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Many agile projects use expert judgment-based methods for estimating effort. Commonly, the judgments made during estimating project features are consensual. However, this will hardly be achieved when a conflict arises between estimators. Besides, estimate depends on the experience and skills of the estimator and could be threatened by his uncertainty to make reliable and accurate assessments. To fill these gaps, an intuitionistic fuzzy expert judgment method is proposed. The latter allows making fuzzified assessments and integrates estimators' priorities according to a set of human factors. As well, it provides consensual estimates either by the end of the estimation rounds or automatically using an iterative algorithm. On the other hand, an initial empirical study has been conducted on an agile project in which user stories have been estimated by students and experts. The first findings have revealed that the proposal is more suitable for inexperienced estimators or in the first sprints of the project where disagreement is still significant. Nevertheless, when group agreement is increased during the estimating process, the proposal maintains a null bias toward the overestimation or the underestimation of the user stories. [ABSTRACT FROM AUTHOR]

Agile software development companies considered small entities (VSE) face a new reality of remote development. However, remote communication has generated many videos because video calls are often recorded for later reference. The architectural knowledge contained in videos, derived from virtual meetings, is essential for companies facing the knowledge vaporization problem. However, only some proposals in the literature can potentially manage AK in videos. The present article proposes a solution to recover this architectural knowledge contained in videos, using an ontology as a classification scheme. We based our proposal on the concept of architectural knowledge condensation and proposed a condensation cycle from it. Finally, we validated our ontology to manage architectural knowledge following the Methontology guidelines. Implementing an ontology as a classification scheme represents a step forward to achieving the condensation of architectural knowledge in an agile development environment for VSE. [ABSTRACT FROM AUTHOR]

The design-building of IT services in data centers has been historically conducted by applying rigorous IT service design-building phases-workflows. Consequently, relevant research has been conducted upon these rigorous phases-workflows to provide theoretical foundations and practical guidance to IT service design-building architects. However, the current dynamic business-governmental environment is demanding agile approaches, and research from this perspective is still very scarce. This research, thus, aims to provide an updated review and quantitative evaluation of the main rigorous (ITIL v2011, CMMI-SVC v1.3, and ISO/IEC 20000-1:2018) and main agile (ITIL v4, VeriSM, and ISO/IEC 29110-4-3) IT service design-building phases-workflows. For this aim, we conduct a conceptual review research methodology enhanced with an analytics hierarchical process (AHP) method to assess quantitatively how well these six IT service design-building phases-workflows fit two theoretical expected rigorous and agile IT service design-building phases-workflows pro formas. We found that the ITIL v2011 and CMMI-SVC v1.3 phases-workflows fit the rigorous pro forma with a high level, and the ISO/IEC 20000-1:2018 fits a moderate level, whereas all these three ones fit a low level the agile pro forma, as it was expected. ITIL v4 and VeriSM were found to fit a high level the agile pro forma but the ISO/IEC 29110-4-3 fits a moderate level. Unexpectedly, ITIL v4 and the ISO/IEC 29110-4-3 fit a moderate and moderate levels the rigorous pro forma, but VeriSM fits a low level as it was expected. Hence, we can conclude that ITIL v4 and VeriSM provide the most agile IT service design-building phase-workflow, and CMMI-SVC v1.3 the most rigorous one. The ISO/IEC 20000-1:2018 and ISO/IEC 29110-4-3 standards are still aligned to the rigorous approach, and ITIL v4 exhibits a dual moderate rigorous and high agile profile. Hence, this research provides ITSM professionals with an updated analysis useful to guide the selection and application of the IT service design-building phase-workflow—rigorous or agile one—in data centers. This research also contributes to the IT service design-building literature with updated insights and proposes specific research avenues to advance our scientific knowledge on how to design-building IT services. [ABSTRACT FROM AUTHOR]

The systematic design, building and implementation of IT services for on-premise, cloud-based or hybrid data centers are a hard engineering and managerial process. Heavyweight IT service design workflows—from ITIL v2011, CMMI-SVC v1.3 and the ISO/IEC 20000 standard—have been used in the last decade. However, the current dynamic business requirements demand to accelerate IT service design, building and implementation. Consequently, agile workflows—from ITIL v4 and VeriSM—or lightweight ones—from ISO/IEC 29110-4-3 standard and FitSM—have been proposed. However, despite these IT service design workflows provide high valuable content, they are still reported in a coarse-grain level, and thus academics and practitioners interested in using to them must add ad-hoc roles, activities-tasks, and artifacts-templates. In this research, we address this relevant knowledge gap, and using a Design Science Research Methodology (DSRM), we elaborate and evaluate exploratory an agile IT service design workflow—called AVS_FD_MVITS—that provides fine-grain content regarding roles, activities-tasks and artifacts-templates. AVS_FD_MVITS was designed using design components taken from Scrum-XP and ITIL v4 IT service design workflows. To evaluate exploratory AVS_FD_MVITS, we applied it in a realistic case in an academic small data center. The exploratory qualitative-based evaluation suggests that AVS_FD_MVITS can be considered a valid agile IT service design workflow useful for academics and practitioners. However, confirmatory quantitative-based evaluations are asked for advancing this research stream. [ABSTRACT FROM AUTHOR]

The software industry is increasingly facing the need for continuous deployment of systems. This leads to the adoption of continuous activities, including planning, integration, and deployment (a.k.a. Continuous Software Engineering (CSE)). At the same time, systems should exhibit high-quality architectures, which are often achieved through architecture evaluation methods. However, there is little insight of how such evaluation happens in the context of CSE. To cover this gap, we investigate in this work the state of the art of continuous evaluation of software architectures in CSE, including agile processes like SCRUM. For this, we systematically examine the literature to collect and summarize evidence. Our results show a diversity of means for evaluating architectures in continuous mode to support the continuous evolution of systems. We also found how such evaluation has been incorporated within continuous development processes and agile processes like SCRUM and Crystal. We finally derive the main trends and open issues in the area, aiming to support the community to better understand and further consolidate the field of continuous evaluation of software architectures. [ABSTRACT FROM AUTHOR]

