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Authoring survey or review articles still requires significant tedious manual effort, despite many advancements in research knowledge management having the potential to improve efficiency, reproducibility, and reuse. However, these advancements bring forth an increasing number of approaches, tools, and systems, which often cover only specific stages and lack a comprehensive workflow utilizing their task-specific strengths. We propose the Streamlined Workflow Automation for Machine-actionable Systematic Literature Reviews (SWARM-SLR) to crowdsource the improvement of SLR efficiency while maintaining scientific integrity in a state-of-the-art knowledge discovery and distribution process. The workflow aims to domain-independently support researchers in collaboratively and sustainably managing the rising scholarly knowledge corpus. By synthesizing guidelines from the literature, we have composed a set of 65 requirements, spanning from planning to reporting a review. Existing tools were assessed against these requirements and synthesized into the SWARM-SLR workflow prototype, a ready-for-operation software support tool. The SWARM-SLR was evaluated via two online surveys, which largely confirmed the validity of the 65 requirements and situated 11 tools to the different life-cycle stages. The SWARM-SLR workflow was similarly evaluated and found to be supporting almost the entire span of an SLR, excelling specifically in search and retrieval, information extraction, knowledge synthesis, and distribution. Our SWARM-SLR requirements and workflow support tool streamlines the SLR support for researchers, allowing sustainable collaboration by linking individual efficiency improvements to crowdsourced knowledge management. If these efforts are continued, we expect the increasing number of tools to be manageable and usable inside fully structured, (semi-)automated literature review workflows., Comment: This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections

In the last two decades, several researchers provided snapshots of the "current" state and evolution of empirical research in requirements engineering (RE) through literature reviews. However, these literature reviews were not sustainable, as none built on or updated previous works due to the unavailability of the extracted and analyzed data. KG-EmpiRE is a Knowledge Graph (KG) of empirical research in RE based on scientific data extracted from currently 680 papers published in the IEEE International Requirements Engineering Conference (1994-2022). KG-EmpiRE is maintained in the Open Research Knowledge Graph (ORKG), making all data openly and long-term available according to the FAIR data principles. Our long-term goal is to constantly maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. Besides KG-EmpiRE, we provide its analysis with all supplementary materials in a repository. This repository contains all files with instructions for replicating and (re-)using the analysis locally or via executable environments and for repeating the research approach. Since its first release based on 199 papers (2014-2022), KG-EmpiRE and its analysis have been updated twice, currently covering over 650 papers. KG-EmpiRE and its analysis demonstrate how innovative infrastructures, such as the ORKG, can be leveraged to make data from literature reviews FAIR, openly available, and maintainable for the research community in the long term. In this way, we can enable replicable, (re-)usable, and thus sustainable literature reviews to ensure the quality, reliability, and timeliness of their research results., Comment: Accepted for publication at the 32nd IEEE International Requirements Engineering conference (RE) 2024

Engineering sciences, such as energy system research, play an important role in developing solutions to technical, environmental, economic, and social challenges of our modern society. In this context, the transformation of energy systems into climate-neutral systems is one of the key strategies for mitigating climate change. For the transformation of energy systems, engineers model, simulate and analyze scenarios and transformation pathways to initiate debates about possible transformation strategies. For these debates and research in general, all steps of the research process must be traceable to guarantee the trustworthiness of published results, avoid redundancies, and ensure their social acceptance. However, the analysis of energy systems is an interdisciplinary field as the investigations of large, complex energy systems often require the use of different software applications and large amounts of heterogeneous data. Engineers must therefore communicate, understand, and (re)use heterogeneous scientific knowledge and data. Although the importance of FAIR scientific knowledge and data in the engineering sciences and energy system research is increasing, little research has been conducted on this topic. When it comes to publishing scientific knowledge and data from publications, software, and datasets (such as models, scenarios, and simulations) openly available and transparent, energy system research lags behind other research domains. According to Schmitt et al. and Nie{\ss}e et al., engineers need technical support in the form of infrastructures, services, and terminologies to improve communication, understanding, and (re)use of scientific knowledge and data., Comment: 1. NFDI4Energy Conference

[Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its "current" state and evolution. However, these papers have never built on or updated earlier ones, resulting in overlap and redundancy. The underlying problem is the unavailability of data from earlier works. Researchers need technical infrastructures to conduct sustainable literature reviews. [Aims.] We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE (KG-EmpiRE) whose data is openly available. Our long-term goal is to continuously maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. [Method.] We conduct a literature review using the ORKG to build and publish KG-EmpiRE which we evaluate against competency questions derived from a published vision of empirical research in software (requirements) engineering for 2020 - 2025. [Results.] From 570 papers of the IEEE International Requirements Engineering Conference (2000 - 2022), we extract and analyze data on the reported empirical research and answer 16 out of 77 competency questions. These answers show a positive development towards the vision, but also the need for future improvements. [Conclusions.] The ORKG is a ready-to-use and advanced infrastructure to organize data from literature reviews as knowledge graphs. The resulting knowledge graphs make the data openly available and maintainable by research communities, enabling sustainable literature reviews., Comment: Accepted for publication at the 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2023)

The reuse of research software is central to research efficiency and academic exchange. The application of software enables researchers with varied backgrounds to reproduce, validate, and expand upon study findings. Furthermore, the analysis of open source code aids in the comprehension, comparison, and integration of approaches. Often, however, no further use occurs because relevant software cannot be found or is incompatible with existing research processes. This results in repetitive software development, which impedes the advancement of individual researchers and entire research communities. In this article, the DataDesc ecosystem is presented, an approach to describing data models of software interfaces with detailed and machine-actionable metadata. In addition to a specialized metadata schema, an exchange format and support tools for easy collection and the automated publishing of software documentation are introduced. This approach practically increases the FAIRness, i.e., findability, accessibility, interoperability, and so the reusability of research software, as well as effectively promotes its impact on research.

Scientific knowledge graphs have been proposed as a solution to structure the content of research publications in a machine-actionable way and enable more efficient, computer-assisted workflows for many research activities. Crowd-sourcing approaches are used frequently to build and maintain such scientific knowledge graphs. To contribute to scientific knowledge graphs, researchers need simple and easy-to-use solutions to generate new knowledge graph elements and establish the practice of semantic representations in scientific communication. In this paper, we present a workflow for authors of scientific documents to specify their contributions with a LaTeX package, called SciKGTeX, and upload them to a scientific knowledge graph. The SciKGTeX package allows authors of scientific publications to mark the main contributions of their work directly in LaTeX source files. The package embeds marked contributions as metadata into the generated PDF document, from where they can be extracted automatically and imported into a scientific knowledge graph, such as the ORKG. This workflow is simpler and faster than current approaches, which make use of external web interfaces for data entry. Our user evaluation shows that SciKGTeX is easy to use, with a score of 79 out of 100 on the System Usability Scale, as participants of the study needed only 7 minutes on average to annotate the main contributions on a sample abstract of a published paper. Further testing shows that the embedded contributions can be successfully uploaded to ORKG within ten seconds. SciKGTeX simplifies the process of manual semantic annotation of research contributions in scientific articles. Our workflow demonstrates how a scientific knowledge graph can automatically ingest research contributions from document metadata., Comment: Accepted for publication at the ACM/IEEE Joint Conference on Digital Libraries 2023 (JCDL2023)

Recent events such as wars, sanctions, pandemics, and climate change have shown the importance of proper supply network management. A key step in managing supply networks is procurement. We present an approach for realizing a next-generation procurement workspace that aims to facilitate resilience and sustainability. To achieve this, the approach encompasses a novel way of information integration, automation tools as well as analytical techniques. As a result, the procurement can be viewed from the perspective of the environmental impact, comprising and aggregating sustainability scores along the supply chain. We suggest and present an implementation of our approach, which is meanwhile used in a global Fortune 500 company. We further present the results of an empirical evaluation study, where we performed in-depth interviews with the stakeholders of the novel procurement platform to validate its adequacy, usability, and innovativeness., Comment: Accepted for publication for 25. International Conference on Enterprise Information Systems (ICEIS'23)

