Contributions published at Human Aspects of Software Engineering (Thomas Fritz)

The workday of software developers is highly fragmented, as many developers work on multiple tasks per day and frequently switch between them, for example, to help co-workers or when being stuck. Frequent task switches introduce time overhead, as the user must always capture and restore the tasks' working context (e.g., applications, documents, folders) and mental context (e.g., task knowledge, goals, intentions). Previous work focused on supporting users in restoring their working context, for instance, by keeping track of task-related documents or web pages. However, these approaches frequently do not help users to re-establish their mental task context and operate fully automated, which can lead to restoring task-unrelated artifacts. In addition, existing approaches are generally not targeting software developers by not displaying source code related information. To overcome these shortcomings, we propose an approach that facilitates task context capturing and resumption for software developers and data scientists by allowing the user to semi-automatically create a snapshot of a task's associated working and mental context at any time. Later, when resuming a task, all information stored in a snapshot can be restored. A two-week pilot study with six participants showed that the approach fitted well into existing workflows, supported users in capturing their working and mental context, and saved them time when resuming a task. Users mainly created snapshots when having enough time, for example, at the end of the workday to reflect on the day and detach from work. Creating snapshots during instant task switches was less common, as participants did not encounter these situations frequently during the pilot study, likely because they were part-time developers. In addition, participants curated snapshots by providing thorough descriptions of their intent on how a task should be continued and frequently restored them within 24 hours.

In today's world, knowledge workers are often overwhelmed by the vast amounts of information they encounter while carrying out their tasks. As a result, it is vital to develop effective strategies for efficiently reusing previously foraged information to minimize foraging effort. One of these strategies is information curation, which is the concept of keeping, managing, and exploiting foraged information. Existing prototypes that addressed this topic have mostly specific use cases, like web resource curation or task history curation. Only a few of them allow the capturing of cross-application settings. None of these prototypes are optimized to support users in information foraging tasks. They lack extensive retrieval functionality, semantic content analysis, and structuring options for curated assets. To fill this void, we designed and developed the ScreenCurator. Our application allows users to capture cross-application screen settings and store them with extensive metadata. This combination shall enable comprehensive retrievability and reusability of curated knowledge. To provide users with a simple and pleasant experience, the ScreenCurator implements a certain degree of automation combined with an intuitive interface. Our application was evaluated in a user study where seven participants used the ScreenCurator for 10-15 working days besides their daily tasks. The gathered feedback implied that our approach improved the experience of taking and retrieving screenshots. Furthermore, two high-level use cases could be identified: long-term backups and short-term to-dos. Nevertheless, we found that the ScreenCurator needs to increase the implemented degree of automation and add further structuring options. Additionally, it would be of great value if the ScreenCurator would enable collaborative curation and knowledge sharing. Besides extending the feature set, care should be taken to maintain the simplicity and intuitiveness of the application.

Knowledge workers profit immensely from modern technologies and use them for many aspects of their work. But these technologies also come with drawbacks, as people are now more than ever expected to be available at all times via their work devices. This can lead to blurring boundaries between ones work and private life, which in turn can have negative effects on the ability to psychologically detach from work and enjoy non-work time. In this study we introduce the concept of artefact-based reflection, a method through which knowledge workers can reflect on so called work-artefacts, like tabs, files or e-mails, that they worked with throughout their day and "clean up their workplace" at the end of their workday. Based on existing research and this new concept we developed Downtime, an application which aims at helping knowledge workers in facilitating psychological detachment through artefact-based reflection. We then conducted a user study over two weeks to evaluate the effects of our application. Our findings suggest that knowledge workers can increase their detachment from work and create mental boundaries between their work and non-work lives through reflecting upon the work-artefacts they used that day, especially when they were not actively seeking detachment from their work beforehand. Further research is necessary to evaluate the long-term effects of artefact-based reflection on a broader range of knowledge workers.

