 173-180
[c33]
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Philip J. Guo:
Codeopticon: Real-Time, One-To-Many Human Tutoring for Computer Programming. UIST 2015: 599-608
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Mitchell L. Gordon, Philip J. Guo:
Codepourri: Creating visual coding tutorials using a volunteer crowd of learners. VL/HCC 2015: 13-21
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Philip J. Guo, Jeffery White, Renan Zanelatto:
Codechella: Multi-user program visualizations for real-time tutoring and collaborative learning. VL/HCC 2015: 79-87
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Joyce Zhu, Jeremy Warner, Mitchell L. Gordon, Jeffery White, Renan Zanelatto, Philip J. Guo:
Toward a domain-specific visual discussion forum for learning computer programming: An empirical study of a popular MOOC forum. VL/HCC 2015: 101-109
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Parmit K. Chilana, Celena Alcock, Shruti Dembla, Anson Ho, Ada Hurst, Brett Armstrong, Philip J. Guo:
Perceptions of non-CS majors in intro programming: The rise of the conversational programmer. VL/HCC 2015: 251-259
2014
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Philip J. Guo:
Clarifying human-computer interaction. Commun. ACM 57(2): 10-11 (2014)
[j8]
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Mark Guzdial, Philip J. Guo:
The difficulty of teaching programming languages, and the benefits of hands-on learning. Commun. ACM 57(7): 10-11 (2014)
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Philip J. Guo:
Refining students' coding and reviewing skills. Commun. ACM 57(9): 10-11 (2014)
[c28]
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Carrie J. Cai, Philip J. Guo, James R. Glass, Robert C. Miller:
Wait-learning: leveraging conversational dead time for second language education. CHI Extended Abstracts 2014: 2239-2244
[c27]
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Juho Kim, Phu Tran Nguyen, Sarah A. Weir, Philip J. Guo, Robert C. Miller, Krzysztof Z. Gajos:
Crowdsourcing step-by-step information extraction to enhance existing how-to videos. CHI 2014: 4017-4026
[c26]
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Philip J. Guo, Katharina Reinecke:
Demographic differences in how students navigate through MOOCs. L@S 2014: 21-30
[c25]
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Juho Kim, Philip J. Guo, Daniel T. Seaton, Piotr Mitros, Krzysztof Z. Gajos, Robert C. Miller:
Understanding in-video dropouts and interaction peaks inonline lecture videos. L@S 2014: 31-40
[c24]
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Philip J. Guo, Juho Kim, Rob Rubin:
How video production affects student engagement: an empirical study of MOOC videos. L@S 2014: 41-50
[c23]
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Anvisha H. Pai, Philip J. Guo, Robert C. Miller:
Modeling programming knowledge for mentoring at scale. L@S 2014: 181-182
[c22]
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Elena L. Glassman, Jeremy Scott, Rishabh Singh, Philip J. Guo, Robert C. Miller:
OverCode: visualizing variation in student solutions to programming problems at scale. UIST (Adjunct Volume) 2014: 129-130
[c21]
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Juho Kim, Philip J. Guo, Carrie J. Cai, Shang-Wen (Daniel) Li, Krzysztof Z. Gajos, Robert C. Miller:
Data-driven interaction techniques for improving navigation of educational videos. UIST 2014: 563-572
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Jeremy Scott, Philip J. Guo, Randall Davis:
A direct manipulation language for explaining algorithms. VL/HCC 2014: 45-48
2013
[j6]
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Philip J. Guo:
Teaching programming the way it works outside the classroom. Commun. ACM 56(8): 10-11 (2013)
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Philip J. Guo:
Helping scientists, engineers to work up to 100 times faster. Commun. ACM 56(10): 12-13 (2013)
[c19]
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Philip J. Guo:
Online python tutor: embeddable web-based program visualization for cs education. SIGCSE 2013: 579-584
2012
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Philip J. Guo:
Software tools to facilitate research programming. Stanford University, USA, 2012
[j4]
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Philip J. Guo:
CDE: A Tool for Creating Portable Experimental Software Packages. Comput. Sci. Eng. 14(4): 32-35 (2012)
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Adam Kiezun, Vijay Ganesh, Shay Artzi, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst:
HAMPI: A solver for word equations over strings, regular expressions, and context-free grammars. ACM Trans. Softw. Eng. Methodol. 21(4): 25:1-25:28 (2012)
[c18]
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Thomas Zimmermann, Nachiappan Nagappan, Philip J. Guo, Brendan Murphy:
Characterizing and predicting which bugs get reopened. ICSE 2012: 1074-1083
[c17]
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Philip J. Guo, Margo I. Seltzer:
BURRITO: Wrapping Your Lab Notebook in Computational Infrastructure. TaPP 2012
2011
[c16]
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Vijay Ganesh, Adam Kiezun, Shay Artzi, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst:
HAMPI: A String Solver for Testing, Analysis and Vulnerability Detection. CAV 2011: 1-19
[c15]
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Philip J. Guo, Thomas Zimmermann, Nachiappan Nagappan, Brendan Murphy:
"Not my bug!" and other reasons for software bug report reassignments. CSCW 2011: 395-404
[c14]
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Philip J. Guo:
Sloppy Python: using dynamic analysis to automatically add error tolerance to ad-hoc data processing scripts. WODA 2011: 35-40
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Philip J. Guo, Dawson R. Engler:
Using automatic persistent memoization to facilitate data analysis scripting. ISSTA 2011: 287-297
[c12]
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Philip J. Guo:
CDE: Run Any Linux Application On-Demand Without Installation. LISA 2011
[c11]
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Philip J. Guo, Sean Kandel, Joseph M. Hellerstein, Jeffrey Heer:
Proactive wrangling: mixed-initiative end-user programming of data transformation scripts. UIST 2011: 65-74
[c10]
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Philip J. Guo, Dawson R. Engler:
CDE: Using System Call Interposition to Automatically Create Portable Software Packages. USENIX Annual Technical Conference 2011
2010
[c9]
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Philip J. Guo, Thomas Zimmermann, Nachiappan Nagappan, Brendan Murphy:
Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows. ICSE (1) 2010: 495-504
[c8]
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Philip J. Guo, Dawson R. Engler:
Towards Practical Incremental Recomputation for Scientists: An Implementation for the Python Language. TaPP 2010

