This working group is conducting a scoping review exploring how interpretivist research paradigms are articulated, applied, and represented in qualitative research in computer science education. Despite the prevalence of qualitative research in our field slowly growing, interpretivist assumptions remain inconsistently described and understood; the direction of influence between this inconsistency and enduring debates over which paradigms are endorsed in our field remains unclear.

Applying the Goal–Question–Metric (GQM) framework is quite challenging for students in software metrics courses, particularly when translating abstract goals into coherent GQM trees and conducting meaningful data analysis. This experience report describes the design, implementation, and perceived usefulness of two-stage collaborative peer-review workshops aimed at addressing these challenges. The workshops complement the existing course lectures by providing guided, collaborative, and feedback-rich learning activities. We analyzed student reflection reports from two course iterations. The results indicate that the workshops supported learning by application, improved understanding of the GQM framework, strengthened analytical skills, and promoted interactive and feedback-driven learning. We discuss how these findings align with the existing literature on collaborative learning and peer feedback in software engineering education.

Peer evaluation is widely used in team project courses in software engineering to assess individual contributions, promote accountability, and improve teamwork. Existing peer evaluation practices vary greatly in their purpose, design, and implementation, making it difficult to compare them and to establish best practices. This study systematically investigates peer evaluation in team project courses in software engineering. It introduces a taxonomy to categorize peer evaluation practices based on their purpose, participants, mechanisms, and outcomes. Using this taxonomy, we organize findings from existing literature and characterize how peer evaluation is applied across different courses. We further examine educators’ perspectives on the quality and applicability of the taxonomy. Based on the educators' feedback, we updated the taxonomy and provided a set of guidelines to support educators and researchers in designing and implementing peer evaluation interventions and reporting them in a structured and informed way.

Organizations are increasingly adopting Participatory Reuse, an InnerSource practice where consumers of the reusable assets also contribute to their development and maintenance. While existing literature has reported various challenges, solutions, and lessons learned from organizations engaging in participatory reuse, a consolidated synthesis of these findings remains lacking. This study aims to collect and analyze the challenges, solutions, and lessons learned in participatory reuse from empirical works conducted within industrial settings. We conducted a case survey of $\mathbf{3 4}$ primary studies in $\mathbf{1 5}$ case organizations that have implemented participatory reuse practices. Based on the core characteristics of software reuse, we categorized the identified challenges, solutions, and lessons learned into three themes: developing reusable assets, using reusable assets, and managing participatory reuse. We organized the identified evidence as a catalog of participatory reuse challenges, solutions, and lessons learned. This catalog is intended to support both practitioners and researchers in identifying relevant strategies to address specific participatory reuse challenges within their organizations. We also pilot tested the catalog with four industry experts, who found it valuable in identifying solutions and lessons learned from the challenges.

InnerSource is a collaborative and cost-effective approach to software development that encourages software reuse and co-creation. Many organizations have embraced InnerSource (IS) to reap these benefits by opening their projects for reuse within the organization and enabling contributions from various teams. However, it is crucial to establish a certain level of maturity in IS projects before inviting contributions. This paper introduces IS self-assessment guidelines designed to help IS teams at IKEA (Ingka Group) evaluate the maturity level of their IS projects. We developed the IS self-assessment guidelines following the design science methodology. The focus of the guidelines is to assess how ready IS teams are to receive external contributions.

GenAI is playing an increasingly important role in computing courses at all levels, offering new opportunities to support teaching and learning. However, using GenAI effectively raises important concerns regarding trust, academic integrity, and broader social and ethical dimensions. This Working Group was formed to report on the current state of the art in using GenAI in upper-level computing courses to aid educators. The working group will undertake a methodological review of published work and solicit input from the computing educational community as part of the report.

Abstract Contemporary practices such as InnerSource (adopting open source practices within an organization), continuous integration and delivery (CI/CD), and the use of microservices promote software reuse. Although the benefits of individual contemporary practices on reuse may be known, the implications of collective contemporary practices, mainly challenges and improvements to mitigate the challenges, are to a large extent unknown. In this study, we investigate the additional effort (cost factors), benefits, challenges, and potential improvements in contemporary reuse at Ericsson. We performed the study in two phases: a) the initial data collection based on a combination of data collection methods (e.g., interviews, discussions, company portals), and b) a follow-up group discussion after a year to understand the status of the challenges and improvements identified in the first phase. Our results indicate that developing reusable assets resulted in upfront cost factors, such as additional effort in ensuring compliance. Furthermore, development with reuse also resulted in cost factors, for example, additional effort in integrating and understanding reusable assets. Ericsson perceived the cost factors as an investment resulting in long-term benefits such as improved quality, productivity, customer experience, and way of working. The main challenge faced by Ericsson was the pressure on the producers of reusable assets. Our study shows how InnerSource can lead to an increase in contributions to reusable assets. Furthermore, Ericsson implemented measures like automating compliance checks that improved the maturity of reusable assets, resulting in an increase in their reuse. In summary, effective use of contemporary practices such as InnerSource and CI/CD, along with the use of microservices, can facilitate large scale reuse.

