Most programs today are written not by professional software developers, but by people with expertise in other domains working towards goals for which they need computational support. For example, a teacher might write a grading spreadsheet to save time grading, or an interaction designer might use an interface builder to test some user interface design ideas. Although these end-user programmers may not have the same goals as professional developers, they do face many of the same software engineering challenges, including understanding their requirements, as well as making decisions about design, reuse, integration, testing, and debugging. This article summarizes and classifies research on these activities, defining the area of End-User Software Engineering (EUSE) and related terminology. The article then discusses empirical research about end-user software engineering activities and the technologies designed to support them. The article also addresses several crosscutting issues in the design of EUSE tools, including the roles of risk, reward, and domain complexity, and self-efficacy in the design of EUSE tools and the potential of educating users about software engineering principles.

The origin of contemporary Europeans remains contentious. We obtained a genome sequence from Kostenki 14 in European Russia dating from 38,700 to 36,200 years ago, one of the oldest fossils of anatomically modern humans from Europe. We find that Kostenki 14 shares a close ancestry with the 24,000-year-old Mal'ta boy from central Siberia, European Mesolithic hunter-gatherers, some contemporary western Siberians, and many Europeans, but not eastern Asians. Additionally, the Kostenki 14 genome shows evidence of shared ancestry with a population basal to all Eurasians that also relates to later European Neolithic farmers. We find that Kostenki 14 contains more Neandertal DNA that is contained in longer tracts than present Europeans. Our findings reveal the timing of divergence of western Eurasians and East Asians to be more than 36,200 years ago and that European genomic structure today dates back to the Upper Paleolithic and derives from a metapopulation that at times stretched from Europe to central Asia.

Present-day hunter-gatherers (HGs) live in multilevel social groups essential to sustain a population structure characterized by limited levels of within-band relatedness and inbreeding. When these wider social networks evolved among HGs is unknown. To investigate whether the contemporary HG strategy was already present in the Upper Paleolithic, we used complete genome sequences from Sunghir, a site dated to ~34,000 years before the present, containing multiple anatomically modern human individuals. We show that individuals at Sunghir derive from a population of small effective size, with limited kinship and levels of inbreeding similar to HG populations. Our findings suggest that Upper Paleolithic social organization was similar to that of living HGs, with limited relatedness within residential groups embedded in a larger mating network.

When software developers want to understand the reason for a program's behavior, they must translate their questions about the behavior into a series of questions about code, speculating about the causes in the process. The Whyline is a new kind of debugging tool that avoids such speculation by instead enabling developers to select a question about program output from a set of "why did and why didn't" questions extracted from the program's code and execution. The tool then finds one or more possible explanations for the output in question. These explanations are derived using a static and dynamic slicing, precise call graphs, reachability analyses, and new algorithms for determining potential sources of values. Evaluations of the tool on two debugging tasks showed that developers with the Whyline were three times more successful and twice as fast at debugging, compared to developers with traditional breakpoint debuggers. The tool has the potential to simplify debugging and program understanding in many software development contexts.

An environment that works the way nonprogrammers expect is more inviting and helps users become more confident and productive.Over the last six years, we have been working to create programming languages and environments that are more natural, or closer to the way people think about their tasks. Our goal is to make it possible for people to express their ideas in the same way they think about them. To achieve this, we have performed various studies about how people think about programming tasks, both when trying to create a new program and when trying to find and fix bugs in existing programs. We then use this knowledge to develop new tools for programming and debugging. Our user studies have shown the resulting systems provide significant benefits to users.

The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor-based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor-based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low-level input events in a development environment. We then automatically extract features from these low-level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non-interruptible and minimizing cases where the model incorrectly estimates that a programmer is non-interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.

A recent study conducted the first genome-wide scan for selection in Inuit from Greenland using single nucleotide polymorphism chip data. Here, we report that selection in the region with the second most extreme signal of positive selection in Greenlandic Inuit favored a deeply divergent haplotype that is closely related to the sequence in the Denisovan genome, and was likely introgressed from an archaic population. The region contains two genes, WARS2 and TBX15, and has previously been associated with adipose tissue differentiation and body-fat distribution in humans. We show that the adaptively introgressed allele has been under selection in a much larger geographic region than just Greenland. Furthermore, it is associated with changes in expression of WARS2 and TBX15 in multiple tissues including the adrenal gland and subcutaneous adipose tissue, and with regional DNA methylation changes in TBX15.

During debugging, a developer must repeatedly and manually reproduce faulty behaviors in order to inspect different facets of the program's execution. Existing tools for reproducing such behaviors prevent the use of debugging aids such as breakpoints and logging, and are not designed for interactive, random-access exploration of recorded behavior. This paper presents Timelapse, a tool for quickly recording, reproducing, and debugging interactive behaviors in web applications. Developers can use Timelapse to browse, visualize, and seek within recorded program executions while simultaneously using familiar debugging tools such as breakpoints and logging. Testers and end-users can use Timelapse to demonstrate failures in situ and share recorded behaviors with developers, improving bug report quality by obviating the need for detailed reproduction steps. Timelapse is built on Dolos, a novel record/replay infrastructure that ensures deterministic execution by capturing and reusing program inputs both from the user and from external sources such as the network. Dolos introduces negligible overhead and does not interfere with breakpoints and logging. In a small user evaluation, participants used Timelapse to accelerate existing reproduction activities, but were not significantly faster or more successful in completing the larger tasks at hand. Together, the Dolos infrastructure and Timelapse developer tool support systematic bug reporting and debugging practices.