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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]

The quality of requirements is typically considered as an important factor for the quality of the end product. For traditional up-front requirements specifications, a number of standards have been defined on what constitutes good quality : Requirements should be complete, unambiguous, specific, time-bounded, consistent, etc. For agile requirements specifications, no new standards have been defined yet, and it is not clear yet whether traditional quality criteria still apply. To investigate what quality criteria for assessing the correctness of written agile requirements exist, we have conducted a systematic literature review. The review resulted in a list of 16 selected papers on this topic. These selected papers describe 28 different quality criteria for agile requirements specifications. We categorize and analyze these criteria and compare them with those from traditional requirements engineering. We discuss findings from the 16 papers in the form of recommendations for practitioners on quality assessment of agile requirements. At the same time, we indicate the open points in the form of a research agenda for researchers working on this topic. [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]

An introduction is presented in which the editor discusses articles in the issue which are extended versions of the best papers from the magazine's 2017 conference, on topics including agile software, user requirements quality, and user rationale in software engineering.

Context: The recent research trend has highlighted that multiple stakeholders are involved during requirement gathering in agile software development. Hence, leading to an increased number of duplicate user stories in agile product backlog during requirement gathering. Objective: The objective of this paper is to evaluate the existing techniques employed in identifying and eliminating the duplicate user stories from agile product backlog and to overcome the existing gaps with the help of a newly proposed clustering algorithm. Method: An agile user story is expressed as a function of input and output parameters. That said multiple user stories having similar set of input parameters are most likely to be duplicate causing a redundancy. The newly proposed algorithm is used for clustering user stories having similar set of input parameters through various iterations and then removing the identified duplicate user stories from agile product backlog. This paper also introduces the concept of mass clustering which means clustering a number of user stories in single run. Results: Experimental results prove the proposed model is capable of handling small and large releases ranging between 100 to 1000 user stories with similar efficiency. The proposed clustering algorithm outperformed the clustering algorithms and resulted in 37% decrease in agile product backlog by eliminating duplicate user stories causing redundancy. The experimental results are obtained from the logs of the MATLAB tool. However, the provided algorithm is generic in nature and can be implemented using R, Python or SAS programming tools. The provided algorithms employs proven matrix operations. Conclusion: The proposed clustering algorithm overcomes the limitation of existing user story management methods and clearly out performs when compared with other clustering algorithms. Finally, this paper gives recommendations about the usage of the provided clustering algorithm during agile release planning for eliminating duplicate user stories from agile product backlog. [ABSTRACT FROM AUTHOR]

Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial intelligence (AI) has empowered smart manufacturing and digital transformation. AI enhances the migration towards industry 4.0 through AI-based decision-making by analyzing real-time data to optimize different processes such as production planning, predictive maintenance, quality control etc., thus guaranteeing reduced costs, high precision, efficiency and accuracy. This paper explores AI-driven smart manufacturing, revolutionizing traditional approaches and unlocking new possibilities throughout the major phases of the industrial equipment lifecycle. Through a comprehensive review, we delve into a wide range of AI techniques employed to tackle challenges such as optimizing process control, machining parameters, facilitating decision-making, and elevating maintenance strategies within the major phases of an industrial equipment lifecycle. These phases encompass design, manufacturing, maintenance, and recycling/retrofitting. As reported in the 2022 McKinsey Global Survey (https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review), the adoption of AI has witnessed more than a two-fold increase since 2017. This has contributed to an increase in AI research within the last six years. Therefore, from a meticulous search of relevant electronic databases, we carefully selected and synthesized 42 articles spanning from 01 January 2017 to 20 May 2023 to highlight and review the most recent research, adhering to specific inclusion and exclusion criteria, and shedding light on the latest trends and popular AI techniques adopted by researchers. This includes AI techniques such as Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Bayesian Networks, Support Vector Machines (SVM) etc., which are extensively discussed in this paper. Additionally, we provide insights into the advantages (e.g., enhanced decision making) and challenges (e.g., AI integration with legacy systems due to technical complexities and compatibilities) of integrating AI across the major stages of industrial equipment operations. Strategically implementing AI techniques in each phase enables industries to achieve enhanced productivity, improved product quality, cost-effectiveness, and sustainability. This exploration of the potential of AI in smart manufacturing fosters agile and resilient processes, keeping industries at the forefront of technological advancements and harnessing the full potential of AI-driven solutions to improve manufacturing processes and products. [ABSTRACT FROM AUTHOR]