Various approaches toward the development of sustainable software systems have been proposed by the requirements engineering community over the last decade. We conducted a systematic mapping study, analyzed 55 publications, and identified 29 approaches that have been published since the year 2000. We analyzed how the approaches evolved over time and how the publications and authors are influenced by each other. Furthermore, the approaches are analyzed in terms of their supported requirements engineering activities, along with the evidence provided in the publications. Additionally, we also analyzed which sustainability definitions have been used, if an iterative application of the approaches is discussed, and if the approaches also provide a tool-support for practitioners. We noticed an increase of publications on requirements engineering approaches toward sustainability in the last years, whereas a majority discuss sustainability based on the same multi-dimensional concept. Although different case studies have been already conducted, we noticed a lack of an industrial application. Our main findings concern the need of an evaluation on how the proposed requirements engineering approaches can also be applied in agile software development processes. Additionally, we also promote the development of supporting software tools to support practitioners in adapting the proposed approaches. [ABSTRACT FROM AUTHOR]

Attention is currently being focused on DevOps, which aims to reduce software development time by means of close collaboration between the development and operations areas. However, little effort has been made to determine the role of requirements management in DevOps. The objective of this study is to help both researchers and practitioners by providing an overview of the best practices regarding requirements engineering in DevOps and identifying which areas still need to be investigated. A multivocal mapping study has, therefore, been carried out in order to study which methodologies, techniques and tools are used to support requirements management in DevOps environments. After applying the review protocol, 37 papers from formal literature and 14 references from grey literature were selected for analysis. The general conclusions obtained after analysing these papers were that, within DevOps, more attention should be paid to: (1) the reuse of requirements in order to identify systems and software artefacts that can serve as a basis for the specification of new projects; (2) the communication of requirements between the different areas of an organisation and the stakeholders of a project; (3) the traceability of requirements in order to identify the relationship with other requirements, artefacts, tasks and processes; (4) non-functional requirements in order to identify the requirements of the operations area in the early phases of a project; and finally (5) specific requirements tools that should be seamlessly integrated into the DevOps toolchain. All these issues must be considered without ignoring the agile and continuous practices of development, operations and business teams. More effort must also be made to validate new methodologies in industry so as to assess and determine their strengths and weaknesses. [ABSTRACT FROM AUTHOR]

Agile approaches being practised by multiple teams operating remotely are widely adopted for large software development efforts these days. An agile setting is typically characterized by flexibility, to accommodate changing customer demands for continuous delivery of business value. A distributed setting brings about multiple demands for stability, in terms of a push for clear specification of requirements and design, and a big picture product definition. Therefore, implementing agile distributed development (ADD) projects results in an inherent conflict that must be reconciled. This article attempts to provide nuanced clarity on the notion of conflict between flexibility and stability and its management across variants of an ADD setup. Through multiple case studies, our findings suggest that the specific mode of agile project engagement and distributed team configuration drives the response to flexibility and stability respectively. Leveraging ambidexterity as a theoretical lens, this study contributes to the literature by providing insights beyond the earlier conceptualization of flexibility-stability conflict for the ADD setting. It considers contextual elements to understand the dynamics of conflicting forces. An empirical contribution of this research is the managerial framework that should assist practice in future implementations. [ABSTRACT FROM AUTHOR]

Software Size Measurement is a critical task in Software Development Life Cycle (SDLC). It is the primary input for effort estimation models and an important measure for project control and process improvement. There exist various size measurement methods whose successes have already been proven for traditional software architectures and application domains. Being one of them, functional size measurement (FSM) attracts specific attention due to its applicability at the early phases of SDLC. Although FSM methods were successful on the data-base centric, transaction oriented stand-alone applications, in contemporary software development projects, Agile methods are highly used, and a centralized database and a relational approach are not used as before while the requirements suffer from a lack of detail. Today's software is frequently service based, highly distributed, message-driven, scalable and has unprecedented levels of availability. In the new era, event-driven architectures are appearing as one of the emerging approaches where the 'event' concept largely replaces the 'data' concept. Considering the important place of events in contemporary architectures, we focused on approaching the software size measurement problem from the event-driven perspective. This situation guided us to explore how useful event as a size measure in comparison to data-movement based methods. The findings of our study indicates that events can be promising for measurement and should be investigated further in detail to be formalized for creating a measurement model thereby providing a replicable approach. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic emphasized the need for process automation, using agile software development practices. However, when agile methods are used in scaled contexts, many software development efforts fail, mainly due to lacking requirements engineering practices. When business-oriented software needs to be developed within a scaled context, the story-card method (SCM), developed as part of a previous study, assists in structuring emerging software requirements within a taxonomy that represents enterprise operation. The SCM helps agile team members to develop a common understanding about enterprise operation when they construct the enterprise operation taxonomy. Digital participatory enterprise modeling (PEM) may increase collaboration and understanding among team members, especially when team members are geographically dispersed, when they co-model their understanding of enterprise operations. Using design science research to further evolve the existing SCM, we identified two concerns regarding the existing SCM: (1) The modeling software did not encourage active participation during modeling, and (2) Low quality of the resulting cooperation structure diagram (CSD) that is used to derive an enterprise operation taxonomy, i.e., the need to further extend the existing SCM. As main contribution of this article, we addressed previous deficiencies of the SCM, developing an extended SCM (eSCM), based on principles and guidelines that would encourage online participation during PEM, also providing a comprehensive case to demonstrate the eSCM. As a second contribution, we used survey-feedback from research participants, as well as activity tracking to evaluate whether the modeling tool encouraged active PEM. Our third contribution is to evaluate the quality of the resulting CSDs with suggestions for future improvement. [ABSTRACT FROM AUTHOR]

The main purpose of Computer-Supported Collaborative Learning (CSCL) is to improve academic performance through collaborative systems design. To increase the quantity and quality of interactions in CSCL and to reduce feelings of loneliness and burnout during online learning, learner group regulation should be supported. According to the literature, performance and learning motivation cannot be achieved if group communication and interactions are not adequately supported in collaborative learning. However, studies comparing traditional online teamwork and co-regulation guidance are rare. In this context, the purpose of this study is to determine the effects of experimental application designed using agile project management tools to support students' group regulation in collaborative teamwork in online environments on co-regulation, transactive memory, group cohesion, atmosphere, and participation in web programming education. 91 university students participated in this study, which was carried out in the web programming course. The application lasted 17 weeks. Qualitative and quantitative data were collected in the study, which was designed with the mixed method. As a result of the research, there was a significant difference between the co-regulation, group cohesion, and group participation scores of the students in group regulation guidance practices through agile learning strategies, according to the intervention groups. It was concluded that the experimental application had positive effects on the improvement of group dynamics. This study provides an example of how to develop co-regulation practices in online collaborative contexts. [ABSTRACT FROM AUTHOR]

