In the early 2000s, software development was shifting from offline to online, and from command line to IDE. We discuss our 2004 paper examining the impact of this shift on developers’ program comprehension behaviors, our motivation for the work, and it's impact on the last twenty years of empirical studies and developer tool innovations. We end with a discussion of the possible unintended impacts LLMs have on program comprehension in the coming decades.

As the online dissemination of scholarly outputs gets faster and easier, altmetrics, social media based indices, have emerged alongside traditional metrics for research evaluation. In a two‐phase survey, we investigate scholars' familiarity and usage of traditional metrics and altmetrics. In this paper, we present the second phase with 448 participants. We found few traditional metrics, like the Journal Impact Factor and number of citations, are familiar to and often used by scholars for research evaluation. Among altmetrics, only views/downloads, readers, and followers are known to more than half the respondents. Unseen benefits and lack of time are hindrances to using metrics for the evaluation of research outputs. Although social media are well‐known, scholars prefer promoting their research by publishing in journals and attending conferences. We found social media usage, perceived ease of use and usefulness of altmetrics affect the usage of altmetrics. Findings suggest altmetrics have attracted attention in academia and could be considered complementary to traditional metrics. We acknowledge that due to the limited sample size, statistics and demographics in this study, findings cannot be said to be representative of the entire academic population worldwide. Future studies are needed that cover a wider range of academic disciplines around the world.

Recently, social media has become a potentially new way for scholarly journals to disseminate and evaluate research outputs. Scholarly journals have started promoting their research articles to a wide range of audiences via social media platforms. This article aims to investigate the social media presence of scholarly journals across disciplines. We extracted journals from Web of Science and searched for the social media presence of these journals on Facebook and Twitter. Relevant metrics and content relating to the journals' social media accounts were also crawled for data analysis. From our results, the social media presence of scholarly journals lies between 7.1% and 14.2% across disciplines; and it has shown a steady increase in the last decade. The popularity of scholarly journals on social media is distinct across disciplines. Further, we investigated whether social media metrics of journals can predict the Journal Impact Factor (JIF). We found that the number of followers and disciplines have significant effects on the JIF. In addition, a word co‐occurrence network analysis was also conducted to identify popular topics discussed by scholarly journals on social media platforms. Finally, we highlight challenges and issues faced in this study and discuss future research directions.

Much of software developers' time is spent understanding unfamiliar code. To better understand how developers gain this understanding and how software development environments might be involved, a study was performed in which developers were given an unfamiliar program and asked to work on two debugging tasks and three enhancement tasks for 70 minutes. The study found that developers interleaved three activities. They began by searching for relevant code both manually and using search tools; however, they based their searches on limited and misrepresentative cues in the code, environment, and executing program, often leading to failed searches. When developers found relevant code, they followed its incoming and outgoing dependencies, often returning to it and navigating its other dependencies; while doing so, however, Eclipse's navigational tools caused significant overhead. Developers collected code and other information that they believed would be necessary to edit, duplicate, or otherwise refer to later by encoding it in the interactive state of Eclipse's package explorer, file tabs, and scroll bars. However, developers lost track of relevant code as these interfaces were used for other tasks, and developers were forced to find it again. These issues caused developers to spend, on average, 35 percent of their time performing the mechanics of navigation within and between source files. These observations suggest a new model of program understanding grounded in theories of information foraging and suggest ideas for tools that help developers seek, relate, and collect information in a more effective and explicit manner.

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.

Recently, several innovative tools have found their way into mainstream use in modern development environments. However, most of these tools have focused on creating and modifying code, despite evidence that most of programmers' time is spent understanding code as part of maintenance tasks. If new tools were designed to directly support these maintenance tasks, what types would be most helpful? To find out, a study of expert Java programmers using Eclipse was performed. The study suggests that maintenance work consists of three activities: (1) forming a working set of task-relevant code fragments; (2) navigating the dependencies within this working set; and (3) repairing or creating the necessary code. The study identified several trends in these activities, as well as many opportunities for new tools that could save programmers up to 35% of the time they currently spend on maintenance tasks.

Power wheelchair joysticks have be used to control a mouse cursor on desktop computers, but they offer no integrated text entry solution, confining users to point-and-click or point-and-dwell with on-screen keyboards. On-screen keyboards reduce useful screen real-estate, exacerbating the need for frequent window management, and impose a secondary focus of attention. By contrast, we present two integrated gestural text entry methods designed for use from power wheelchairs: one for use with joysticks and the other for use with touchpads. Both techniques are adaptations of EdgeWrite, originally a stylus-based unistroke method designed for people with tremor. In a preliminary text entry study of 7 power wheelchair users, we found that EdgeWrite with a touchpad was faster than the on-screen keyboard WiViK with a joystick, and EdgeWrite with a joystick was only slightly slower. These results warranted a multi-session comparison of text entry with EdgeWrite and WiViK using joysticks and touchpads, in which we found touchpads faster than joysticks, and EdgeWrite faster than WiViK with both devices after initial learning periods.

Power wheelchair joysticks have been used to control a mouse cursor on desktop computers, but they offer no integrated text entry solution, confining users to point-and-click or point-and-dwell with on-screen keyboards. But on-screen keyboards reduce useful screen real-estate, exacerbate the need for frequent window management, and impose a second focus of attention. By contrast, we present two integrated gestural text entry methods designed for use from power wheelchairs: one for joysticks and the other for touchpads. Both techniques are adaptations of EdgeWrite, originally a stylus-based unistroke method designed for people with tremor. In a preliminary study of 7 power wheelchair users, we found that touchpad EdgeWrite was faster than joystick WiVik, and joystick EdgeWrite was only slightly slower after minimal practice. These findings reflect "walk up and use"-ability and warrant further investigation into extended use.

As programming skills increase in demand and utility, the learnability of end-user programming systems is of utmost importance. However, research on learning barriers in programming systems has primarily focused on languages, overlooking potential barriers in the environment and accompanying libraries. To address this, a study of beginning programmers learning Visual Basic.NET was performed. This identified six types of barriers: design, selection, coordination, use, understanding, and information. These barriers inspire a new metaphor of computation, which provides a more learner-centric view of programming system design.