Snapshot diagrams, which visualize in-memory program state, are frequently used in programming education to demonstrate new concepts and help students develop a better understanding of program functionality. In this paper we introduce Snapdown, a textual language for drawing snapshot diagrams, designed for use by both students and instructors of programming courses. Snapdown is designed with an emphasis on learnability and simplicity: both to be picked up by students in a classroom setting in a matter of minutes, and to enable creation and maintenance of diagrams in instructional content with minimal overhead. We introduce several use cases of Snapdown and describe the design and features of its textual language. We also describe a deployment of Snapdown during two semesters of emergency remote teaching in 6.031 Software Construction at MIT, a software engineering course intended for sophomore- and junior-level undergraduate students.

Immediate, individualized feedback on their code helps students learning to program. However, even in short, focused exercises in active learning, teachers do not have much time to write feedback. In addition, only looking at a student's final code hides a lot of the students' learning and discovering process. We created a glanceable code history visualization that enables teachers to view a student's entire coding history quickly and efficiently. A preliminary user study shows that this visualization captures previously unseen information that allows teachers to give students better grades and give students longer feedback and better feedback that focuses not just on their final code, but all their code in between.

A common pattern among undergraduate computer science curriculums is to teach an introductory subject in Python followed by a more advanced software engineering subject in Java. We are building an online tool that will help students who already know Python learn the syntax and semantics of Java. Our system will differ from existing online tutors and tools for learning Java in two main aspects. First, our tutor will focus on the transition from Python to Java. Using this basis will allow us to gloss over basic concepts of programming which students are already familiar with and focus on the specifics of Java. Second, our tutor will crowdsource writing test cases for problems to the learners themselves. This will give students practice writing tests, and will also reduce the burden on instructors, who would otherwise need to implement test suites for every problem in the tutor.

This paper describes Collabode, a web-based Java integrated development environment designed to support close, synchronous collaboration between programmers. We examine the problem of collaborative coding in the face of program compilation errors introduced by other users which make collaboration more difficult, and describe an algorithm for error-mediated integration of program code. Concurrent editors see the text of changes made by collaborators, but the errors reported in their view are based only on their own changes. Editors may run the program at any time, using only error-free edits supplied so far, and ignoring incomplete or otherwise error-generating changes. We evaluate this algorithm and interface on recorded data from previous pilot experiments with Collabode, and via a user study with student and professional programmers. We conclude that it offers appreciable benefits over naive continuous synchronization without regard to errors and over manual version control.

Pair programming is the practice of having two programmers work together on the same code in a single development environment. The goals of pair programming are to improve communication and the sharing of knowledge within a team; to increase productivity; to improve developer process and help team members stay productive; and ultimately to strengthen the quality of the resulting software [1].

Mechanical Turk (MTurk) provides an on-demand source of human computation. This provides a tremendous opportunity to explore algorithms which incorporate human computation as a function call. However, various systems challenges make this difficult in practice, and most uses of MTurk post large numbers of independent tasks. TurKit is a toolkit for prototyping and exploring algorithmic human computation, while maintaining a straight-forward imperative programming style. We present the crash-and-rerun programming model that makes TurKit possible, along with a variety of applications for human computation algorithms. We also present case studies of TurKit used for real experiments across different fields.

When faced with the need for documentation, examples, bug fixes, error descriptions, code snippets, workarounds, templates, patterns, or advice, software developers frequently turn to their Web browser. Web resources both organized and authoritative as well as informal and community-driven are heavily used by developers. The time and attention devoted to finding (or re-finding) and navigating these sites is significant. We present Codetrail, a system that demonstrates how the developerpsilas use of Web resources can be improved by connecting the Eclipse IDE and the Firefox Web browser. Codetrail uses a communication channel and shared data model between these applications to implement a variety of integrative tools. By combining information previously available only to the IDE or the Web browser alone (such as editing history, code contents, and recent browsing), Codetrail can automate previously manual tasks and enable new interactions that exploit the marriage of data and functionality from Firefox and Eclipse. Just as the IDE will change the contents of peripheral views to focus on the particular code or task with which the developer is engaged, so, too, the web browser can be focused on the developerpsilas current context and task.