Agility gives the ability to be highly responsive to changes and make improvements in the way the agile project is documented. The just-in-time and just barely good enough documentation may miss out on important executable specifications. Interestingly, the frequently asked 'how-to-do' questions on the popular question answering (Q&A) websites like stack overflow are strong indicators of gaps in documentation and respondent answers can complement conventional software documentation practices. Social interaction within these QA websites generates partially structured content commonly referred to as crowd knowledge that can offer a peer-reviewed re-documentation by integrating the answers of these 'how-to-do' concerns. But finding the best, value-added answer to the question which can contribute toward an enriched and curated documentation is computationally difficult. Moreover, query duplicates can cause seekers to spend more time finding these best answers. As a solution, the research proffers a novel question-answering crowd documentation model (QACDoc) which is based on a socially mediated documentation mechanics involving the dynamics of community-based web. Firstly, duplicate questions are detected using Siamese neural architecture where two identical hierarchical attention networks are used to generate vectors for similarity matching. Semantic matching is done using Manhattan distance function, and a multi-layer perceptron is trained to output the predictions. Next, all respondents of semantically matched questions are grouped to form an intent-based crowd and lastly, top k-experts are identified using representative social presence features for expert ranking. The crowd documentation is then filtered to only include answers of these identified experts. [ABSTRACT FROM AUTHOR]

Although agile software development (ASD) has been adopted in the industry, requirements approaches for ASD still neglect non-functional requirements. Privacy has become a concern due to new user demands and data protection laws. Hence, privacy needs to be properly specified, but agile requirements engineering techniques do not explicitly represent privacy requirements and, therefore, are not able to proper analyze such requirements. In this context, Privacy Criteria Method (PCM), an approach to specify privacy in requirements activities, was proposed to produce more complete and detailed privacy requirements. By considering PCM a promising approach to be used in ASD and the importance of empirical evaluation of new methods, we have as objectives: 1 evaluate the ability of PCM to support systems analysts in specifying privacy requirements when used in conjunction with some agile specification methods; and 2 show our lessons learned in conducting empirical research based on an mix-method approach defined to empirically evaluate the suitability of a requirements specification in specifying privacy requirements. Mixed-method approach is a controlled experiment as a quantitative evaluation and a feasibility study (questionnaire and task analysis based) study as a qualitative and quantitative evaluation. The requirements specifications following PCM allow to represent privacy aspects, such as user's personal data and the privacy mechanism that can be used to mitigate a privacy risk scenario. We also observed that some extra time is necessary to specify privacy requirements with PCM, but it does not imply a greater perceived effort. Specifications produced with PCM are of good quality and more privacy detailed. Additionally, we attest to the importance of conducting empirical research to evaluate new methods. PCM assists in specifying more complete and detailed in relation to traditional techniques used in ASD, which facilitates communication between the requirements analysts and developers. [ABSTRACT FROM AUTHOR]

The article discusses the use of model-based code generation and its limitations. While there have been successful industrial projects that have used code generation from abstract models, the widespread adoption of code generation from explicitly defined models has not been as successful. The article identifies several challenges, including developers' ability to think in abstract form, the limitations of existing tooling, the need for flexible adaptation of the generator, and weak tool support for defining abstraction levels in a model. The article suggests that a "smart" generator could address these challenges by generating code for various functionalities, such as data transportation, user interfaces, logging, and search functionality. However, the article acknowledges that current code generators are not yet capable of such smartness and that more work is needed in this area. [Extracted from the article]

Nowadays, Internet applications with different network resource requirements have been growing exponentially; therefore, the network equipment needs to be configured consistently based on application resource requirements. In this paper, Software Defined Network (SDN) is used to make the network more programmable, flexible and agile to develop the proposed model. Flow discrimination and optimized resource allocation are significant and challenging items in providing the required network resources for each flow. In this paper, we propose a model composed of (1) network flows' types discriminator and (2) the optimized resource allocation based on the flow classes. The applications are clustered into four groups according to the network resource requirements, and a deep network traffic discriminator is used for classification. The greedy algorithm is also used for optimized resource allocation. The proposed model is developed in Mininet with a Pox controller to prove Quality of Service (QoS) improvement paralleled with maximized utilization. The simulation results show that the proposed model has intelligent behaviour in network resource allocation based on flows' requirements compared to Spanning Tree Protocol (STP) and Dynamic and Adaptive Multipath Routing (DAMR) while maximizing the network utilization. [ABSTRACT FROM AUTHOR]

Scrum is one of many agile frameworks and is considered the most popular and widely adopted. Although Scrum presents several advantages, process and final product quality continue to be Scrum's main challenges. The quality assessment should be an essential activity in the software development process. Several authors have attempted to improve the quality of Scrum projects, changing some aspects of the framework, such as including new quality practices, a quality role, and quality processes. However, the quantification of quality is still a challenge. For that reason, the authors proposed a framework called Scrumlity, which was defined in a previous study. This framework proposes a change to Scrum, including a quality role and some artifacts to evaluate quality through a complete execution of a Sprint. In this study, the authors add a User Story Quality assessment to the framework. The User Story Quality Assessment includes over 250 analyzed User Stories. Results obtained after this experiment indicate the importance of executing a User Story Quality Assessment and that Scrum Team members are willing to accept adding this to the framework. [ABSTRACT FROM AUTHOR]

Modern software development requires agile methods to deploy and scale increasingly demanded distributed systems. Practitioners have adopted the microservices architecture to cope with the challenges posed by modern software demands. However, the adoption and deployment of this architecture also creates technical and organizational challenges, potentially slowing down the development and operation teams, which require more time and effort to implement a quality deployment process that allows them to constantly release new features to production. The adoption of a DevOps culture, along with its practices and tools, alleviates some of these new challenges. In this paper we propose a guide for the deployment of systems with a microservices architecture, considering the practices of a DevOps culture, providing practitioners with a base path to start implementing the necessary platform for this architecture. We conducted this work following the Design Science Research Methodology for Information Systems (DSRM). In this way, we identified the problem, and also defined the solution objectives through the execution of a Systematic Literature Mapping and a Gray Literature Review, having as a result the proposed guide. This work can be summarized as follows: (I) Identification of practices and technologies that support the deployment of microservices. (II) Identification of recommendations, challenges, and best practices for the deployment process. (III) Modeling of the microservices deployment process using SPEM. (IV) Integration of the knowledge in a guide to deploying microservices by adopting DevOps practices. [ABSTRACT FROM AUTHOR]