Team project courses in software engineering allow students to apply their acquired disciplinary knowledge while developing essential skills needed to work in the software industry. This paper examines the challenges and lessons learned by students in two team project courses involving industrial customers. The first course involves small teams and less complex project, whereas the second course, has larger teams and more complex projects. Using thematic analysis, we analyzed 158 reports submitted by two cohorts of students across two successive team project courses. As per our findings most challenges and lessons learned pertain to soft skills, such as teamwork, working in remote and hybrid setting, and collaboration with industrial customers. The results show that challenges and lessons learned evolve as students progress to the second team project course, for example, managing changes and addressing individual skill gaps were more pronounced in the first project course, while students reported greater coordination, communication, and contribution issues in the second team project course. The alignment between the challenges faced and the lessons learned suggests that addressing challenges in teamwork, collaborating with industrial customers, and working in hybrid or remote settings helped students develop effective strategies to mitigate these challenges. This process offers a valuable learning experience for the students, enriching their professional growth. • We analyze students’ reports from two cohorts across two team project courses. • We analyze the evolution of challenges and lessons learned across two courses. • Most challenges and lessons learned relate to soft skills. • Involving industrial customers in team project courses enhances student learning. • Multiple team project courses improve students’ learning experiences.

Software reuse costs and benefits have been investigated in several primary studies, which have been aggregated in multiple secondary studies as well. However, existing secondary studies on software reuse have not critically appraised the evidence in primary studies. Moreover, there has been relatively less focus on how software reuse costs and benefits were measured in the primary studies, and the aggregated evidence focuses more on software reuse benefits than reuse costs. This study aims to cover the gaps mentioned in the context above by synthesizing and critically appraising the evidence reported on software reuse costs and benefits from industrial cases. We used a systematic literature review (SLR) to conduct this study. The results of this SLR are based on a final set of 30 primary studies. We identified nine software reuse benefits and six software reuse costs, in which better quality and improved productivity were investigated the most. The primary studies mostly used defect-based and development time-based metrics to measure reuse benefits and costs. Regarding the reuse practices, the results show that software product lines, verbatim reuse, and systematic reuse were the top investigated ones, contributing to more reuse benefits. The quality assessment of the primary studies showed that most of them are either of low (20%) or moderate (67%) quality. Based on the number and quality of the studies, we conclude that the strength of evidence for better quality and improved productivity as reuse benefits is high. There is a need to conduct more high quality studies to investigate, not only other reuse costs and benefits, but also how relatively new reuse-related practices, such as InnerSource and microservices architecture, impact software reuse.

Several secondary studies have investigated the relationship between internal quality attributes, source code metrics and external quality attributes. Sometimes they have contradictory results. We synthesize evidence of the link between internal quality attributes, source code metrics and external quality attributes along with the efficacy of the prediction models used. We conducted a tertiary review to identify, evaluate and synthesize secondary studies. We used several characteristics of secondary studies as indicators for the strength of evidence and considered them when synthesizing the results. From 711 secondary studies, we identified 15 secondary studies that have investigated the link between source code and external quality. Our results show : (1) primarily, the focus has been on object-oriented systems, (2) maintainability and reliability are most often linked to internal quality attributes and source code metrics, with only one secondary study reporting evidence for security, (3) only a small set of complexity, coupling, and size-related source code metrics report a consistent positive link with maintainability and reliability, and (4) group method of data handling (GMDH) based prediction models have performed better than other prediction models for maintainability prediction. Based on our results, lines of code, coupling, complexity and the cohesion metrics from Chidamber & Kemerer (CK) metrics are good indicators of maintainability with consistent evidence from high and moderate-quality secondary studies. Similarly, four CK metrics related to coupling, complexity and cohesion are good indicators of reliability, while inheritance and certain cohesion metrics show no consistent evidence of links to maintainability and reliability. Further empirical studies are needed to explore the link between internal quality attributes, source code metrics and other external quality attributes, including functionality, portability, and usability. The results will help researchers and practitioners understand the body of knowledge on the subject and identify future research directions.

