Joshua Sunshine

Assistant Professor

Office: TCS Hall 323

I am an Assistant Professor in the Institute for Software Research at Carnegie Mellon University. I have broad research interests at the intersection of programming languages and human-computer interaction. I am particularly interested in better understanding of the factors that influence the usability of reusable software components.

I am fortunate to work with amazing students. See my advising page for details.

I direct the Research Experience for Undergraduates in interdisciplinary Software Engineering (REUSE) program with Charlie Garrod and Claire Le Goues. The program provides an opportunity for a diverse cohort of undergraduates from school across the country to spend the summer working with the world’s leading computer scientists. Students conduct research in a broad range of areas, including: collaboration and teams, computational statistics, computer architecture, diagrams and visualization, data mining and analysis, embedded systems, human-computer interaction, networking, privacy, program synthesis, program repair, programming languages, security, software architecture, societal computing, software requirements, and testing.

I completed my PhD in Software Engineering from Carnegie Mellon in December 2013. My dissertation focused on the usability of software libraries with ordering constraints (API protocols). I graduated from Brandeis University in 2004 and worked for almost four years as a software engineer before starting graduate school. I’m married to Kira Sunshine, and we have three children: Akiva, Elisheva, and Tamir.

selected publications

L@S

Edgeworth: Efficient and Scalable Authoring of Visual Thinking Activities

Wode Ni, Sam Estep, Hwei-Shin Harriman, Kenneth R. Koedinger, and Joshua Sunshine

In Proc. of the ACM Conference on Learning @ Scale, 2024. 🏆 Best Paper Nominee

Abstract PDF

Visual thinking with diagrams is a crucial skill for learning and problem-solving in STEM subjects. To improve in this area, students need a variety of visual problems for deliberate practice. However, in our interviews, educators shared that they struggle to create these practice exercises because of limitations of existing tools. We introduce Edgeworth, a tool designed to help educators easily create visual problems. Edgeworth works in two main ways: firstly, it takes a single diagram from the user and systematically alters it to produce many variations, which the educator can then choose from to create multiple problems. Secondly, it automates the layout of diagrams, ensuring consistent high quality without the need for manual adjustments. To assess Edgeworth, we carried out case studies, a technical evaluation, and expert walkthrough demonstrations. We show that Edgeworth can create problems in three domains: geometry, chemistry, and discrete math. These problems were authored in just 15 lines of Edgeworth code on average. Edgeworth generated usable answer options within the first 10 diagram variations in 87% of authored problems. Finally, educators gave positive feedback on Edgeworth’s utility and the real-world applicability of its outputs.
ESEC/FSE

Nanofuzz: A usable tool for automatic test generation

Matthew Davis, Sangheon Choi, Sam Estep, Brad Myers, and Joshua Sunshine

In Proc. of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2023.

Abstract PDF

In the United States alone, software testing labor is estimated to cost $48 billion USD per year. Despite widespread test execution automation and automation in other areas of software engineering, test suites continue to be created manually by software engineers. We have built a test generation tool, called NaNofuzz, that helps users find bugs in their code by suggesting tests where the output is likely indicative of a bug, e.g., that return NaN (not-a-number) values. NaNofuzz is an interactive tool embedded in a development environment to fit into the programmer’s workflow. NaNofuzz tests a function with as little as one button press, analyses the program to determine inputs it should evaluate, executes the program on those inputs, and categorizes outputs to prioritize likely bugs. We conducted a randomized controlled trial with 28 professional software engineers using NaNofuzz as the intervention treatment and the popular manual testing tool, Jest, as the control treatment. Participants using NaNofuzz on average identified bugs more accurately (p < .05, by 30%), were more confident in their tests (p < .03, by 20%), and finished their tasks more quickly (p < .007, by 30%).
TOCHI

PLIERS: A Process That Integrates User-Centered Methods into Programming Language Design

Michael Coblenz, Gauri Kambhatla, Paulette Koronkevich, Jenna L. Wise, Celeste Barnaby, Joshua Sunshine, Jonathan Aldrich, and Brad A. Myers

ACM Transactions on Computer-Human Interaction (TOCHI), 2021.

Abstract PDF

Programming language design requires making many usability-related design decisions. However, existing HCI methods can be impractical to apply to programming languages: languages have high iteration costs, programmers require significant learning time, and user performance has high variance. To address these problems, we adapted both formative and summative HCI methods to make them more suitable for programming language design. We integrated these methods into a new process, PLIERS, for designing programming languages in a user-centered way. We assessed PLIERS by using it to design two new programming languages. Glacier extends Java to enable programmers to express immutability properties effectively and easily. Obsidian is a language for blockchains that includes verification of critical safety properties. Empirical studies showed that the PLIERS process resulted in languages that could be used effectively by many programmers and revealed additional opportunities for language improvement.
SIGGRAPH

Penrose: From Mathematical Notation to Beautiful Diagrams

Katherine Ye, Wode Ni, Max Krieger, Dor Ma’ayan, Jenna Wise, Jonathan Aldrich, Joshua Sunshine, and Keenan Crane

ACM Transaction on Graphics (SIGGRAPH), 2020.

Abstract PDF

We introduce a system called Penrose for creating mathematical diagrams. Its basic functionality is to translate abstract statements written in familiar math-like notation into one or more possible visual representations. Rather than rely on a fixed library of visualization tools, the visual representation is user-defined in a constraint-based specification language; diagrams are then generated automatically via constrained numerical optimization. The system is user-extensible to many domains of mathematics, and is fast enough for iterative design exploration. In contrast to tools that specify diagrams via direct manipulation or low-level graphics programming, Penrose enables rapid creation and exploration of diagrams that faithfully preserve the underlying mathematical meaning. We demonstrate the effectiveness and generality of the system by showing how it can be used to illustrate a diverse set of concepts from mathematics and computer graphics.