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]

, we have a special section and eight regular research papers. The first two regular research papers are linked by the common theme of code smells, and these are followed by a systematic literature review on risk factors found in software development. The paper derives formal, methodological, and technological requirements for a modelling language quality evaluation method to tackle some of the open model-driven engineering quality challenges. [Extracted from the article]

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]

Although extensive research has been conducted on the characteristics of the agile developer, little attention has been given to the features of the software-testing role. This paper explores the human factors of the software testers working in agile projects through a qualitative study focusing on how these factors are perceived. We interviewed 22 agile software practitioners working in three international companies: 14 testers, five developers, and three designers. Additionally, we observed 11 meetings and daily work of 13 participants in one of the companies. Our findings show that the views on the human factors shaping the agile software tester's role were crystallized into seven traits, which the agile team members saw as central for the software-testing role: the ability to see the whole picture, good communication skills, detail-orientation, structuredness, creativeness, curiosity, and adaptability. The testers spent half their day communicating and learned how to mitigate the fact that they had to bring bad news to other project members. They also facilitated communication between the business side and development. Based on our results, we propose the seven traits as dimensions to consider for organizations recruiting agile software testers, as well as a reference for IT and non-IT professionals considering a software-testing career. [ABSTRACT FROM AUTHOR]

Agile hardware development methodology has been widely adopted over the past decade. Despite the research progress, the industry still doubts its applicability, especially for the functional verification of complicated processor chips. Functional verification commonly employs a simulation-based method of co-simulating the design under test with a reference model and checking the consistency of their outcomes given the same input stimuli. We observe limited collaboration and information exchange through the design and verification processes, dramatically leading to inefficiencies when applying the conventional functional verification workflow to agile development. In this paper, we propose workflow integration with collaborative task delegation and dynamic information exchange as the design principles to effectively address the challenges on functional verification under the agile development model. Based on workflow integration, we enhance the functional verification workflows with a series of novel methodologies and toolchains. The diff-rule based agile verification methodology (DRAV) reduces the overhead of building reference models with runtime execution information from designs under test. We present the RISC-V implementation for DRAV, DiffTest, which adopts information probes to extract internal design behaviors for co-simulation and debugging. It further integrates two plugins, namely XFUZZ for effective test generation guided by design coverage metrics and LightSSS for efficient fault analysis triggered by co-simulation mismatches. We present the integrated workflows for agile hardware development and demonstrate their effectiveness in designing and verifying RISC-V processors with 33 functional bugs found in NutShell. We also illustrate the efficiency of the proposed toolchains with a case study on a functional bug in the L2 cache of XiangShan. [ABSTRACT FROM AUTHOR]

Colocated software development teams benefit from natural work context building, which occurs mainly thanks to the team members, virtually, being forced to listen to what others are talking about. They absorb the information not by directing their attention to the communication, but by being exposed to it and perceiving it peripherally. The same effect of peripheral perception can be enforced with instant messaging, which is a predominant way of communication in distributed teams. However, forcing team members to observe too many and mostly unrelated message notifications can be distracting and causing unnecessary work interruption. This paper presents an approach and tool that ensure peripheral perception in instant messaging constrained by a continuously extracted work context. This is achieved by maintaining a personal work context from developer activities and using this context to filter instant messages to be displayed. A four-week experiment carried out with one of the teams of seven members in the Team Project course at our university indicates that message filtering based on continuous work context extraction performs better over common channel based filtering (as available in Slack). More precisely, message filtering based on continuous work context extraction decreases work interruption and distraction. [ABSTRACT FROM AUTHOR]

How then can agile software development methods be used efficiently while meeting the safety, interoperability, and security demands of the safety-critical software systems? This Special Issue of Quality of Information and Communication Technology presents papers on advanced methods, techniques, and tools for supporting quality approaches to ICT engineering and management. This special issue addresses the issues of software safety and security, interoperability, and risk-centric software development approach in the papers it contains. [Extracted from the article]