Knowledge Graphs (KG) have gained increasing importance in science, business and society in the last years. However, most knowledge graphs were either extracted or compiled from existing sources. There are only relatively few examples where knowledge graphs were genuinely created by an intertwined human-machine collaboration. Also, since the quality of data and knowledge graphs is of paramount importance, a number of data quality assessment models have been proposed. However, they do not take the specific aspects of intertwined human-machine curated knowledge graphs into account. In this work, we propose a graded maturity model for scholarly knowledge graphs (KGMM), which specifically focuses on aspects related to the joint, evolutionary curation of knowledge graphs for digital libraries. Our model comprises 5 maturity stages with 20 quality measures. We demonstrate the implementation of our model in a large scale scholarly knowledge graph curation effort., Comment: Accepted as a full paper at the ICADL 2022: International Conference on Asian Digital Libraries 2022

There is a strong overlap between requirements engineering (RE) and user experience (UX). Nevertheless, in practice both disciplines are often performed by separate roles and there are deficits in collaboration. In order to provide starting points for the further development of roles, activities and artifacts of the disciplines, the Requirements Engineering and User Experience Working Group (AK REUX) has been conducting a series of case studies since 2021, analyzing the UX processes of different companies from a RE perspective. We presented interim results of this investigation at the RE specialist group meeting in 2022 and compared them with the experiences of the participants., Comment: in German language, Gesellschaft f\"ur Informatik, Fachgruppentreffen Requirements Engineering 2022

Background: Teamwork, coordination, and communication are a prerequisite for the timely completion of a software project. Meetings as a facilitator for coordination and communication are an established medium for information exchange. Analyses of meetings in software projects have shown that certain interactions in these meetings, such as proactive statements followed by supportive ones, influence the mood and motivation of a team, which in turn affects its productivity. So far, however, research has focused only on certain interactions at a detailed level, requiring a complex and fine-grained analysis of a meeting itself. Aim: In this paper, we investigate meetings from a more abstract perspective, focusing on the polarity of the statements, i.e., whether they appear to be positive, negative, or neutral. Method: We analyze the relationship between the polarity of statements in meetings and different social aspects, including conflicts as well as the mood before and after a meeting. Results: Our results emerge from 21 student software project meetings and show some interesting insights: (1) Positive mood before a meeting is both related to the amount of positive statements in the beginning, as well as throughout the whole meeting, (2) negative mood before the meeting only influences the amount of negative statements in the first quarter of the meeting, but not the whole meeting, and (3) the amount of positive and negative statements during the meeting has no influence on the mood afterwards. Conclusions: We conclude that the behaviour in meetings might rather influence short-term emotional states (feelings) than long-term emotional states (mood), which are more important for the project., Comment: This is the authors' version. The final version was published in ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) (ESEM '22)

In recent decades, there has been a major shift towards improved digital access to scholarly works. However, even now that these works are available in digital form, they remain document-based, making it difficult to communicate the knowledge they contain. The next logical step is to extend these works with more flexible, fine-grained, semantic, and context-sensitive representations of scholarly knowledge. The Open Research Knowledge Graph (ORKG) is a platform that structures and interlinks scholarly knowledge, relying on crowdsourced contributions from researchers (as a crowd) to acquire, curate, publish, and process this knowledge. In this experience report, we consider the ORKG in the context of Crowd-based Requirements Engineering (CrowdRE) from two perspectives: (1) As CrowdRE researchers, we investigate how the ORKG practically applies CrowdRE techniques to involve scholars in its development to make it align better with their academic work. We determined that the ORKG readily provides social and financial incentives, feedback elicitation channels, and support for context and usage monitoring, but that there is improvement potential regarding automated user feedback analyses and a holistic CrowdRE approach. (2) As crowd members, we explore how the ORKG can be used to communicate scholarly knowledge about CrowdRE research. For this purpose, we curated qualitative and quantitative scholarly knowledge in the ORKG based on papers contained in two previously published systematic literature reviews (SLRs) on CrowdRE. This knowledge can be explored and compared interactively, and with more data than what the SLRs originally contained. Therefore, the ORKG improves access and communication of the scholarly knowledge about CrowdRE research. For both perspectives, we found the ORKG to be a useful multi-tool for CrowdRE research., Comment: Accepted for publication at 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW)