Knowledge workers generally have only a limited amount of personal resources, including energy, attention and physical capacity, to achieve tasks throughout their day. When these resources are depleted, the person can feel stressed and emotionally exhausted. Knowing how and being able to recharge personal resources is, therefore, essential. As knowledge workers often spend a large part of their day at work, it can be helpful to use time spent at work to establish tiny positive habits, which help to recharge personal resources. Several studies demonstrated that regular breaks can significantly reduce stress and physical discomfort. However, while many studies focus on identifying opportune moments to suggest breaks, they rarely consider the activities that knowledge workers pursue during the break. By the definition of resource depletion, each activity can recharge or deplete resources, depending on personal preferences, making break activities crucial for achieving beneficial breaks. This thesis explores how the Break Scheduler approach may increase users' awareness on their personal resources and break habits and how it supports them in identifying beneficial break activities to improve their personal resources. This approach focuses on self-experimentation to improve awareness through self-reporting and nudging. Additionally, a rule-based system suggests a break schedule which is personalized by the user and will be adjusted by the Break Scheduler over the use period based on the user's self-reports. The investigation included 13 participants who used the software over one to two weeks. A total of 154 breaks were reported, as well as 143 daily reports. Each participant also answered a pre- and post-intervention questionnaire, giving valuable insights into their demographics, previous break habits, and their experience with the Break Scheduler. Overall, the findings suggest that self-reporting and nudging, such as scheduling the breaks in advance and notifications, can improve the awareness of the participant's personal resources and break habits. Additionally, the personalisation aspect of the Break Scheduler is crucial to help users to identify break activities that were successfully supporting them to recharge their personal resources. The results of this thesis offer insights into the potential of the Break Scheduler approach in supporting knowledge workers to increase their awareness on their personal resources and break habits by self-reporting and nudging and in helping them find beneficial activities to improve their personal resources.

This thesis explores the integration of habit formation techniques into a smartphone application to promote better sleep hygiene. Based on a literature review, the "Habstack" app was developed, incorporating habit-stacking, implementation intention rehearsal, and habit-tracking to support behaviour change. A two-week user study with 14 participants was conducted to test the feasibility of the approach and to evaluate the app's impact. A quantitative analysis of the usage data captured in the app and a qualitative analysis of interviews conducted at the end of the study was performed. The results suggest that the app was helpful and supported participants' in adopting the new sleep hygiene behaviours. To improve the effectiveness of the method, apps should provide a list of common existing habits, promote matching contexts for the habit-stacks, encourage placement of additional cues, and design reminders carefully to avoid users forming a dependency. These findings are discussed to complement existing design recommendations and to identify areas for future work. The findings provide preliminary evidence for the potential of habit formation techniques in promoting behaviour change in sleep hygiene but more work is needed to assess the long-term impact. The underlying approach and design recommendations provided could be applied to other domains and guide the development of future digital health interventions.

Programming Question-Answer Communities are at the forefront of modern Developer Work. While existing research has historically focused on finding duplicate posts in Stack Overflow, there is currently little to no research for near-duplicate detection which focuses on Platforms like Discord. To address this gap, we consider existing state-of-the-art approaches in the field and additionally replicate and apply the most promising to the new domain. A Discord-Stackoverflow dataset in the Java domain is constructed and utilized, while for the evaluation both a classification and retrieval task are considered. The experimental results show that a direct transfer from an existing domain and model is feasible to an extent, while classification and retrieval in the new domain reach up to 77% Precision, 70% F1-Score, and 80% Recall-Rate depending on the length of the examined Input Sequence.

Given a task description, a developer’s job is to alter the software system in a way that accomplishes the task, usually by fixing a bug or adding a new feature. Completing these tasks typically requires developers to use multiple tools, spanning multiple applications, within their environment. In this paper, we investigate how existing desktop environments align with and facilitate developers’ needs as they tackle their tasks. We examine how developers use their tools to perform their tasks and the ways in which these tools inhibit development velocity. Through a controlled user study with 17 subjects and a field study with 10 industrial engineers, we found that developers frequently formulate specific objectives, or goals, on-demand as they encounter new information when progressing through their tasks. These goals are often not achievable directly in the environment, forcing developers to translate their task into goals and their goals into the low-level actions provided by the environment. When carrying out these low-level actions, developers routinely perform extra work such as locating and integrating resources and adapting their needs to align with the capabilities of the environment. This extra work acts as a form of friction, limiting how quickly and directly developers can complete their tasks. Much of this extra work exists due to mismatches between current tools and environments and how developers actually work in practice. This work identifies seven types of development friction and provides design recommendations that future tools and environments could use to more effectively help developers complete their tasks.

