Background and Context. Problem decomposition is a core concern of computing education. It has also become increasingly relevant: in response to GenAI, many CS1 educators are advocating for shifting instructional emphasis away from code writing and towards decomposition and higher-level planning. Currently, there is a lack of knowledge in how novices do decomposition in large, multifunction tasks.

Tools to inspect runtime state, like print statements and debuggers, are an essential part of programming.Yet, a major limitation is that they present data at a fixed, low level of abstraction which can overload the user with irrelevant details.In contrast, human drawings of data structures use many illustrative visual abstractions to show the most useful information.We attempt to bridge the gap by surveying 80 programmer-produced diagrams to develop a mechanical approach for capturing visual abstraction, termed abstraction moves.An abstraction move selects data objects of interest, and then revisualizes, simplifies, or annotates them.We implement these moves as a diagramming language for JavaScript code, named Chisel, and show that it can effectively reproduce 78 out of the 80 surveyed diagrams.In a preliminary study with four CS educators, we evaluate its usage and discover potential contexts of use.Our approach of mechanically moving between levels of abstraction in data displays opens the doors to new tools and workflows in programming education and software development.

Documentation in codebases facilitates knowledge transfer. But tools for programming are largely text-based, and so developers resort to creating ASCII diagrams—graphical artifacts approximated with text—to show visual ideas within their code. Despite real-world use, little is known about these diagrams. We interviewed nine authors of ASCII diagrams, learning why they use ASCII and what roles the diagrams play. We also compile and analyze a corpus of 507 ASCII diagrams from four open source projects, deriving a design space with seven dimensions that classify what these diagrams show, how they show it, and ways they connect to code. These investigations reveal that ASCII diagrams are professional artifacts used across many steps in the development lifecycle, diverse in role and content, and used because they visualize ideas within the variety of programming tools in use. Our findings highlight the importance of visualization within code and lay a foundation for future programming tools that tightly couple text and graphics.

Program visualizations help to form useful mental models of how programs work, and to reason and debug code. But these visualizations exist at a fixed level of abstraction, e.g., line-by-line. In contrast, programmers switch between many levels of abstraction when inspecting program behavior. Based on results from a formative study of hand-designed program visualizations, we designed CrossCode, a web-based program visualization system for JavaScript that leverages structural cues in syntax, control flow, and data flow to aggregate and navigate program execution across multiple levels of abstraction. In an exploratory qualitative study with experts, we found that CrossCode enabled participants to maintain a strong sense of place in program execution, was conducive to explaining program behavior, and helped track changes and updates to the program state.

Virtual reality has recently been adopted for use within the domain of visual analytics because it can provide users with an endless workspace within which they can be actively engaged and use their spatial reasoning skills for data analysis. However, virtual worlds need to utilize layouts and organizational schemes that are meaningful to the user and beneficial for data analysis. This paper presents DataHop, a novel visualization system that enables users to lay out their data analysis steps in a virtual environment. With a Filter, a user can specify the modification they wish to perform on one or more input data panels (i.e., containers of points), along with where output data panels should be placed in the virtual environment. Using this simple tool, highly intricate and useful visualizations may be generated and traversed by harnessing a user's spatial abilities. An exploratory study conducted with six virtual reality users evaluated the usability, affordances, and performance of DataHop for data analysis tasks, and found that spatially mapping one's workflow can be beneficial when exploring multidimensional datasets.

We present Plane, Ray, and Point, a set of interaction techniques that utilizes shape constraints to enable quick and precise object alignment and manipulation in virtual reality. Users create the three types of shape constraints, Plane, Ray, and Point, by using symbolic gestures. The shape constraints are used like scaffoldings and limit and guide the movement of virtual objects that collide or intersect with them. The same set of gestures can be performed with the other hand, which allow users to further control the degrees of freedom for precise and constrained manipulation. The combination of shape constraints and bimanual gestures yield a rich set of interaction techniques to support object transformation. An exploratory study conducted with 3D design experts and novice users found the techniques to be useful in 3D scene design workflows and easy to learn and use.