Background: InnerSource consists of the use of open source development techniques within the corporation. It helps improve software reuse through increased transparency and inter-team collaboration. Companies need to understand their context and specific needs before deciding to adopt any specific InnerSource practices since they cannot apply all InnerSource practices at once. Aim: This study aims to support the case company in assessing its readiness for adopting InnerSource practices to improve its internal reuse, identify and prioritize the improvement areas, and identify suitable solutions. Method: We performed a case study using a questionnaire and a workshop to check the current and desired status of adopting InnerSource practices and collect potential solutions. Results: The study participants identified that the company needs to prioritize the improvements related to the discoverability, communication channels, and ownership of the reusable assets. In addition, they identified certain InnerSource practices as solutions for the prioritized improvement areas, such as better structured repositories for storing and searching the reusable assets and standardized documentation of the reusable assets. Conclusion: The questionnaire instrument aids the case company in identifying the improvement areas related to InnerSource and reuse practices. InnerSource practices could improve the development and maintenance of reusable assets. Keywords: InnerSource, software reuse, readiness

Kubernetes is a free, open-source container orchestration system for deploying and managing Docker containers that host microservices. Kubernetes cluster logs help in determining the reason for the failure. However, as systems become more complex, identifying failure reasons manually becomes more difficult and time-consuming. This study aims to identify effective and efficient classification algorithms to automatically determine the failure reason. We compare five classification algorithms, Support Vector Machines, K-Nearest Neighbors, Random Forest, Gradient Boosting Classifier, and Multilayer Perceptron. Our results indicate that Random Forest produces good accuracy while requiring fewer computational resources than other algorithms.

There has been a lot of research on personality and its impact on software engineering practice. These studies use different psychological tests to identify personality types of software practitioners. The administration of these tests requires expertise. As the humans are involved, other ethical issues, such as consent, also become important. In this study, we evaluated a small sample of 15 studies that used a psychological test Myers-Briggs Type Indicator (MBTI) in a software engineering context with respect to different ethical issues related to informed consent, qualification of the test administrators and the use of appropriate tests. The results show that most of the studies in our sample seriously lack with respect to various ethical issues.

Context: Methodological research on systematic literature reviews (SLRs) in Software Engineering (SE) has so far focused on developing and evaluating guidelines for conducting systematic reviews. However, the support for quality assessment of completed SLRs has not received the same level of attention. Objective: To raise awareness of the need for a critical appraisal tool (CAT) for assessing the quality of SLRs in SE. To initiate a community-based effort towards the development of such a tool. Method: We reviewed the literature on the quality assessment of SLRs to identify the frequently used CATs in SE and other fields. Results: We identified that the CATs currently used is SE were borrowed from medicine, but have not kept pace with substantial advancements in the field of medicine. Conclusion: In this paper, we have argued the need for a CAT for quality appraisal of SLRs in SE. We have also identified a tool that has the potential for application in SE. Furthermore, we have presented our approach for adapting this state-of-the-art CAT for assessing SLRs in SE.

Context: Existing empirical evidence indicates that loss of alertness associated with mental fatigue is highly correlated with fluctuations in the performance of people carrying out auditory tasks. In software engineering research, mental fatigue may affect the results of study selection (an auditory task) when conducting secondary studies such as systematic literature reviews or systematic mapping studies. However, to date there is no empirical study that reports an in-depth investigation about the relationship between mental fatigue and researchers' selection decisions during study selection process.

In Agile Software Development (ASD) effort estimation plays an important role during release and iteration planning. The state of the art and practice on effort estimation in ASD have been recently identified. However, this knowledge has not yet been organized. The aim of this study is twofold: (1) To organize the knowledge on effort estimation in ASD and (2) to use this organized knowledge to support practice and the future research on effort estimation in ASD. We applied a taxonomy design method to organize the identified knowledge as a taxonomy of effort estimation in ASD. The proposed taxonomy offers a faceted classification scheme to characterize estimation activities of agile projects. Our agile estimation taxonomy consists of four dimensions: estimation context, estimation technique, effort predictors and effort estimate. Each dimension in turn has several facets. We applied the taxonomy to characterize estimation activities of 10 agile projects identified from the literature to assess whether all important estimation-related aspects are reported. The results showed that studies do not report complete information related to estimation. The taxonomy was also used to characterize the estimation activities of four agile teams from three different software companies. The practitioners involved in the investigation found the taxonomy useful in characterizing and documenting the estimation sessions.

