Many researchers have proposed programming languages that support incremental computation (IC), which allows programs to be efficiently re-executed after a small change to the input. However, existing implementations of such languages have two important drawbacks. First, recomputation is oblivious to specific demands on the program output; that is, if a program input changes, all dependencies will be recomputed, even if an observer no longer requires certain outputs. Second, programs are made incremental as a unit, with little or no support for reusing results outside of their original context, e.g., when reordered.

We present Expositor, a new debugging environment that combines scripting and time-travel debugging to allow programmers to automate complex debugging tasks. The fundamental abstraction provided by Expositor is the execution trace, which is a time-indexed sequence of program state snapshots. Programmers can manipulate traces as if they were simple lists with operations such as map and filter. Under the hood, Expositor efficiently implements traces as lazy, sparse interval trees whose contents are materialized on demand. Expositor also provides a novel data structure, the edit hash array mapped trie, which is a lazy implementation of sets, maps, multisets, and multimaps that enables programmers to maximize the efficiency of their debugging scripts. We have used Expositor to debug a stack overflow and to unravel a subtle data race in Firefox. We believe that Expositor represents an important step forward in improving the technology for diagnosing complex, hard-to-understand bugs.

Large-scale software engineering requires communication and collaboration to successfully build and ship products. We conducted a survey with Microsoft engineers on inter-team coordination and found that the most impactful problems concerned finding and keeping track of other engineers. Since engineers are connected by their shared work, a tool that discovers connections in their work-related repositories can help.

Static analysis designers must carefully balance precision and efficiency. In our experience, many static analysis tools are built around an elegant, core algorithm, but that algorithm is then extensively tweaked to add just enough precision for the coding idioms seen in practice, without sacrificing too much efficiency. There are several downsides to adding precision in this way: the tool's implementation becomes much more complicated; it can be hard for an end-user to interpret the tool's results; and as software systems vary tremendously in their coding styles, it may require significant algorithmic engineering to enhance a tool to perform well in a particular software domain.

In this demo, we describe WhoseIsThat, a social search portal which we built using the Codebook framework. We improve the search experience in two ways: first, we search across multiple software repositories at once with a single query; second, we return not just a list of artifacts in the results, but also engineers.

JavaScript programmers make extensive use of event-driven programming to help build responsive web applications. However, standard approaches to sequencing events are messy, and often lead to code that is difficult to understand and maintain. We have found that arrows, a generalization of monads, are an elegant solution to this problem. Arrows allow us to easily write asynchronous programs in small, modular units of code, and flexibly compose them in many different ways, while nicely abstracting the details of asynchronous program composition. In this paper, we present Arrowlets, a new JavaScript library that offers arrows to the everyday JavaScript programmer. We show how to use Arrowlets to construct a variety of state machines, including state machines that branch and loop. We also demonstrate how Arrowlets separate computation from composition with examples such as a drag-and-drop handler and a bubblesort animation.

The research and industrial communities have made great strides in developing sophisticated defect detection tools based on static analysis. To date most of the work in this area has focused on developing novel static analysis algorithms, but has neglected study of other aspects of static analysis tools, particularly user interfaces. In this work, we present a novel user interface toolkit called Path Projection that helps users visualize, navigate, and understand program paths, a common component of many tools' error reports. We performed a controlled user study to measure the benefit of Path Projection in triaging error reports from Locksmith, a data race detection tool for C. We found that Path Projection improved participants' time to complete this task without affecting accuracy, while participants felt Path Projection was useful and strongly preferred it to a more standard viewer.