The Brazilian General Data Protection Law (LGPD) implementation has impacted activities carried out by the software development teams. Due to it, developers had to become aware of the existing techniques and tools to carry out privacy requirements elicitation. Extending our previous work, we have investigated the actions taken by organizations regarding the LGPD, specifically in software development, considering the perception of agile development teams after two years of the LGPD implementation. In addition, we also investigated the perception of an agile team regarding the practices, techniques, and tools previously cited by practitioners as potential solutions for use in this context, along with techniques already in use in the current context. We have conducted a systematic literature review (SLR) and selected 36 primary studies. Furthermore, we have conducted a survey with 53 IT practitioners and semi-structured interviews with ten practitioners. The LGPD principles are known by most agile teams and are being implemented by the organizations, although the existing tools to support privacy requirements elicitation are still underused by agile teams. Moreover, agile teams consider that software requirements and software construction are the most impacted areas of knowledge by the LGPD, and most of them use user stories in privacy requirements elicitation. Our findings reveal that agile teams and Brazilian organizations are more concerned with user data privacy issues after the LGPD became effective. However, agile teams still face challenges in privacy requirements elicitation. [ABSTRACT FROM AUTHOR]

Due to their expanded methods, agile methodologies are now the accepted standard for software development. Collaboration, addressing changing requirements with workable software, and simple design are just a few aspects of typical techniques. By employing the aforementioned approaches, these methods handle the issue of variable requirements. As a result, these methods lower the cost of changes at a later point in the software development process. Due to the unpredictability of requirements, such methodologies do not hold up well for an early estimate of size, cost, and timeframe. Agile techniques, it has been noticed, rely on expert analysis and prior project information to estimate cost, complexity, and time. Such approaches, it has been discovered, do not take into account the critical aspects affecting the project's cost, complexity, and timeframe when estimating. Based on predefined estimation methods including analogy and planning, poker becomes unexpected in the lack of historical data and professionals. As a result, there is a pressing need to develop a simple computational solution that takes into account the factors that influence the project budget, complexity, and timeframe. It also serves as a foundation for unskilled practitioners to make better estimates. The research of both traditional and agile estimation techniques with a comparability of concepts and variations is presented in this work. We looked into a few key elements that influence the estimation of an agile project with lower, moderate, and higher scalability factors. Integrating critical aspects is also recommended using the Constructive Agile Estimation Algorithm (CAEA). [ABSTRACT FROM AUTHOR]

The microservice architecture shows great potentials in business solutions by providing agile response to emerging demands, which is believed a fundamental shift in innovative software development. However, the microservices are still facing a number challenges, including monolithic applications, limited reuse, operational agility, etc. This work focuses on building microservices in the Internet of Things environment by overcoming above challenges. Specifically, a microservices priority assessment method is proposed by combing the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE), in which AHP is used to calculate the weights of the related factors, while FCE is used for comprehensive evaluation to determine the priority of microservices. The experimental results on an IoT platform demonstrate the effectiveness of the proposed solution. Moreover, it is found that the most influential factors of the microservices priority are non-resource factors, and occupy the majority of the proportion. [ABSTRACT FROM AUTHOR]

Agile development is known for efficient software development practices that enable teams to quickly develop software to cope with changing requirements. Although there is evidence that agile practices are helpful in such environments, the literature does not inform us as to whether agile practices can also be beneficial in hyper-agile environments. Such environments are characterized by an extremely fast pace of change with fluid requirements. COVID-19 vaccine distribution is one such problem that governments have had to deal with. To solve this problem, governments need to come up with robust responses by formulating teams that have the capability to provide software solutions enabling information visibility into the vaccine distribution process. Such emergent teams need to quickly understand the distribution process, oftentimes define the process itself because it might be non-existent, and build software systems to solve the problem in a matter of days. Not much is known about how systems can be developed at such a fast pace. We adopt a clinical research methodology and employ agile software development practices to develop such a mission-critical system. In the process of building the system, we learn important lessons that can be used to adapt and extend agile methodologies to be used in hyper-agile development environments. We offer these lessons as important first steps to understanding the best practices needed to develop software systems that have the capability to provide visibility into the unprecedented health challenge of distribution of life-saving COVID-19 vaccine. [ABSTRACT FROM AUTHOR]

Distributed agile software development (DASD) has gained much popularity over the past years. It relates to Agile Software Development (ASD) being executed in a distributed environment due to factors such as low development budget, emerging software application markets and the need for more expertise. DASD faces a number of challenges with respect to coordination and communication issues. Task allocation in such an environment thus becomes a challenging task. Adopting proper task allocation strategy is crucial to overcome challenges and issues in DASD. Various studies highlight the challenges being faced by DASD and have proposed solutions in the form of framework or models. Knowledge models in the form of ontologies can help to solve certain issues and challenges by providing a proper representation of data that is shareable among distributed teams. Several ontologies with respect to task allocation exist. However, ontologies incorporating factors and dependencies influencing task allocation process in DASD are limited. An ontology representing the knowledge related to task allocation and coordination is important for proper decision making in organizations. Based on an in-depth literature review and a survey conducted among professionals in industry, this paper proposes an ontology, OntoDASD, that incorporates relevant factors and dependencies to be considered in task allocation and coordination process in DASD environment. The ontology facilitates team coordination through effective communication and task allocation by defining the concepts to share knowledge and information in an appropriate way. OntoDASD has been properly evaluated and validated by professionals in the field. [ABSTRACT FROM AUTHOR]

Agile is often associated with a lack of architectural thinking causing technical debt but has the advantage of user centricity and a strong focus on value. Model-driven software engineering (MDSE) strongly performs for building a quality architecture and code, but lacks focus on user requirements and tends to consider development as a monolithic whole. The combination of Agile and MDSE has been explored, but a convincing integrated method has not been proposed yet. This paper addresses this gap by exploring the specific combination of MERODE—as an example of a proven MDSE method—with Scrum, a reference agile method offering a concrete (sprint-based) life cycle management on the basis of user stories. The method resulting of this integration is called Agile MERODE; it is driven by user stories, themselves associated with behavior-driven development scenarios. It allows for domain-driven design and permits fast development from domain models by means of code generation. An illustrative example further clarifies the practical application of Agile MERODE, while a case study shows the planning game application in the case's context. While the approach, in its entirety, allows reducing technical debt by building the architecture in a logical, consistent and complete manner, introducing MDSE involves a trade-off with pure value-driven development. Agile MERODE contributes to the state of the art by showing how to increase user centricity in MDSE, how to align model-driven engineering with the Scrum cycle, and how to reduce the technical debt of agile developments yet remaining value-focused. [ABSTRACT FROM AUTHOR]