One of the most important issues in requirements engineering (RE) is the alignment of stakeholders' mental models. Making sure that all stakeholders share the same vision of a changing system is crucial to the success of any project. Misaligned mental models of stakeholders can lead to conflicting requirements. A promising approach to this problem is the use of video showing a system vision, so-called vision videos, which help stakeholders to disclose, discuss, and align their mental models of the future system. However, videos have the drawback of allowing viewers to adopt a passive role, as has been shown in research on e-learning. In this role, viewers tend to be inactive, unfocused and bored while watching a video. In this paper, we learn and adopt findings from scientific literature in the field of e-learning on how to mitigate this passive role while watching vision videos in requirements engineering. In this way, we developed concepts that incorporate interactive elements into vision videos to help viewers stay focused. These elements include questions that are asked during the video and ways for viewers to decide what happens next in the video. In a preliminary evaluation with twelve participants, we found statistically significant differences when comparing the interactive vision videos with their traditional form. Using an interactive vision videos, viewers are noticeably more engaged and gather more information on the shown system., Comment: Accepted for publication at 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW)

Vision videos are established for soliciting feedback and stimulating discussions in requirements engineering (RE) practices, such as focus groups. Different researchers motivated the transfer of these benefits into crowd-based RE (CrowdRE) by using vision videos on social media platforms. So far, however, little research explored the potential of using vision videos for CrowdRE in detail. In this paper, we analyze and assess this potential, in particular, focusing on video comments as a source of feedback. In a case study, we analyzed 4505 comments on a vision video from YouTube. We found that the video solicited 2770 comments from 2660 viewers in four days. This is more than 50% of all comments the video received in four years. Even though only a certain fraction of these comments are relevant to RE, the relevant comments address typical intentions and topics of user feedback, such as feature request or problem report. Besides the typical user feedback categories, we found more than 300 comments that address the topic safety, which has not appeared in previous analyses of user feedback. In an automated analysis, we compared the performance of three machine learning algorithms on classifying the video comments. Despite certain differences, the algorithms classified the video comments well. Based on these findings, we conclude that the use of vision videos for CrowdRE has a large potential. Despite the preliminary nature of the case study, we are optimistic that vision videos can motivate stakeholders to actively participate in a crowd and solicit numerous of video comments as a valuable source of feedback., Comment: Accepted for publication at 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW)

A wide variety of use case templates supports different variants to link a use case with its associated requirements. Regardless of the linking, a reader must process the related information simultaneously to understand them. Linking variants are intended to cause a specific reading behavior in which a reader interrelates a use case and its associated requirements. Due to the effort to create and maintain links, we investigated the impact of different linking variants on the reading behavior in terms of visual effort and the intended way of interrelating both artifacts. We designed an eye tracking study about reading a use case and requirements. We conducted the study twice each with 15 subjects as a baseline experiment and as a repetition. The results of the baseline experiment, its repetition, and their joint analysis are consistent. All investigated linking variants cause comparable visual effort. In all cases, reading the single artifacts one after the other is the most frequently occurring behavior. Only links embedded in the fields of a use case description significantly increase the readers' efforts to interrelate both artifacts. None of the investigated linking variants impedes reading a use case and requirements. However, only the most detailed linking variant causes readers to process related information simultaneously.

