The lead author of the paper is Kubick Lubick. The abstract of the paper follows:
An effective way to learn about software development tools is by
directly observing peers’ workflows. However, these tool knowledge transfer events happen infrequently because developers must be both colocated and available. We explore an online social screencasting system that removes the dependencies of colocation and availability while maintaining the beneficial tool knowledge transfer of peer observation. Our results from a formative study indicate these online observations happen more frequently than in-person observations, but their effects are only temporary. We conclude that while peer observation facilitates online knowledge transfer, it is not the only component — other social factors may be involved.
Developers who use version control are expected to produce systematic commit histories that show well-defined steps with logical forward progress. Existing version control tools assume that developers also write code systematically. Unfortunately, the process by which developers write source code is often evolutionary, or as-needed, rather than systematic. Our contribution is a fragment-oriented concept called Commit Bubbles that will allow developers to construct systematic commit histories that adhere to version control best practices with less cognitive effort, and in a way that integrates with their as-needed coding workflows.
In other words, Commit Bubbles aims to alleviate the “tangled commit” and “non-descriptive commit message” dilemmas that developers routinely encounter when constructing version control commit histories:
The official release of Apache Hadoop 2.6.0 does not include the required binaries (e.g., winutils.exe) necessary to run hadoop. In order to use Hadoop on Windows, it must be compiled from source. This takes a bit of effort, so I’ve provided a pre-compiled, unofficial distribution below:
Self-explanation is one cognitive strategy through which developers comprehend error notifications. Self-explanation, when left solely to developers, can result in a significant loss of productivity because humans are imperfect and bounded in their cognitive abilities. We argue that modern IDEs offer limited visual affordances for aiding developers with self-explanation, because compilers do not reveal their reasoning about the causes of errors to the developer.
The contribution of our paper is a foundational set of visual annotations that aid developers in better comprehending error messages when compilers expose their internal reasoning. We demonstrate through a user study of 28 undergraduate Software Engineering students that our annotations align with the way in which developers self-explain error notifications. We show that these annotations allow developers to give significantly better self-explanations when compared against today’s dominant visualization paradigm, and that better self-explanations yield better mental models of notifications.
The results of our work suggest that the diagrammatic techniques developers use to explain problems can serve as an effective foundation for how IDEs should visually communicate to developers.
Error notifications, as presented by modern integrated development environments, are cryptic and confusing to developers. My dissertation research will demonstrate that modifying production compilers to expose detailed semantics about compilation errors is feasible, and that these semantics can be leveraged through diagrammatic representations using visual overlays on the source code to significantly improve compiler error notification comprehension.
I’m returning to Mountain View, California this summer to intern for Google, from June 16 to September 5. This time around, I will be working with the Knowledge: Translate team on interactive visualizations applied to the domain of machine learning.
Error notifications and their resolutions, as presented by modern IDEs, are still cryptic and confusing to developers. We propose an interaction-first approach to help developers more effectively comprehend and resolve compiler error notifications through a conceptual interaction framework. We propose novel taxonomies that can serve as controlled vocabularies for compiler notifications and their resolutions. We use preliminary taxonomies to demonstrate, through a prototype IDE, how the taxonomies make notifications and their resolutions more consistent and unified.
The paper reports on the experience of teaching an industry-validated course on Artificial Intelligence in Computer Games within the Simulation and Game Design department at a two-year community college during a 16-week semester. The course format used a blended learning just-in-time teaching approach, which included active learning programming exercises and one-on-one student interactions.