The role of software architecture in large-scale Agile development is important because several teams need to work together to release a single software product while helping to maximise teams' autonomy. Governing and aligning Agile architecture across autonomous squads (i.e., teams), when using the Spotify model, is a challenge because the Spotify model lacks practices for addressing Agile architecture governance. To explore how software architecture can be governed and aligned by scaling the Spotify model, we conducted a longitudinal embedded case study in a multinational FinTech organisation. Then, we developed and evaluated an approach for architectural governance by conducting an embedded case study. The collected data was analysed using Thematic Analysis and informed by selected Grounded Theory techniques such as memoing, open coding, constant comparison, and sorting. Our approach for architectural governance comprises an organisational structure change and an architecture change management process. The benefits reported by the practitioners include devolving architectural decision-making to the operational level (i.e., Architecture Owners), enhancing architectural knowledge sharing among squads, minimising wasted effort in architectural refactoring, and other benefits. The practitioners in our case study realised an improved squad autonomy by the ability to govern and align architectural decisions. We provide two key contributions in this paper. First, we present the characteristics of our proposed architectural governance approach, its evaluation, benefits, and challenges. Second, we present how the novel Heterogeneous Tailoring model was enhanced to accommodate our architectural governance approach. [ABSTRACT FROM AUTHOR]

A common way to describe requirements in Agile software development is through user stories, which are short descriptions of desired functionality. Nevertheless, there are no widely accepted quantitative metrics to evaluate user stories. We propose a novel metric to evaluate user stories called instability, which measures the number of changes made to a user story after it was assigned to a developer to be implemented in the near future. A user story with a high instability score suggests that it was not detailed and coherent enough to be implemented. The instability of a user story can be automatically extracted from industry-standard issue tracking systems such as Jira by performing retrospective analysis over user stories that were fully implemented. We propose a method for creating prediction models that can identify user stories that will have high instability even before they have been assigned to a developer. Our method works by applying a machine learning algorithm on implemented user stories, considering only features that are available before a user story is assigned to a developer. We evaluate our prediction models on several open-source projects and one commercial project and show that they outperform baseline prediction models. [ABSTRACT FROM AUTHOR]

The adequate allocation of human resources is one of the most important success factors in software projects. Although project teams can be regarded as complex systems in which a team's performance is highly influenced by the interdependencies among team members, the allocation methods applied to date have focused only on individual skills and consider project teams as units of isolated workers. The existing software project scheduling problem (SPSP) is extended to (1) consider different skills and efficiencies of employees and (2) examine the pairwise synergies between them, as well as to (3) handle the flexible structure of the project that is used in flexible management, such as agile project management. To better understand the impact of synergies on the project's cost, the solutions of the traditional and extended SPSP versions are analyzed and compared on the generated project networks. The results show not only that this factor has a highly significant impact but also that the project cost strongly depends on the structural parameters of the synergy network (e.g., topology, network size and degree centrality). Among these parameters, a low degree of centrality and some topologies, most notably star and circular networks, obtained the highest reduction in the projects' total cost. [ABSTRACT FROM AUTHOR]

Software effort estimation is a significant part of software development and project management. The accuracy of effort estimation and scheduling results determines whether a project succeeds or fails. Many studies have focused on improving the accuracy of predicted results, yet accurate estimation of effort has proven to be a challenging task for researchers and practitioners, particularly when it comes to projects that use agile approaches. This work investigates the application of the adaptive neuro-fuzzy inference system (ANFIS) along with the novel Energy-Efficient BAT (EEBAT) technique for effort prediction in the Scrum environment. The proposed ANFIS-EEBAT approach is evaluated using real agile datasets. It provides the best results in all the evaluation criteria used. The proposed approach is also statistically validated using nonparametric tests, and it is found that ANFIS-EEBAT worked best as compared to various state-of-the-art meta-heuristic and machine learning (ML) algorithms such as fireworks, ant lion optimizer (ALO), bat, particle swarm optimization (PSO), and genetic algorithm (GA). [ABSTRACT FROM AUTHOR]

Software traceability, the ability to relate software development artifacts such as requirements, design models and code to each other, is an important aspect in software development. It yields a number of benefits such as facilitating impact analysis and tracking software changes. However, for companies to reap these benefits, a proper traceability strategy—a plan for how traceability should be managed—needs to be defined and implemented. Existing literature lacks concrete guidelines for practitioners to systematically define such a strategy. In this study, we address this gap by defining a Traceability Introduction Methodology (TracIMo), which is a methodology for systematically designing, implementing and evaluating software traceability in practice. We used design science research to design TracIMo and evaluated it in a case study with an agile development team of a company in the finance domain. Our results show that TracIMo is feasible as it allows incremental definition and evaluation of a traceability strategy that is aligned with the company's traceability goals and the existing development process. We also report practical challenges encountered when designing a traceability strategy such as defining the right level of granularity and the need for defining intermediate development artifacts. [ABSTRACT FROM AUTHOR]

Organizations have increasingly applied agile project management; however, they face challenges in scaling up this approach to large projects. Thus, this study investigates the key barriers and benefits of scaling agile methods to large projects. The research approach is a literature review, applying bibliometrics and content analysis with Bibliometrix and UCINET software. We conducted a sampling process in the Web of Science and Scopus databases and surveyed 76 articles in depth. The results identified 53 barriers clustered into six main categories: organizational issues, managerial issues, agile method-specific barriers, product/process issues, customer issues, and team issues. Thirty-two benefits were coded and clustered into three categories: business, project, and team. Requirement management appears as a core topic, impacting both barriers and benefits for scaling agile project management. We identified a strong relationship between the barriers and benefits. These results can be used to create questionnaires to explore these barriers and benefits in practice. [ABSTRACT FROM AUTHOR]

Modern software development faces several challenges related to fast technological changes and shorter delivery cycles. This, is reflected in adopting agile approaches that try to lean as much as possible the software development process, from requirements engineering to system deployment. As part of this leaning effort, requirements prioritization is an important activity, as it is usually not possible to implement all requirements at once. Nevertheless, requirements prioritization is a complex activity where several stakeholder's opinions have to be taken into account hierarchically. There are many techniques to prioritize requirements, being the most accurate and complex the Analytic Hierarchy Process (AHP). AHP is very reliable when prioritizing requirements in the most accurate way due to its mathematical founding, however, this method involves matrix and vectors operations as well as a defined number of pairwise comparisons, which makes it a CPU-intensive method. This paper presents an improved AHP using evolutionary computing techniques to try to optimize requirements prioritization. The proposed approach reduces the complexity of the overall AHP process, and shows to outperform traditional AHP in terms of prioritization accuracy, according to some industry-level requirements data sets extracted from developed software systems. [ABSTRACT FROM AUTHOR]