Artificial intelligence-driven software development paradigms have been attracting much attention in academia, industry and the government. More specifically, within the last 5 years, a wave of data analytics is affecting businesses from all domains, influencing engineering management practices in many industries and making a difference in academic research. Several major software vendors have been adopting a form of “intelligent” development in one or more phases of their software development processes. Agile for example, is a well-known example of a lifecycle used to build intelligent and analytical systems. The agile process consists of multiple sprints; in each sprint a specific software feature is developed, tested, refined and documented. However, because agile development depends on the context of the project, testing is performed differently in every sprint. This paper introduces a method to predict software failures in the subsequent agile sprints. That is achieved by utilizing analytical and statistical methods (such as using Mean Time between Failures and modelling regression). The novel method is called: analytics-driven testing (ADT). ADT predicts errors and their locations (with a certain statistical confidence level). That is done by continuously measuring MTBF for software components, and using a forecasting regression model for estimating where and what types of software system failures are likely to occur. ADT is presented and evaluated. [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]

Society today is moving towards rapid digitalization of almost every aspect of our lives. From healthcare and transport to work or entertainment, we depend on software products that need to function properly. The adequate construction of these software products can be evaluated and certified by means of quality standards. However, adopting quality standards is a complex and time-consuming task that requires experienced practitioners with advanced knowledge about standards and development practices. This presents a dichotomy for development companies that are transitioning to more agile schemes, where the necessary quality knowledge is scarce and poorly documented, and is slowly learnt and applied by novel practitioners. To overcome these issues, this paper presents a model-driven approach to automate the analysis of software development processes that must be aligned to quality standards. The approach has been implemented in an open-source tool and applied to a case study to automatically generate a gap analysis by reusing expert knowledge related to the ISO 9001 standard. The application has demonstrated it is possible to reduce the effort required from expert practitioners to perform the analysis and improve development processes to ensure the fulfillment of specific quality standards. [ABSTRACT FROM AUTHOR]

The ability to develop innovative Business Models (BMs) with high speed and good Return of Investment has become the cornerstone for the competitiveness of many successful businesses operating in many different Business Model Ecosystems (BMES) today. Business Model Innovation (BMI) appears even more important in these days—as well as in the Biogas 2020 BMES—as digitalization affect all areas of innovating and operating businesses. Increased digitalization leads to new ways of working, communicating, cooperating and supporting BMI. Thanks to these new technologies todays businesses are more interconnected in physical, digital and virtual networks. The cooperation between businesses, academia and the use of competences across different domains becomes more important to strengthen BMI and advance BMI. One main challenge however of digitization of BMI is modeling human behavior and cognitive processes in BMI processes into logical expressions that can be digitized and automated. Our state-of-the-art review shows that has been no research in this field related to BMI. The aim is therefore to find a way to value the BMI process and support the BMI process in a more advanced way than previously supported by sensor technologies. This paper report on a first experiment carried out in a cross interdisciplinary CGC research group with 3 different European Biogas Technological BMI (TBMI) challenges. The aim of this first experiment was twofold. (1) To support the test and further development of a conceptual model of a future agile BMI learning environment first presented at the Global Wireless Summit 2017 conference in Cape Town, South Africa. The the aim is later to adapt these results, findings and experiment recommendation to prepare a largescale global experiment in 2019. The used sensor technology backbone was to this experiment made as a special build cloud-based sensing BM and sensing BMI room—imbedded in special built BMI rooms called B-lab/Beecube. The B-labs was embedded with advanced mobile and wireless sensors, both environmental and wearable by the participants. The aim was to test use and utilization of these sensors in BMI to improve observations, improve analyzing abilities and predict in a latter stage human behavior in BMI processes, (2) to support the development of an advanced network based BMI environment and in a latter perspective to support a Multi Business Model Innovation (MBMI) framework embedded with AI, machine learning, AI, Multi Business model archetypes and pattern techniques. In our experiment we were able to use the Biogas 2020 BMES and project as a testbed. We report on our preliminary findings and draw some proposals to how the large scale experiment technical and BMI wise can be adjusted. [ABSTRACT FROM AUTHOR]