Context: Software Engineering (SE) is an evolving discipline with new subareas being continuously developed and added. To structure and better understand the SE body of knowledge, taxonomies have been proposed in all SE knowledge areas. Objective: The objective of this paper is to characterize the state-of-the-art research on SE taxonomies. Method: A systematic mapping study was conducted, based on 270 primary studies. Results: An increasing number of SE taxonomies have been published since 2000 in a broad range of venues, including the top SE journals and conferences. The majority of taxonomies can be grouped into the following SWEBOK knowledge areas: construction (19.55%), design (19.55%), requirements (15.50%) and maintenance (11.81%). Illustration (45.76%) is the most frequently used approach for taxonomy validation. Hierarchy (53.14%) and faceted analysis (39.48%) are the most frequently used classification structures. Most taxonomies rely on qualitative procedures to classify subject matter instances, but in most cases (86.53%) these procedures are not described in sufficient detail. The majority of the taxonomies (97%) target unique subject matters and many taxonomy-papers are cited frequently. Most SE taxonomies are designed in an ad-hoc way. To address this issue, we have revised an existing method for developing taxonomies in a more systematic way. Conclusion: There is a strong interest in taxonomies in SE, but few taxonomies are extended or revised. Taxonomy design decisions regarding the used classification structures, procedures and descriptive bases are usually not well described and motivated.

Context: Agile methods are used both by both co-located and globally distributed teams. Recently separate studies have been conducted to understand how effort estimation is practiced in Agile Software Development (ASD) in co-located and distributed contexts. There is need to compare the findings of these studies. Objectives: The objective of this comparative study is to identify the similarities and differences in how effort estimation is practiced in co-located and globally distributed ASD. Method: We combined the data of the two surveys to conduct this comparative study. First survey was conducted to identify the state of the practice on effort estimation in co-located ASD, while the second one identified the same in globally distributed ASD context. Results: The main findings of this comparative study are: 1) Agile practitioners, both in co-located and distributed contexts, apply techniques that use experts' subjective assessment to estimate effort. 2) Story points are the most frequently used size metrics in both co-located and distributed agile contexts 3) Team's prior experience and skill level are leading cost drivers in both contexts. Distributed agile practitioners cited additional cost drivers related to the geographical distance between distributed teams. 4) In both co-located and distributed agile context, effort is estimated mainly at iteration and release planning levels 5) With regard to the accuracy of effort estimates, underestimation is the dominant for both co-located and distributed agile software development. Conclusions: Similar techniques and size metrics have been used to estimate effort by both co-located and distributed agile teams. The main difference is with regard to the factors that are considered as important cost drivers. Global barriers due to cultural, geographical and temporal differences are important cost and effort drivers for distributed ASD. These additional cost drivers should be considered when estimating effort of a distributed agile project to avoid gross underestimation.

Context: There are numerous studies on effort estimation in Agile Software Development (ASD) and the state of the art in this area has been recently documented in a Systematic Literature Review (SLR). However, to date there are no studies on the state of the practice in this area, focusing on similar issues to those investigated in the above-mentioned SLR. Objectives: The aim of this paper is to report on the state of the practice on effort estimation in ASD, focusing on a wide range of aspects such as the estimation techniques and effort predictors used, to name a few. Method: A survey was carried out using as instrument an on-line questionnaire answered by agile practitioners who have experience in effort estimation. Results: Data was collected from 60 agile practitioners from 16 different countries, and the main findings are: 1) Planning poker (63%), analogy (47%) and expert judgment (38%) are frequently practiced estimation techniques in ASD; 2) Story points is the most frequently (62%) employed size metric, used solo or in combination with other metrics (e.g., function points); 3) Team's expertise level and prior experience are most commonly used cost drivers; 4) 52% of the respondents believe that their effort estimates on average are under/over estimated by an error of 25% or more; 5) Most agile teams take into account implementation and testing activities during effort estimation; and 6) Estimation is mostly performed at sprint and release planning levels in ASD. Conclusions: Estimation techniques that rely on experts' subjective assessment are the ones used the most in ASD, with effort underestimation being the dominant trend. Further, the use of multiple techniques in combination and story points seem to present a positive association with estimation accuracy, and team-related cost drivers are the ones used by most agile teams. Finally, requirements and management related issues are perceived as the main reasons for inaccurate estimates.