Purpose: Allogeneic stem cell transplantation would benefit from re-engineering care towards an integrated eHealth-facilitated care model. With this paper we aim to: (1) describe the development of an integrated care model (ICM) in allogeneic SteM-cell-transplantatIon faciLitated by eHealth (SMILe) by combining implementation, behavioral, and computer science methods (e.g., contextual analysis, Behavior Change Wheel, and user-centered design combined with agile software development); and (2) describe that model's characteristics and its application in clinical practice. Methods: The SMILe intervention's development consisted of four steps, with implementation science methods informing each: (1) planning its set-up within a theoretical foundation; (2) using behavioral science methods to develop the content; (3) choosing and developing its delivery method (human/technology) using behavioral and computer science methods; and (4) describing its characteristics and application in clinical practice. Results: The SMILe intervention is embedded within the eHealth enhanced Chronic Care Model, entailing four self-management intervention modules, targeting monitoring and follow-up of important medical and symptom-related parameters, infection prevention, medication adherence, and physical activity. Interventions are delivered partly face-to-face by a care coordinator embedded within the transplant team, and partly via the SMILeApp that connects patients to the transplant team, who can monitor and rapidly respond to any relevant changes within 1 year post-transplant. Conclusion: This paper provides stepwise guidance on how implementation, behavioral, and computer science methods can be used to develop interventions aiming to improve care for stem cell transplant patients in real-world clinical settings. This new care model is currently being tested in a hybrid I effectiveness-implementation trial. [ABSTRACT FROM AUTHOR]

They identify problems with current MDE tooling support for DevOps and give an industrial experience report describing how they enabled CI/CD pipelines using DevOps and MDE. From the perspective of MDE researchers, incorporating Agile practices into MDE appeared to be a way to widen the uptake of MDE to more general software application areas. Agile methods have become a widely used software development approach across many industry sectors [[14]], with established benefits in terms of increased responsiveness to change and decreased time to market. [Extracted from the article]

Agile software development (ASD) and software product line (SPL) have shown significant benefits for software engineering processes and practices. Although both methodologies promise similar benefits, they are based on different foundations. SPL encourages systematic reuse that exploits the commonalities of various products belonging to a common domain and manages their variations systematically. In contrast, ASD stresses a flexible and rapid development of products using iterative and incremental approaches. ASD encourages active involvement of customers and their frequent feedback. Both ASD and SPL require alternatives to extend agile methods for several reasons such as (1) to manage reusability and variability across the products of any domain, (2) to avoid the risk of developing core assets that will become obsolete and not used in future projects, and (3) to meet the requirements of changing markets. This motivates the researchers for the integration of ASD and SPL approaches. As a result, an innovative approach called agile product line engineering (APLE) by integrating SPL and ASD has been introduced. The principal aim of APLE is to maximize the benefits of ASD and SPL and address the shortcomings of both. However, combining both is a major challenge. Researchers have proposed a few approaches that try to put APLE into practice, but none of the existing approaches cover all APLE features needed. This paper proposes a new dynamic variability approach for APLE that uses APLE practices for reusing features. The proposed approach (PA) is based on the agile method Scrum and the reactive approach of SPL. In this approach, reusable core assets respond reactively to customer requirements. The PA constructs and develops the SPL architecture iteratively and incrementally. It provides the benefits of reusability and maintainability of SPLs while keeping the delivery-focused approach from agile methods. We conducted a quantitative survey of software companies applying the APLE to assess the performance of the PA and hypotheses of empirical study. Findings of empirical evaluation provide evidence on integrating ASD and SPL and the application of APLE into practices. [ABSTRACT FROM AUTHOR]

The future of work has become a pressing matter of concern: Researchers, business consultancies, and industrial companies are intensively studying how new work models could be best implemented to increase workplace flexibility and creativity. In particular, the agile model has become one of the "must-have" elements for re-organizing work practices, especially for technology development work. However, the implementation of agile work often comes together with strong presumptions: it is regarded as an inevitable tool that can be universally integrated into different workplaces while having the same outcome of flexibility, transparency, and flattened hierarchies everywhere. This paper challenges such essentializing assumptions by turning agile work into a "matter of care." We argue that care work occurs in contexts other than feminized reproductive work, namely, technology development. Drawing on concepts from feminist Science and Technology Studies and ethnographic research at agile technology development workplaces in Germany and Kenya, we examine what work it takes to actually keep up with the imperative of agile work. The analysis brings the often invisibilized care practices of human and nonhuman actors to the fore that are necessary to enact and stabilize the agile promises of flexibilization, co-working, and rapid prototyping. Revealing the caring sociotechnical relationships that are vital for working agile, we discuss the emergence of power asymmetries characterized by hierarchies of skills that are differently acknowledged in the daily work of technology development. The paper ends by speculating on the emancipatory potential of a care perspective, by which we seek to inspire careful Emancipatory Technology Studies. [ABSTRACT FROM AUTHOR]

Risk management is considered as a critical project management activity that needs to be performed for successful software development. Within risk management, risk prioritization is an important process which helps the software team to effectively manage the risks at early stage of the project. In agile-based software environment, it is necessary to prioritize the risks in an effective manner in order to address the risks in shorter duration of time. In recent times, swarm intelligence techniques are widely popular in solving various optimization problems in software development process. The main reason is due to its convergence accuracy toward global optimal solution and faster computational time. In this study, an efficient risk prioritization technique termed as ARP–GWO (agile risk prioritization–grey wolf optimization) has been proposed for prioritizing the risk factors present in the agile software development using grey wolf optimization (GWO). The proposed ARP–GWO method helps the organization to mitigate the risks and ensures successful delivery of software products with good quality, in lesser cost and time. The effectiveness of ARP–GWO is analyzed using two performance metrics, namely Index of Integration and Usability Goals Achievement Metric, for which case studies are performed on five industrial projects from two different organizations. The experimental results indicate that ARP–GWO is most effective in prioritization of risks and offers better enhancement with high degree of satisfaction among developers and users as compared with the existing agile process. [ABSTRACT FROM AUTHOR]

