Meetings and Mood-Related or Not? Insights from Student Software Projects

[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

How agile coaches create an agile mindset in development teams: Insights from an interview study

Since the publication of the agile manifesto in 2001, many companies implement an agile—or at least more agile—software development process. However, only including agile methods or practices in the overall process does not guarantee being agile. The mindset of the people involved in the process, including the development team, the customers, and the management, is of particular importance. As such an agile mindset cannot be enforced, the process of creating a suitable mindset needs to be handled with care. In an interview study with nine agile coaches, we analyzed which aspects they perceive being of particular importance during an agile transformation. One of these aspects is the agile mindset. We figure out how they support the creation of such a mindset. We identify 12 categories related to the process of creating an agile mindset. These categories include the collaboration between the coach and the management as well as the necessity to internalize the agile values. The main factor for succeeding with the creation of an agile mindset, however, can be hardly influenced: The success strongly depends on the personal prerequisites and attitudes of the individuals involved in the process, mainly the development team. We synthesize the results of our study into a timeline describing the process of how an agile coach can support the development team creating an agile mindset as part of the transformation towards an agile development process

When you don’t know with whom to collaborate: Towards an interactive system connecting contributors in a research project

Stakeholders are important for software projects as they help to define the requirements. However, in case of multiple stakeholders with different viewpoints, it is often difficult to find a suitable solution for almost everybody. We faced this situation in a large interdisciplinary research project with contributors from different natural sciences. The contributors have to collaborate with each other, i.e., they need to share and exchange knowledge, data, and research strategies from their disciplines. In order to support them, we develop an approach that facilitates the collaboration by enabling data exchange between research groups. However, the contributors – i.e., stakeholders – do not know with whom and how to collaborate. Therefore, it is difficult to identify stakeholders who can contribute to the requirements elicitation at the moment. In this paper, we present the first idea of our approach, as well as faced and expected challenges and open questions

Identifying the Mood of a Software Development Team by Analyzing Text-Based Communication in Chats with Machine Learning

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 Engineerin

Defining Frames to Structure Agile Development in Hybrid Settings - A Multi-Case Interview Study

Companies often combine agile and plan-based methods to so-called hybrid development approaches to benefit from the advantages of both. Recent research highlights conflicts introduced when combining agile and plan-based approaches in the different phases of the software lifecycle. For example, using both agile and plan-based methods during the requirements engineering of a project requires a decision on how many requirements should be gathered up-front and how many can be gathered during the runtime of a project. These conflicts need to be solved in order to construct a successful development approach. In order to investigate why the conflicts exist, how they are addressed in industry, and how they are related to each other, we performed a multi-case interview study with 15 practitioners. Our results reveal that the conflicts exist because companies use plan-based approaches to structure their agile development and define spaces of freedom and flexibility at the same time. From this insight and our results, we derive a theory that shows how companies structure their development stepwise by defining frames

The Potential of Using Vision Videos for CrowdRE: Video Comments as a Source of Feedback

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.© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Organizing GUI Tests from Behavior‐Driven Development as Videos to Obtain Stakeholders’ Feedback

Demonstrating software early and responding to feedback is crucial in agile development. However, it is difficult for stakeholders who are not on-site customers but end users, marketing people, or designers, etc. to give feedback in an agile development environment. Successful Graphical User Interface (GUI) test executions can be documented and then demonstrated for feedback. In our new concept, GUI tests from Behavior-Driven Development (BDD) are recorded, augmented, and demonstrated as videos. A GUI test is divided into several GUI unit tests, which are specified in Gherkin, a semi-structured natural language. For each GUI unit test, a video is generated during test execution. Test steps specified in Gherkin are traced and highlighted in the video. Stakeholders review these generated videos and provide feedback, e.g., on misunderstandings of requirements or on inconsistencies. To evaluate the impact of videos in identifying inconsistencies, we asked 22 participants to identify inconsistencies between (1) given requirements in regular sentences and (2) demonstrated behaviors from videos with Gherkin specifications or from Gherkin specifications alone. Our results show that participants tend to identify more inconsistencies from demonstrated behaviors which are not in accordance with given requirements. They tend to recognize inconsistencies more easily through videos than through Gherkin specifications alone. The types of inconsistency are three-fold: the mentioned feature can be incorrectly implemented, not implemented, or an unspecified new feature. We use a fictitious example showing how this feedback helps a product owner and her team manage requirements. We conclude that GUI test videos can help stakeholders give feedback more effectively. By obtaining early feedback, inconsistencies can be resolved, thus contributing to higher stakeholder satisfaction.Deutsche Forschungsgemeinschaft/ViViUse/289386339/E

Divide and Conquer the EmpiRE: A Community-Maintainable Knowledge Graph of Empirical Research in Requirements Engineering

[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.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works