Reinforcement learning (RL) has emerged as an effective approach for building an intelligent system, which involves multiple self-operated agents to collectively accomplish a designated task. More importantly, there has been a renewed focus on RL since the introduction of deep learning that essentially makes RL feasible to operate in high-dimensional environments. However, there are many diversified research directions in the current literature, such as multi-agent and multi-objective learning, and human-machine interactions. Therefore, in this paper, we propose a comprehensive software architecture that not only plays a vital role in designing a connect-the-dots deep RL architecture but also provides a guideline to develop a realistic RL application in a short time span. By inheriting the proposed architecture, software managers can foresee any challenges when designing a deep RL-based system. As a result, they can expedite the design process and actively control every stage of software development, which is especially critical in agile development environments. For this reason, we design a deep RL-based framework that strictly ensures flexibility, robustness, and scalability. To enforce generalization, the proposed architecture also does not depend on a specific RL algorithm, a network configuration, the number of agents, or the type of agents. [ABSTRACT FROM AUTHOR]

University-industry collaboration (UIC) projects are complex undertakings, that can involve multiple parties or stakeholders. Effective management of UICs can mean the difference between success and failure, in terms of technology transfer and research commercialization. This research paper focuses on the micro-level analysis of UICs and in particular the project management practices that can help major UICs deliver benefits and broader societal impact. PM has been evolving toward more hybrid approaches involving both traditional and agile practices. A conceptualization of a hybrid approach is presented based on a literature review. This conceptualization is then used as a starting point for exploratory empirical research. Participant observation, document analysis, and thirty semi-structured interviews were conducted in a large UIC case study to help identify PM practices and check their relevance. Data analysis led to a framework comprising 29 transversal or must-have practices distributed throughout the project lifecycle and 30 contingent or optional practices, divided into traditional, agile and common. This research extends the existing knowledge on UICs by giving a micro-level perspective on managing UIC projects and providing evidence of the adoption of hybrid approaches to assure the overall governance of significant inter-organizational endeavors. The framework provides a roadmap for future major UIC projects. [ABSTRACT FROM AUTHOR]

This article focuses on the strategic issue of an agile supply chain. Different goals are considered in supply chain design. Today, the concept of sustainability in supply chains plays an important role in goal setting. In general, sustainability leads to less economic, social, and environmental risks, and attention to this type of sustainability covers many criteria in the literature. Therefore, in this study, optimization of the stability of a supply chain network has been considered. In addition, a lesser-known aspect of sustainability, the political aspect, has been added to the previous aspects. This paper assumes four levels, namely supplier, wholesaler, retailer, and customer. An optimal network structure is designed to consider economic, social, and environmental sustainability and the new measure of political sustainability. The design of this supply chain is done by defining a mathematical model that has several objective functions, including economic, political, and environmental goals. These objective functions select the relationships and links between the levels in a supply chain network. For this purpose, a directional graph corresponding to a supply chain is designed. Then, with the help of an ideal multi-objective planning problem, an optimal configuration is obtained, which is a subgraph of the main network graph. The target problem has been modeled for a holding company which is a supply chain for COVID-19 drugs. Then, problem is solved using Multi-objective Particle Swarm Optimization (MOPSO) metaheuristics algorithm and NSGAII multi-objective genetic algorithm. A comparison was carried out between these two methods, and the results indicated that MOPSO performed better. The value of the objective functions is calculated, and the best value for the considered functions is obtained. Also, the amount of drug supply has been obtained by two distributors. Also, the amount of medicine purchased by the customer from each pharmacy is determined. [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]

In the last years, agile methodologies are gaining substantial momentum, becoming increasingly popular in a broad plethora of industrial contexts. Unfortunately, many obstacles have been met while pursuing adoption in secure and safe systems, where different standards and operational constraints apply. In this paper, we propose a novel agile methodology for the development and innovation of safety-critical systems. In particular, we developed an extension of the well-known Scrum methodology and discussed the complete workflow. We finally validated the applicability of the proposed methodology over a real case study from the railway domain. [ABSTRACT FROM AUTHOR]