The objective of the present work is to build and test a framework which makes use of process-based software metrics to determine the defects in software projects in an agile software development environment. A methodological framework based on fuzzy linguistic modelling has been proposed to predict the defect density using various process metrics derived from literature studies to measure the attributes stated in the agile manifesto. Further, the model is investigated by using the data set from the PROMISE software engineering repository, and its performance has been compared with existing models from the literature. The proposed model shows better accuracy (for projects with size ≥ 50 KLOC) as observed from statistical results, i.e. RMSE (18.69), NRMSE (0.0110), MMRE (0.0539) and BMMRE (0.0585). The value of R2 for all projects size up to 10 KLOC is 0.993, projects with size 10–50 KLOC is 0.998, and projects with size ≥ 50 KLOC is 0.997. The main contribution of the framework lies in the use of the process metrics and their linguistic assessment. Results obtained from the linguistic model emphasise the value of concepts related to customer involvement and interactions, the collaboration between stakeholders, responding to change, i.e. flexibility, team experience, skills, communication and coordination, as per agile manifesto. [ABSTRACT FROM AUTHOR]

Defects in requirement specifications can have severe consequences during the software development life cycle. Some of them may result in poor product quality and/or time and budget overrun due to incorrect or missing quality characteristics, such as security. This characteristic requires special attention in web applications because they have become a target for manipulating sensible data. Several concerns make security difficult to deal with. For instance, security requirements are often misunderstood and improperly specified due to lack of security expertise and emphasis on security during early stages of software development. This often leads to unspecified or ill-defined security-related aspects. These concerns become even more challenging in agile contexts, where lightweight documentation is typically produced. To tackle this problem, we designed an approach for reviewing security-related aspects in agile requirements specifications of web applications. Our proposal considers user stories and security specifications as inputs and relates those user stories to security properties via natural language processing. Based on the related security properties, our approach identifies high-level security requirements from the Open Web Application Security Project (OWASP) to be verified and generates a reading technique to support reviewers in detecting defects. We evaluate our approach via three experimental trials conducted with 56 novice software engineers, measuring effectiveness, efficiency, usefulness and ease of use. We compare our approach against using: (1) the OWASP high-level security requirements and (2) a perspective-based approach as proposed in contemporary state of the art. The results strengthen our confidence that using our approach has a positive impact (with large effect size) on the performance of inspectors in terms of effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

National governments and international organizations such as the European Commission, are promoting the increased use of information and communication technologies to assist scientists in the "mining" of knowledge. A typical workflow for a hydrogeologist consists of investigating and reporting hydrogeological processes in a study area, from data collection to model-based analysis. While hydrogeologists may feel insufficiently skilled to undertake the self-automatizing and digitizing process, the digitalization of the aforementioned workflow can be easily obtained by means of agile and parsimonious methodologies based on free and open-source software, and by using existing standards. This route is demonstrated for the digitalization of a vadose-zone monitoring system, where a large number of raw data related to water infiltration through the vadose zone are collected. The main aspects of the proposed methodology are a structured database (DB) where field data are stored, and a Python script to manage and process the available data. The structured DB was designed to store data recorded by field sensors and to generate inputs to run a transfer-function-based model to simulate percolation to the water table. Field data and model outputs were also exploited to automatically generate summary reports, like plots and table statistics. The proposed methodology can be generalized to other hydrogeological processes and case studies, as it is based on commonly available standards, basic knowledge of data-storage and data-management, and elementary programming skills to connect the different components of its suite. [ABSTRACT FROM AUTHOR]

Behavior-driven development (BDD) has gained popularity in agile software development as a means of specifying user requirements through user stories and scenarios for interactive systems under construction. Templates for guiding the writing of such stories are widely employed and can be helpful to ensure that consistent information about the requirements is provided. With the aim of getting preliminary results about how product owners (POs) write their own user stories under a predefined template, we conducted a case study with potential POs at the department in charge of business trips in a French research institute. The participants were invited to write their own user stories to describe a feature they are used to perform. The resultant stories have been analyzed to check their adherence to a template including common interactive behaviors defined by an ontology for interactive systems. Although the participants have followed different specification strategies, we observed an overall high level of adherence to the proposed template (62.26%). The results also pointed out to a wide use of domain-dependent behaviors, with the interactive behaviors defined by the ontology being, to some extent, reproduced by the participants even without prior training in the adopted vocabulary. [ABSTRACT FROM AUTHOR]

The state-of-the-practice in software development is driven by constant change fueled by continues integration servers. Such constant change demands for frequent and fully automated tests capable to detect faults immediately upon project build. As the fault detection capability of the test suite becomes so important, modern software development teams continuously monitor the quality of the test suite as well. However, it appears that the state-of-the-practice is reluctant to adopt strong coverage metrics (namely mutation coverage), instead relying on weaker kinds of coverage (namely branch coverage). In this paper, we investigate three reasons that prohibit the adoption of mutation coverage in a continuous integration setting: (1) the difficulty of its integration into the build system, (2) the perception that branch coverage is "good enough", and (3) the performance overhead during the build. Our investigation is based on a case study involving four open source systems and one industrial system. We demonstrate that mutation coverage reveals additional weaknesses in the test suite compared to branch coverage and that it is able to do so with an acceptable performance overhead during project build. [ABSTRACT FROM AUTHOR]

At present, in the software industry, agile and non-agile software development approaches are followed and effort estimation is an intrinsic part of both the approaches. This work investigates the application of deep belief network (DBN) along with antlion optimization (ALO) technique for effort prediction in both agile as well as non-agile software development environment. The study also provides a prediction interval of effort to handle uncertainty in estimation. This will help the project managers to estimate the effort in ranges instead of a crisp value. The proposed DBN-ALO approach is applied on four promise repository datasets for traditional software development (non-agile), and on three agile datasets. It provides the best results in all the evaluation criteria used. The proposed approach is also statistically validated using nonparametric tests, and it is found that DBN-ALO worked best for both agile and non-agile development approaches. [ABSTRACT FROM AUTHOR]

Understanding how developers interact with different software artifacts when performing comprehension tasks has a potential to improve developers' productivity. In this paper, we propose a method to analyze eye-tracking data using process mining to find distinct reading patterns of how developers interacted with the different artifacts. To validate our approach, we conducted an exploratory study using eye-tracking involving 11 participants. We applied our method to investigate how developers interact with different artifacts during domain and code understanding tasks. To contextualize the reading patterns and to better understand the perceived benefits and challenges participants associated with the different artifacts and their choice of reading patterns, we complemented the eye-tracking data with the data obtained from think aloud. The study used behavior-driven development, a development practice that is increasingly used in Agile software development contexts, as a setting. The study shows that our method can be used to explore developers' behavior at an aggregated level and identify behavioral patterns at varying levels of granularity. [ABSTRACT FROM AUTHOR]