As software projects are very diverse, each software development process must be adjusted to the needs of the project and the corresponding development team. Frequently, we find different methods and practices combined in a so-called hybrid development method. Research has shown that these hybrid methods evolve over time and are devised based on experience. However, when devising a hybrid method, the methods and practices used should cover the whole software project with its different phases including, among others, project management, requirements analysis, quality management, risk management, and implementation. In this paper, we analyze which methods and practices are used in which phase of a software project. Based on an initial survey with 27 practitioners, we provide a mapping of methods and practices to different project phases and vice versa. Despite the preliminary nature of our study and the small sample size, we observe three remarkable aspects: (1) there are discrepancies between the intended use of methods and practices according to literature and the real use in practice, (2) practices are used more consistently than methods, and (3) parts of the software lifecycle such as maintenance and evolution are hardly covered by widely distributed methods and practices. Consequently, when devising a development process, it is worth a thought whether all phases of the software lifecycle are addressed or not., Comment: Accepted for publication at the Joint 15th International Conference on Software and System Processes (ICSSP) and 16th ACM/IEEE International Conference on Global Software Engineering (ICGSE)

Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts., Comment: 11 pages, Conference, 5 figures, 9 tables

Facilitated meetings are an established practice for the requirements engineering activities elicitation and validation. Focus groups are one well-known technique to implement this practice. Several researchers already reported the successful use of vision videos to stimulate active discussions among the participants of on-site focus groups, e.g., for validating scenarios and eliciting feedback. These vision videos show scenarios of a system vision. In this way, the videos serve all parties involved as a visual reference point to actively disclose, discuss, and align their mental models of the future system to achieve shared understanding. In the joint project TrUSD, we had planned to conduct such an on-site focus group using a vision video to validate a scenario of a future software tool, the so-called Privacy Dashboard. However, the COVID-19 pandemic and its associated measures led to an increase in home and remote working, which also affected us. Therefore, we had to replan and conduct the focus group virtually. In this paper, we report about our experiences and recommendations for the use of vision videos in virtual focus groups., Comment: Gesellschaft f\"ur Informatik, Fachgruppentreffen Requirements Engineering 2020

Software development encompasses many collaborative tasks in which usually several persons are involved. Close collaboration and the synchronization of different members of the development team require effective communication. One established communication channel are meetings which are, however, often not as effective as expected. Several approaches already focused on the analysis of meetings to determine the reasons for inefficiency and dissatisfying meeting outcomes. In addition to meetings, text-based communication channels such as chats and e-mails are frequently used in development teams. Communication via these channels requires a similar appropriate behavior as in meetings to achieve a satisfying and expedient collaboration. However, these channels have not yet been extensively examined in research. In this paper, we present an approach for analyzing interpersonal behavior in text-based communication concerning the conversational tone, the familiarity of sender and receiver, the sender's emotionality, and the appropriateness of the used language. We evaluate our approach in an industrial case study based on 1947 messages sent in a group chat in Zulip over 5.5 months. Using our approach, it was possible to automatically classify written sentences as positive, neutral, or negative with an average accuracy of 62.97% compared to human ratings. Despite this coarse-grained classification, it is possible to gain an overall picture of the adequacy of the textual communication and tendencies in the group mood., Comment: Published in the proceedings of the 8th International Conference on Human-Centered Software Engineering

Background and Motivation: In recent years, the topic of applying videos in requirements engineering has been discussed and its contributions are of interesting potential. In the last 35 years, several researchers proposed approaches for applying videos in requirements engineering due to their communication richness and effectiveness. However, these approaches mainly use videos but omit the details about how to produce them. This lack of guidance is one crucial reason why videos are not an established documentation option for successful requirements communication and thus shared understanding. Software professionals are not directors and thus they do not necessarily know what constitutes a good video in general and for an existing approach. Therefore, this lack of knowledge and skills on how to produce and use videos for visual communication impedes the application of videos by software professionals in requirements engineering. How to Create Effective Videos and Vision Videos?: This technical report addresses this lack of knowledge and skills by software professionals. We provide two guidelines that can be used as checklists to avoid frequent flaws in the production and use of videos respectively vision videos. Software professionals without special training should be able to follow these guidelines to achieve the basic capabilities to produce (vision) videos that are accepted by their stakeholders. These guidelines represent a core set of those capabilities in the preproduction, shooting, postproduction, and viewing of (vision) videos. We do not strive for perfection in any of these capabilities, .e.g., technical handling of video equipment, storytelling, or video editing. Instead, these guidelines support all steps of the (vision) video production and use process to a balanced way., Comment: Technical report, 52 pages, 63 recommendations for producing generic videos, 52 recommendations for producing vision videos