2000 – 2009

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2009
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Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, Scott R. Klemmer:
Opportunistic Programming: Writing Code to Prototype, Ideate, and Discover. IEEE Softw. 26(5): 18-24 (2009)
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Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira Dontcheva, Scott R. Klemmer:
Two studies of opportunistic programming: interleaving web foraging, learning, and writing code. CHI 2009: 1589-1598
[c6]
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Adam Kiezun, Philip J. Guo, Karthick Jayaraman, Michael D. Ernst:
Automatic creation of SQL Injection and cross-site scripting attacks. ICSE 2009: 199-209
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Adam Kiezun, Vijay Ganesh, Philip J. Guo, Pieter Hooimeijer, Michael D. Ernst:
HAMPI: a solver for string constraints. ISSTA 2009: 105-116
[c4]
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Philip J. Guo, Dawson R. Engler:
Linux Kernel Developer Responses to Static Analysis Bug Reports. USENIX Annual Technical Conference 2009
2008
[c3]
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Joel Brandt, Philip J. Guo, Joel Lewenstein, Scott R. Klemmer:
Opportunistic programming: how rapid ideation and prototyping occur in practice. WEUSE@ICSE 2008: 1-5
2007
[j1]
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Michael D. Ernst, Jeff H. Perkins, Philip J. Guo, Stephen McCamant, Carlos Pacheco, Matthew S. Tschantz, Chen Xiao:
The Daikon system for dynamic detection of likely invariants. Sci. Comput. Program. 69(1-3): 35-45 (2007)
2006
[c2]
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Brian Demsky, Michael D. Ernst, Philip J. Guo, Stephen McCamant, Jeff H. Perkins, Martin C. Rinard:
Inference and enforcement of data structure consistency specifications. ISSTA 2006: 233-244
[c1]
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Philip J. Guo, Jeff H. Perkins, Stephen McCamant, Michael D. Ernst:
Dynamic inference of abstract types. ISSTA 2006: 255-265

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