An empirical study aims to investigate the development in the research on the assessment of supply chain agility. Here, a state-of-the-art literature review of research conducted between 2000 and 2017 is presented to provide a comprehensive basis for future studies related to supply chain agility measurement and management. A descriptive analysis and a content analysis of 66 publications in the Scopus and the Web of Science online databases are conducted. The selected articles may prove to be a good starting point for the identification of gaps and issues in the field of supply chain assessment; for example, the effects of investments in information technology (IT) networks and multi-functional resources on supply chain agility and the consequent effects on corporate strategies. Further, there are aspects related to supply chain networks and their performances that are summarised in the last section of the paper as future scope for research. [ABSTRACT FROM AUTHOR]

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches. [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]

Despite the wide adoption of agile methodologies, software development teams still struggle to meet requirements, partially due to practitioners' lack of motivation to apply agile techniques in practice. We propose a gamification software tool to make Scrum techniques more fun and engaging for practitioners. This paper presents the results of the first iteration of a larger research effort that follows the Design Science Research methodology, in which a prototype was developed as a Jira Software app and evaluated with a real-world Scrum team. The results suggest that gamification can positively impact practitioners' motivation by changing the atmosphere within the team, even if it does not contribute to the improvement of Scrum practices adoption. The metrics corresponding to Scrum techniques slightly increased after using the app, but this result probably cannot be attributed to practitioners' improved motivation. Quantitative analysis and interviews with the team members showed that the gamified experience should be more challenging. We conclude that gamification's potential can be better achieved if more and better studies are conducted based on mixed methods, even if the conditions are not ideal. The app has been improved based on the feedback received, and currently is being evaluated with other Scrum teams. [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]

Software organizations focus on delivery of quality software that meets customer requirements, with zero defects. In agile software development, quality means quality of code wherein the quality is maintained through the use of test-driven development and refactoring. During test driven development of software, large number of defects have been detected and preliminary studies on the causes of these defects revealed the complex nature of the problem. Robust design methodology is one of the important quality improvement techniques used in manufacturing systems focusing on reducing variability in the output. This paper integrates robust design methodology into agile software development in order to capture maximum number of defects at the earliest. The proposed framework is implemented on the defect data from a large telecommunication organization. The software quality is measured in terms of metrics such as number of defects during development of software. Robust design methodology is applied on software during development to determine the optimal parameter values which will influence maximum defects to be captured before the software is released in the market. Three crucial parameters from the dataset are extracted using the analytic hierarchy process. The outcome of the study is the determination of the optimal levels of the input parameters that will maximize the number of defects captured. As agile processes rarely use formal review and inspection processes, the proposed approach will build inherent defect capturing capability in the software development process. [ABSTRACT FROM AUTHOR]

The challenge of reducing complexity, failures and time in software development are tasks found in the vast majority of information technology companies. The professionals seek to structure the development of applications through agile methodologies, but in reality, there are several difficulties in planning the time to make applications development tasks. To help in this situation, this paper proposes the use of fuzzy neural network composed by fuzzy rules to assist in the construction of a specialist system based on interpretable rules, facilitating the prediction of software development hours according to the complexity of the elements present in the project. To support in the data fuzzification process, an incremental density technique is proposed for the first layer of the model. To improve the sensitivity of the neuron present in the neural network a Leaky-ReLU type activation function is used to obtain the results. The set of rules to be created, through tests in a real database based on the technique of use case point, can help in the development of future expert systems, to be used by these professionals. The results of the tests were efficient to generate predictability about the efforts to build the software. [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]

When NoSQL database systems are used in an agile software development setting, data model changes occur frequently and thus, data is routinely stored in different versions. The management of versioned data leads to an overhead potentially impeding the software development. Several data migration strategies exist that handle legacy data differently during data accesses, each of which can be characterized by certain advantages and disadvantages. Depending on the requirements for the software application, we evaluate and compare different migration strategies through metrics like migration costs and latency as well as precision and recall. Ideally, exactly that strategy should be selected whose characteristics fulfill service-level agreements and match the migration scenario, which depends on the query workload and the changes in the data model which imply an evolution of the database schema. In this paper, we present a methodology of self-adapting data migration, which automatically adjusts migration strategies and their parameters with respect to the migration scenario and service-level agreements, thereby contributing to the self-management of database systems and supporting agile development. [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]