Traceability is crucial for many activities in software and systems engineering including monitoring the development progress, and proving compliance with standards. In practice, the use and maintenance of trace links are challenging as artifacts undergo constant change, and development takes place in distributed scenarios with multiple collaborating stakeholders. Although traceability management in general has been addressed in previous studies, there is a need for empirical insights into the collaborative aspects of traceability management and how it is situated in existing development contexts. The study reported in this paper aims to close this gap by investigating the relation of collaboration and traceability management, based on an understanding of characteristics of the development effort. In our multiple exploratory case study, we conducted semi-structured interviews with 24 individuals from 15 industrial projects. We explored which challenges arise, how traceability management can support collaboration, how collaboration relates to traceability management approaches, and what characteristics of the development effort influence traceability management and collaboration. We found that practitioners struggle with the following challenges: (1) collaboration across team and tool boundaries, (2) conveying the benefits of traceability, and (3) traceability maintenance. If these challenges are addressed, we found that traceability can facilitate communication and knowledge management in distributed contexts. Moreover, there exist multiple approaches to traceability management with diverse collaboration approaches, i.e., requirements-centered, developer-driven, and mixed approaches. While traceability can be leveraged in software development with both agile and plan-driven paradigms, a certain level of rigor is needed to realize its benefits and overcome challenges. To support practitioners, we provide principles of collaborative traceability management. The main contribution of this paper is empirical evidence of how culture, processes, and organization impact traceability management and collaboration, and principles to support practitioners with collaborative traceability management. We show that collaboration and traceability management have the potential to be mutually beneficial—when investing in one, also the other one is positively affected. [ABSTRACT FROM AUTHOR]

Artificial bee colony (ABC) algorithm inspired by the complex behaviors of honey bees in foraging is one of the most significant swarm intelligence-based meta-heuristics and has been successfully applied to a number of numerical and combinatorial optimization problems. In this study, for increasing the early convergence performance of the ABC algorithm while protecting the qualities of the final solutions, a new exploitation mechanism from the best food source that is managed by the number of evaluations is described and its efficiency on both employed and onlooker bee phases is analyzed. The results of the experimental studies obtained from a set of benchmark problems showed that the ABC algorithm with the proposed method performs significantly better than the standard implementation of ABC algorithm and its other variants in terms of convergence speed and solution quality especially for the difficult problems that should be solved before completion of the relatively small number of fitness evaluations. [ABSTRACT FROM AUTHOR]

Agile methods are based on frequent delivery of software, improved customer satisfaction, closed interaction with the clients and accommodation of requirement change at any stage of development. However, several challenges exist such as scalability, transparency, face-to-face communication, smooth control of development, and ability to build applications from distributed locations. A framework proposed for Agile Development using Cloud Computing (ADCC) in the earlier study is evaluated in the current study. The Malaysia Research and Education Network cloud is utilized to implement the framework. An industrial survey is conducted to evaluate the framework. The results of the industrial survey show that the ADCC framework has a positive impact on the performance of agile methods and overcomes some challenges found in distributed agile development. Furthermore, the survey verifies the challenges in agile development and the solutions covers these challenges so far. [ABSTRACT FROM AUTHOR]

In agile methods, software products are developed in several releases. In each release, a new set of requirements for development is proposed. Due to technical and non-technical problems, it is almost impossible to develop all the proposed requirements in the next release. The select of an optimal subset from among all the proposed requirements has become an important problem for the developer team. The aim of this problem is to select an optimal subset from among the requirements for product development in the next release so that it has the highest satisfaction to the clients and the lowest cost for the manufacturing company. Since this problem faces two conflicting objectives and several constraints, it is placed in the NP-hard problems category. In this paper, we intend to formulate this problem for the first time as a fuzzy multi-objective optimization problem. We intend to use an artificial chemical reaction optimization algorithm to solve this problem. In the implementation stage, we make use of five interactions between requirements as one of the constraints of the problem for the first time. Two randomized fuzzy synthetic datasets are used to do the experiments. The results of the proposed algorithm are evaluated using three criteria of multi-objective problems. The results and diagrams of the proposed algorithm are very reliable and can help the developer team to make a decision. [ABSTRACT FROM AUTHOR]

Automotive manufacturers have historically adopted rigid requirements engineering processes. This allowed them to meet safety-critical requirements when producing a highly complex and differentiated product out of the integration of thousands of physical and software components. Nowadays, few software-related domains are as rapidly changing as the automotive industry. In particular, the needs of improving development speed are increasingly pushing companies in this domain toward new ways of developing software. In this paper, we investigate how the goal to increase development speed impacts how requirements are managed in the automotive domain. We start from a manager perspective, which we then complement with a more general perspective. We used a qualitative multiple-case study, organized in two steps. In the first step, we had 20 semi-structured interviews, at two automotive manufacturers. Our sampling strategy focuses on manager roles, complemented with technical specialists. In the second step, we validated our results with 12 more interviews, covering nine additional respondents and three recurring from the first step. In addition to validating our qualitative model, the second step of interviews broadens our perspective with technical experts and change managers. Our respondents indicate and rank six aspects of the current requirements engineering approach that impact development speed. These aspects include the negative impact of a requirements style dominated by safety concerns as well as decomposition of requirements over many levels of abstraction. Furthermore, the use of requirements as part of legal contracts with suppliers is seen as hindering fast collaboration. Six additional suggestions for potential improvements include domain-specific tooling, model-based requirements, test automation, and a combination of lightweight upfront requirements engineering preceding development with precise specifications post-development. Out of these 12 aspects, seven can likely be addressed as part of an ongoing agile transformation. We offer an empirical account of expectations and needs for new requirements engineering approaches in the automotive domain, necessary to coordinate hundreds of collaborating organizations developing software-intensive and potentially safety-critical systems. [ABSTRACT FROM AUTHOR]

For medical device software development organizations, it is very challenging to maintain both conformance to the strict regulatory requirements enforced by the safety-critical nature of the domain and achieve efficiency in software development. Agile software development methods provide promising solutions to overcome the efficiency issues and the challenges of traditional software development approaches in the domain. Previously, we investigated to what extent the regulatory requirements defined in MDevSPICE® (the software process assessment framework for medical device software development) are met through using eXtreme Programming (XP) and Scrum and what additional practices have to be performed to ensure safety and regulatory compliance in the medical device software development domain. In this paper, we extended the research to include the Dynamic Systems Development Method (DSDM) which covers the whole software development life cycle. Here, we provide a comprehensive and quantitative analysis of XP's and DSDM's suitability for medical device software development and briefly discuss Scrum from the same perspective. We provide the coverage ratios of processes and practices defined in MDevSPICE® when these agile software development methods are implemented. [ABSTRACT FROM AUTHOR]