A very common reason for the unhappiness of software engineers is being stuck in problem-solving. We developed a data gathering tool named Stuck Detector which uses face recognition and computer interaction trackers for users to report their stuck phases. The study with six software engineers consisted of a pre-study questionnaire, a two-week data gathering phase, and a final interview. The data of this study was used to create a definition for the term stuck and to observe some characteristics of stuck phases. A software engineer can be labelled as stuck, if she or he is working on a software engineering problem for a longer period, has tried different options, which didn't work, lacks information, or lacks knowledge, and can't make any progress towards the goal of the task. The results of the study implied that the frequency of stuck phases varies and is heavily dependent on the task. Furthermore, it was stated by the participants that a stuck phase occurs on average once a day. In the period of around 20 minutes before a stuck phase, the user input activity tends to decrease while the number of window changes and frustration had a tendency to increase. The participants stated that privacy and being monitored for productivity reasons were the biggest concerns about data gathering and stuck detecting tools.

Knowledge workers account for a sizeable and continuously growing proportion of today's workforce. In order to continue to provide work of impeccable quality, knowledge workers, like any other group of employees, must replenish their depleted resources regularly. Through this research, we examine psychological detachment from work as a means to restore cognitive resources that have been exhausted during daily work. Our high-level goal is to develop and investigate a practical solution to promote psychological detachment for knowledge workers. Based on previous research in the area of organizational psychology, we designed a "Shutdown Ritual" that facilitates the transition from work to life domains. An initial version of a desktop application, named "Shutdown Helper", accommodates the Shutdown Ritual and provides a range of features to facilitate the ritual execution. As a preliminary evaluation of this approach and tool, we conducted a user study with 7 participants from the knowledge sector (i.e., students). Our findings suggest that having a dedicated ritual for detachment at the end of the workday, as well as creating a tasklist with upcoming tasks and commitments, facilitate detachment from work. The effectiveness of the remaining steps in the Shutdown Ritual is highly dependent on individual workflows and detachment needs. Additional research is required to provide conclusive statements about the effectiveness of our approach for a more diverse set of knowledge workers.

Employees from all different fields struggle to schedule their work. Although they face this challenge, not everyone uses support tools or models to ease their struggle. This has a general effect on individuals' but also on a whole organizations' productivity. In the field of productivity,a lot of research has already been conducted to find out more about various factors such as emotions or environments which can influence productivity. We further examined one of the dimensions of emotions also called arousal or energy level. Our tool tracks the user's energy level with self-assessments once an hour and displays the information into a calendar. Furthermore, they rate each task on how demanding it will be. With this information the user can therefore schedule accordingly and try to map more demanding tasks to time slots where they are more energized. To test the tool's effectiveness, we conducted a user study. We found that our tool created self-awareness in terms of energy- and productivity behavior and it was reported to be helpful after all. However, it was not able to create a statistically significant increase in productivity. With further adaption of the tool, for instance extending its To-Do list characteristic, and improving the user study, we are convinced that the tool nevertheless has the potential to increase a person's productivity.

Automatic emotion recognition in couples may be useful for understanding mental health risks or evaluating outcomes for chronic disease management. However, emotion recognition in couples is under-researched due to difficulties in obtaining data and overcoming issues such as limited samples, noise, and imbalance. In this thesis, a novel in-the-wild dataset called DyMand is investigated for emotion recognition in couples. Furthermore, transfer learning models are developed using the public datasets VAMand K-EmoCon, and the best neural network layers for fine-tuning are demonstrated. In addition, multimodal fusion approaches (early fusion and late fusion) are investigated to utilize different modalities of physiological, acoustic, and linguistic data. Additionally, multi-modal fusion is compared across these modalities and this thesis demonstrates which modalities can improve couples emotion recognition. Furthermore, the developed transfer learning models could improve performance across all modalities by up to 12%.