Establishing a shared software project vision is a key challenge in Requirements Engineering (RE). Several approaches use videos to represent visions. However, these approaches omit how to produce a good video. This missing guidance is one crucial reason why videos are not established in RE. We propose a quality model for videos representing a vision, so-called vision videos. Based on two literature reviews, we elaborate ten quality characteristics of videos and five quality characteristics of visions which together form a quality model for vision videos that includes all 15 quality characteristics. We provide two representations of the quality model: (a) A hierarchical decomposition of vision video quality into the quality characteristics and (b) A mapping of these characteristics to the video production and use process. While the hierarchical decomposition supports the evaluation of vision videos, the mapping provides guidance for video production. In an evaluation with 139 students, we investigated whether the 15 characteristics are related to the overall quality of vision videos perceived by the subjects from a developer's the point of view. Six characteristics (video length, focus, prior knowledge, clarity, pleasure, and stability) correlated significantly with the likelihood that the subjects perceived a vision video as good. These relationships substantiate a fundamental relevance of the proposed quality model. Therefore, we conclude that the quality model is a sound basis for future refinements and extensions., Comment: Preprint accepted for publication in Journal of Systems and Software

The adequate use of documentation for communication is one challenge in requirements engineering (RE). In recent years, several researchers addressed this challenge by using videos as a communication mechanism. All of them concluded that this way of using videos has the potential to facilitate requirements communication. Nevertheless, software professionals are not directors and thus do not necessarily know what constitutes a good video. This lack of knowledge is one crucial reason why videos are still not an established communication mechanism in RE. When videos shall be established in the RE activities, practices, and techniques, requirements engineers have to acquire the necessary knowledge to produce and use good videos on their own at moderate costs, yet sufficient quality. In our research project ViViReq (see Acknowledgment), we aspire to bridge this knowledge gap about what constitutes a good video. Whether a video is good or not depends on its quality perceived by its viewers. However, video quality is a rather ill-defined concept due to numerous unspecified technical and subjective characteristics. As part of our research plan, we develop a quality model for videos inspired by the idea of Femmer and Vogelsang to define and evaluate the quality of videos as RE artifacts. In addition to evaluating videos, this quality model can be used to identify the relevant characteristics of videos for their specific purpose which can be further used to specify requirements, their criteria for satisfaction, and corresponding measures. Therefore, software professionals may use the quality model as guidance for producing and using videos., Comment: 2 pages, Fachgruppentreffen Requirements Engineering, GI Softwaretechnik-Trends

[Context and motivation] Complex software-based systems involve several stakeholders, their activities and interactions with the system. Vision videos are used during the early phases of a project to complement textual representations. They visualize previously abstract visions of the product and its use. By creating, elaborating, and discussing vision videos, stakeholders and developers gain an improved shared understanding of how those abstract visions could translate into concrete scenarios and requirements to which individuals can relate. [Question/problem] In this paper, we investigate two aspects of refining vision videos: (1) Refining the vision by providing alternative answers to previously open issues about the system to be built. (2) A refined understanding of the camera perspective in vision videos. The impact of using a subjective (or "ego") perspective is compared to the usual third-person perspective. [Methodology] We use shopping in rural areas as a real-world application domain for refining vision videos. Both aspects of refining vision videos were investigated in an experiment with 20 participants. [Contribution] Subjects made a significant number of additional contributions when they had received not only video or text but also both - even with very short text and short video clips. Subjective video elements were rated as positive. However, there was no significant preference for either subjective or non-subjective videos in general., Comment: 15 pages, 25th International Working Conference on Requirements Engineering: Foundation for Software Quality 2019