Designing and assessing learning outcomes could be a challenging activity for any Software Engineering (SE) educator. To support the process of designing and assessing SE courses, educators have been applied the cognitive domain of Bloom's taxonomy. However, to the best of our knowledge, the evidence on the usage of Bloom's taxonomy in SE higher education has not yet been systematically aggregated or reviewed. Therefore, in this paper we report the state of the art on the usage of Bloom's taxonomy in SE education, identified by conducted a systematic mapping study. As a result of the performed systematic mapping study, 26 studies were deemed as relevant. The main findings from these studies are: i) Bloom's taxonomy has mostly been applied at undergraduate level for both design and assessment of software engineering courses; ii) software construction is the leading SE subarea in which Bloom's taxonomy has been applied. The results clearly point out the usefulness of Bloom's taxonomy in the SE education context. We intend to use the results from this systematic mapping study to develop a set of guidelines to support the usage of Bloom's taxonomy cognitive levels to design and assess SE courses.

Nowadays, software systems are a key factor in the success of many organizations as in most cases they play a central role helping them attain a competitive advantage. However, despite their importance, software systems may be quite costly to develop, so substantially decreasing companies' profits. In order to tackle this challenge, many organizations look for ways to decrease costs and increase profits by applying new software development approaches, like Global Software Development (GSD). Some aspects of the software project like communication, cooperation and coordination are more challenging in globally distributed than in collocated projects, since language, cultural and time zone differences are factors which can increase the required effort to globally perform a software project. Communication, coordination and cooperation aspects affect directly the effort estimation of a project, which is one of the critical tasks related to the management of a software development project. There are many studies related to effort estimation methods/techniques for colocated projects. However, there are evidences that the colocated approaches do not fit to GSD. So, this paper presents the results of a systematic literature review of effort estimation in the context of GSD, which aimed at help both researchers and practitioners to have a holistic view about the current state of the art regarding effort estimation in the context of GSD. The results suggest that there is room to improve the current state of the art on effort estimation in GSD.

Context: Software architecture (SA) plays pivotal role in development and maintenance of large software systems. Architectural decisions impact all subsequent phases in software development life cycle. Structure of large software systems has been in discussion since early 70s but software architecture started emerging as separate discipline since mid-90s. Objective: Researchers have been publishing empirical studies (i.e. case studies, experiments, experience reports) in SA discipline. Empirical literature has been aggregated in other disciplines of software engineering but no such effort has been made in SA. Objective of this study is to aggregate and synthesize the empirical evidence from literature of software architecture to report the trends, patterns and knowledge gaps. Method: To synthesize the empirical work in SA, we conducted a systematic literature review (SLR). This study reports the results of SLR based on 247 included primary studies. Results: Based on the percentage of 247 primary studies we identified that SA Evaluation (28%), non- functional requirements related work (22%) and SA Design (12%) are relatively mature sub areas of SA. Most of the empirical work (59%) in SA uses case study research method. Experiments (20%) and experience reports (14%) are also employed in empirical SA work. Conclusion: SA discipline is maturing as few sub areas of SA are mature and some areas are new and being developed. We have also identified few emerging trends in SA i.e. service oriented architecture, Product line architecture, Aspect oriented architecture, and model driven architecture.

Causes of requirement change - A systematic literature review

CONTEXT: Previous work suggests that half of the companies that have tried global software development (GSD) have failed to realise the anticipated outcomes, the root cause of which is often related to requirements problems. Despite the importance of this problem, little research has been carried out to improving requirements engineering process in the GSD projects. OBJECTIVE: In this paper an ongoing project is discussed which will bring together the work of researchers and software development experts to develop a framework for the requirements engineering process of global software development projects (GlobReq). Managers of GSD projects will be able to use GlobReq to plan a requirements engineering process suitable for a specific GSD project. In this paper the need for such a framework along with the proposed methodology, novelty and the preliminary results are discussed. METHODOLOGY: The basis of the GlobReq framework is Sommerville et al's framework of 66 requirements best practices as well as our empirical study with GSD organisations. INITIAL RESULTS: The initial findings from 5 organisations are interesting to observe that not all 66 RE best practices are perceived as high value practices for GSD projects.

One of the ways of improving quality of Software Engineering (SE) education is to develop mechanisms for quantitatively analyzing SE courses taught in universities. We propose a new multidimensional approach for analyzing SE courses. Two aspects are important for this analysis. One is what is covered (how much of the total SE knowledge space is covered in the course)? And second is how is it covered (how effectively SE topics and subtopics are covered in lectures)? We call the first one structural analysis and second one pedagogical analysis. Techniques and metrics for structural and pedagogical analysis of SE courses are presented in this paper together with results from implementation of the work on four SE courses.