Software development is a collaborative process requiring a careful balance of focused individual effort and team coordination. Though questions of individual productivity have been widely examined in past literature, less is known about the interplay between developers' perceptions of their own productivity as opposed to their team’s. In this paper, we present an analysis of 624 daily surveys and 2899 self-reports from 25 individuals across five software teams in North America and Europe, collected over the course of three months. We found that developers tend to operate in fluid team constructs, which impacts team awareness and complicates gauging team productivity. We also found that perceived individual productivity most strongly predicted perceived team productivity, even more than the amount of team interactions, unplanned work, and time spent in meetings. Future research should explore how fluid team structures impact individual and organizational productivity.

Developers work on a broad variety of tasks during their workdays and constantly switch between them. While these task switches can be beneficial, they can also incur a high cognitive burden on developers, since they have to continuously remember and rebuild task context - the artifacts and applications relevant to the task. Researchers have therefore proposed to capture task context more explicitly and use it to provide better task support, such as task switch reduction or task resumption support. Yet, these approaches generally require the developer to manually identify task switches. Automatic approaches for predicting task switches have so far been limited in their accuracy, scope, evaluation, and the time discrepancy between predicted and actual task switches. In our work, we examine the use of automatically collected computer interaction data for detecting developers' task switches as well as task types. In two field studies - a 4h observational study and a multi-day study with experience sampling - we collected data from a total of 25 professional developers. Our study results show that we are able to use temporal and semantic features from developers' computer interaction data to detect task switches and types in the field with high accuracy of 84% and 61% respectively, and within a short time window of less than 1.6 minutes on average from the actual task switch. We discuss our findings and their practical value for a wide range of applications in real work settings.

Software developers are generally interested in developing better habits to increase their workplace productivity and well-being, but have difficulties identifying concrete goals and actionable strategies to do so. In several areas of life, such as the physical activity and health domain, self-reflection has been shown to be successful at increasing people's awareness about a problematic behavior, motivating them to define a self-improvement goal, and fostering goal-achievement. We therefore designed a reflective goal-setting study to learn more about developers' goals and strategies to improve or maintain good habits at work. In our study, 52 professional software developers self-reflected about their work on a daily basis during two to three weeks, which resulted in a rich set of work habit goals and actionable strategies that developers pursue at work. We also found that purposeful, continuous self-reflection not only increases developers' awareness about productive and unproductive work habits (84.5%), but also leads to positive self-improvements that increase developer productivity and well-being (79.6%). We discuss how tools could support developers with a better trade-off between the cost and value of workplace self-reflection and increase long-term engagement.

With the world becoming more and more digital, managing multiple tasks and their artifacts at once has become a central part of knowledge work and requires cognitive energy that could be invested in the task it-self. Most Web browsers and many web extension try to provide features that can help to manage browser artifacts by allowing to save, group or mark them. However, most of these features do not manage to fully support task-based work and were no designed to help with clutter on screen. We propose an approach that allows users to temporarily mark and group artifacts with colors, gives them a quick way to interact with the groups of artifacts and tries to help them re-find artifacts they have previously visited and might be of interest. To evaluate the usefulness of this bundle of features, we conducted a study with six participants over two weeks followed by an interview. We found that Taboor was liked by our participants and encourages task-based work and thinking, however participants with already established and clear strategies struggled to integrate Taboor in their existing workflows and found Taboor to be less useful. From our participants’ feedback and usage logs collected by Taboor we formulated five design implications to further help improve future artifact management tools.

Working long hours in front of a computer can negatively affect the health of knowledge workers. In this regard, emotions can play a significant role. Emotional awareness can help people to recognize their emotions, to make sense out of them, and to (pro-)actively regulate them. For example, by switching to another, more exciting task or taking a break when being in a negative emotional state. However, recognizing and being aware of one’s own emotions can be challenging. We propose the EmotionalAwareness-Tool that tries to sense the emotional and cognitive state of a person sitting in front of a computer through a regular webcam. We aim to increase the users’ awareness by visualizing the sensed data in real-time on a glanceable, always on top display. A user study revealed that even though the sensing accuracy of the EmotionalAwareness-Tool is very limited, it helped users to be more aware of their emotional and cognitive state. Participants of the study perceived the accuracy of the tool as reasonably good, possibly because the glanceable display was biasing them.