In requirements engineering (RE), knowledge is mainly communicated via written specifications. This practice is cumbersome due to its low communication richness and effectiveness. In contrast, videos can transfer knowledge more richly and effectively. However, video is still a neglected medium in RE. We investigate if software professionals perceive video as a medium that can contribute to RE. We focus on their attitudes towards video as a medium in RE including its strengths, weaknesses, opportunities, and threats. We conducted a survey to explore these attitudes with a questionnaire. 64 out of 106 software professionals completed the survey. The respondents' overall attitude towards video is positive. 59 of them stated that video has the potential to improve RE. However, 34 respondents also mentioned threats of videos for RE. We identified the strengths, weaknesses, opportunities, and threats of videos for RE from the point of view of software professionals. Video is a medium with a neglected potential. Software professionals do not fundamentally reject videos in RE. Despite the strengths and opportunities of video, the stated weaknesses and threats impede its application. Based on our findings, we conclude that software professionals need guidance on how to produce and use videos for visual communication to take full advantage of the currently neglected potential., Comment: 8 pages, 19th International Conference on Product-Focused Software Process Improvement

Videos are one of the best documentation options for a rich and effective communication. They allow experiencing the overall context of a situation by representing concrete realizations of certain requirements. Despite 35 years of research on integrating videos in requirements engineering (RE), videos are not an established documentation option in terms of RE best practices. Several approaches use videos but omit the details about how to produce them. Software professionals lack knowledge on how to communicate visually with videos since they are not directors. Therefore, they do not necessarily have the required skills neither to produce good videos in general nor to deduce what constitutes a good video for an existing approach. The discipline of video production provides numerous generic guidelines that represent best practices on how to produce a good video with specific characteristics. We propose to analyze this existing know-how to learn what constitutes a good video for visual communication. As a plan of action, we suggest a literature study of video production guidelines. We expect to identify quality characteristics of good videos in order to derive a quality model. Software professionals may use such a quality model for videos as an orientation for planning, shooting, post-processing, and viewing a video. Thus, we want to encourage and enable software professionals to produce good videos at moderate costs, yet sufficient quality., Comment: 4 pages, IEEE International Requirements Engineering Conference Workshops (REW'18)

Multitasking has always been an inherent part of software development and is known as the primary source of interruptions due to task switching in software development teams. Developing software involves a mix of analytical and creative work, and requires a significant load on brain functions, such as working memory and decision making. Thus, task switching in the context of software development imposes a cognitive load that causes software developers to lose focus and concentration while working thereby taking a toll on productivity. To investigate the disruptiveness of task switching and interruptions in software development projects, and to understand the reasons for and perceptions of the disruptiveness of task switching we used a mixed-methods approach including a longitudinal data analysis on 4,910 recorded tasks of 17 professional software developers, and a survey of 132 software developers. We found that, compared to task-specific factors (e.g. priority, level, and temporal stage), contextual factors such as interruption type (e.g. self/external), time of day, and task type and context are a more potent determinant of task switching disruptiveness in software development tasks. Furthermore, while most survey respondents believe external interruptions are more disruptive than self-interruptions, the results of our retrospective analysis reveals otherwise. We found that self-interruptions (i.e. voluntary task switchings) are more disruptive than external interruptions and have a negative effect on the performance of the interrupted tasks. Finally, we use the results of both studies to provide a set of comparative vulnerability and interaction patterns which can be used as a mean to guide decision-making and forecasting the consequences of task switching in software development teams.

Challenges in spatial planning include adjusting settlement patterns to increasing or shrinking populations; it also includes organizing food delivery in rural and peripheral environments. Discourse typically starts with an open problem and the search for a holistic and innovative solution. Software will often be needed to implement the innovation. Spatial planning problems are characterized by large and heterogeneous groups of stakeholders, such as municipalities, companies, interest groups, citizens, women and men, young people and children. Current techniques for participation are slow, laborious and costly, and they tend to miss out on many stakeholders or interest groups. We propose a triple shift in perspective: (1) Discourse is reframed as a requirements process with the explicit goal to state software, hardware, and organizational requirements. (2) Due to the above-mentioned characteristics of spatial planning problems, we suggest using techniques of requirements engineering (RE) and CrowdRE for getting stakeholders (e.g. user groups) involved. (3) We propose video as a medium for communicating problems, solution alternatives, and arguments effectively within a mixed crowd of officials, citizens, children and elderly people. Although few spatial planning problems can be solved by software alone, this new perspective helps to focus discussions anyway. RE techniques can assist in finding common ground despite the heterogeneous group of stakeholders, e.g. citizens. Digital requirements and video are well-suited for facilitating distribution, feedback, and discourse via the internet. In this paper, we propose this new perspective as a timely opportunity for the spatial planning domain - and as an increasingly important application domain of CrowdRE., Comment: 6 pages, IEEE International Requirements Engineering Conference Workshops (REW'17)

Requirements engineering provides several practices to analyze how a user wants to interact with a future software. Mockups, prototypes, and scenarios are suitable to understand usability issues and user requirements early. Nevertheless, users are often dissatisfied with the usability of a resulting software. Apparently, previously explored information was lost or no longer accessible during the development phase. Scenarios are one effective practice to describe behavior. However, they are commonly notated in natural language which is often improper to capture and communicate interaction knowledge comprehensible to developers and users. The dynamic aspect of interaction is lost if only static descriptions are used. Digital prototyping enables the creation of interactive prototypes by adding responsive controls to hand- or digitally drawn mockups. We propose to capture the events of these controls to obtain a representation of the interaction. From this data, we generate videos, which demonstrate interaction sequences, as additional support for textual scenarios. Variants of scenarios can be created by modifying the captured event sequences and mockups. Any change is unproblematic since videos only need to be regenerated. Thus, we achieve video as a by-product of digital prototyping. This reduces the effort compared to video recording such as screencasts. A first evaluation showed that such a generated video supports a faster understanding of a textual scenario compared to static mockups., Comment: 7 pages, IEEE International Requirements Engineering Conference Workshops (REW'17)

The task board is an essential artifact in many agile development approaches. It provides a good overview of the project status. Teams often customize their task boards according to the team members' needs. They modify the structure of boards, define colored codings for different purposes, and introduce different card sizes. Although the customizations are intended to improve the task board's usability and effectiveness, they may also complicate its comprehension and use. The increased effort impedes the work of both the team and team externals. Hence, task board customization is in conflict with the agile practice of fast and easy overview for everyone. In an eye tracking study with 30 participants, we compared an original task board design with three customized ones to investigate which design shortened the required time to identify a particular story card. Our findings yield that only the customized task board design with modified structures reduces the required time. The original task board design is more beneficial than individual colored codings and changed card sizes. According to our findings, agile teams should rethink their current task board design. They may be better served by focusing on the original task board design and by applying only carefully selected adjustments. In case of customization, a task board's structure should be adjusted since this is the only beneficial kind of customization, that additionally complies more precisely with the concept of fast and easy project overview., Comment: 16 pages, 18th International Conference on Product-Focused Software Process Improvement (Profes 2017)

Classifying requirements into functional requirements (FR) and non-functional ones (NFR) is an important task in requirements engineering. However, automated classification of requirements written in natural language is not straightforward, due to the variability of natural language and the absence of a controlled vocabulary. This paper investigates how automated classification of requirements into FR and NFR can be improved and how well several machine learning approaches work in this context. We contribute an approach for preprocessing requirements that standardizes and normalizes requirements before applying classification algorithms. Further, we report on how well several existing machine learning methods perform for automated classification of NFRs into sub-categories such as usability, availability, or performance. Our study is performed on 625 requirements provided by the OpenScience tera-PROMISE repository. We found that our preprocessing improved the performance of an existing classification method. We further found significant differences in the performance of approaches such as Latent Dirichlet Allocation, Biterm Topic Modeling, or Naive Bayes for the sub-classification of NFRs., Comment: 7 pages, the 25th IEEE International Conference on Requirements Engineering (RE'17)