As remote work is becoming more prevalent, the informal, spontaneous conversations regularly encountered in co-located work become less frequent because knowledge workers lack essential cues about their colleagues, such as their state of attention or current location. The lack of such social interactions can lead to feelings of isolation at work. While existing approaches focus mainly on improving team awareness to ameliorate coordination and collaboration problems caused by remote work, fewer tools focus on fostering informal, spontaneous communication to reduce the feeling of isolation. To address this gap, our approach focuses on people, their moods and current status, and opportunities for spontaneous interactions to create more social awareness. To this end, we developed AmbientTeams, an unobtrusive and informal tool that aims to reduce the perceived distance between distant colleagues. AmbientTeams seeks to achieve this goal through a mood-based micro-blogging approach that allows knowledge workers to share moods and status updates with their team and provides various ways to respond to what has been shared. In a preliminary evaluation, we tested our research prototype on a group of five knowledge workers who used the tool for one week. The results show that AmbientTeams facilitated getting to know each other by sharing moods and bringing more natural communication, which is otherwise often lost in a remote setting. In general, the encouraging results show that our novel approach of allowing knowledge workers to quickly and easily share moods with their team can benefit them by enabling and encouraging a more informal, lighthearted way of communicating.

Virtual reality enables a far more immersive experience than a visualization on a 2D screen. Moreover, the representation of data distributed over the three spatial dimensions can be perceived in a very intuitive way. The goal of this work is to illustrate the representation of segmented point clouds as well as to present possibilities for interactions with point clouds in VR. Furthermore, the process which integrates the raw data of a 3D scan into a VR application shall be automated. In particular, the immersive experience is enhanced by having the user physically located in the corresponding space from which their scanned data is viewed. The final result is achieved by training a neural network with a dataset that includes scans of office spaces. After preprocessing the data from a point cloud scan of an office, it can be segmented using the trained network. Finally, the segmented data is rendered in a game engine so that it can be viewed and interacted with in virtual reality. Thus, the segmentation can be visualized and serves as the basis for interactive elements that creates an inspiring or game-like experience.

What is a good workday for a software developer? What is a typical workday? We seek to answer these two questions to learn how to make good days typical. Concretely, answering these questions will help to optimize development processes and select tools that increase job satisfaction and productivity. Our work adds to a large body of research on how software developers spend their time. We report the results from 5971 responses of professional developers at Microsoft, who reflected about what made their workdays good and typical, and self-reported about how they spent their time on various activities at work. We developed conceptual frameworks to help define and characterize developer workdays from two new perspectives: good and typical. Our analysis confirms some findings in previous work, including the fact that developers actually spend little time on development and developers' aversion for meetings and interruptions. It also discovered new findings, such as that only 1.7% of survey responses mentioned emails as a reason for a bad workday, and that meetings and interruptions are only unproductive during development phases; during phases of planning, specification and release, they are common and constructive. One key finding is the importance of agency, developers' control over their workday and whether it goes as planned or is disrupted by external factors. We present actionable recommendations for researchers and managers to prioritize process and tool improvements that make good workdays typical. For instance, in light of our finding on the importance of agency, we recommend that, where possible, managers empower developers to choose their tools and tasks.

Modern office space design is in a constant state of change, intending to improve employee wellbeing and maximize productivity. A newer concept, the work oasis, attempts to tackle this issue of keeping employees at the peak of their productivity throughout the workweek. Work oases aim to be spaces where employees can take a few minutes of downtime to relax, do simple tasks, get their minds off work, play games, and recharge. As not all companies can offer their employees such a fringe benefit, we aim to provide a virtual alternative using virtual reality technology. To accomplish this, we developed the Holoft software, which allows users to set up their own virtual work oasis in their rooms of choice to foster a distraction-free and more relaxed work experience. A pilot study showed that users liked the virtual work oasis both during breaks and at the end of the workday and that it provided some of the same benefits as traditional work oases.