In this paper, we focus on the innovative advanced data analysis dedicated for product owners in software development teams. The goal of our novel solutions is to increase cognition and decision making in rapid software development process. The major contribution of this work is the methodology and the tool that gathers the input raw data from the tools such as GitLab or SonarQube, and processes the data further (e.g., using Apache Kafka, Kibana, and Spark) to calculate and visualize more advanced metrics, product factors (e.g., in accordance to Quamoco model), and indicators, and to find correlations between them. Then, such high-level data are shown to product owners to increase their cognition, situational awareness, and decision-making capabilities. We have now implemented the proof-of-concept system which was positively validated by product owners using the real data from their projects. [ABSTRACT FROM AUTHOR]

The validation of any new methodological proposal demands several real-life implementations. However, organizations are reluctant to invest without the firm guarantee that they will be returned the entire expended amount of money. For this purpose, expert judgment techniques are very useful to provide a less-costly initial validation that, when positive, may encourage organizations to use these new proposals. Therefore, the primary goal of the paper will be to assess how expert judgment techniques based on the Delphi method can be applied to Web Engineering field and, more in particular, to assess the validity of the NDT-Agile framework. NDT-Agile is a framework that combines Agile and Web Engineering techniques to meet Capability Maturity Model Integration development goals. The paper presents a real example of an application of a Delphi-based expert judgment method to assess NDT-Agile framework validity, explaining the design as well as the selection and usage of the different techniques it involves. The application of the method will allow assessing benefits and limitations of use in Web Engineering. As a main conclusion, we will state the utility of the proposed methods to obtain a low-resource initial validation of a certain proposal. Finally, we will identify further lines of research related to the analyzed topics. [ABSTRACT FROM AUTHOR]

This paper is aimed at presenting a locomotion control framework to realize agile and robust locomotion behaviors on conventional stiff-by-nature legged robots. First, a trajectory generator that is capable of characterizing angular momentum is utilized to synthesize reference CoM trajectories and associated force inputs, in accordance with the target locomotion profile. Second, the controller evaluates both force and position errors in the joint level, using a servo controller and an admittance control block. The trade-off between the position and force errors is naturally adjusted via admittance control coefficients. Implementing the controller on a 4-link, 3-jointed one-legged robot, we conducted several balancing and running experiments under challenging conditions; e.g., balancing on a moving cart, balancing on a surface with varying orientation, running on a flat surface, running on an inclined surface. The experimental study results indicated that the locomotion controller enabled the robot to perform untethered one-legged running and to maintain its balance when subject to disturbances. [ABSTRACT FROM AUTHOR]

Large open and closed source organizations like Google, Facebook and Mozilla are migrating their products towards rapid releases. While this allows faster time-to-market and user feedback, it also implies less time for testing and bug fixing. Since initial research results indeed show that rapid releases fix proportionally less reported bugs than traditional releases, this paper investigates the changes in software testing effort after moving to rapid releases in the context of a case study on Mozilla Firefox, and performs a semi-systematic literature review. The case study analyzes the results of 312,502 execution runs of the 1,547 mostly manual system-level test cases of Mozilla Firefox from 2006 to 2012 (5 major traditional and 9 major rapid releases), and triangulates our findings with a Mozilla QA engineer. We find that rapid releases have a narrower test scope that enables a deeper investigation of the features and regressions with the highest risk. Furthermore, rapid releases make testing more continuous and have proportionally smaller spikes before the main release. However, rapid releases make it more difficult to build a large testing community , and they decrease test suite diversity and make testing more deadline oriented. In addition, our semi-systematic literature review presents the benefits, problems and enablers of rapid releases from 24 papers found using systematic search queries and a similar amount of papers found through other means. The literature review shows that rapid releases are a prevalent industrial practice that are utilized even in some highly critical domains of software engineering, and that rapid releases originated from several software development methodologies such as agile, open source, lean and internet-speed software development. However, empirical studies proving evidence of the claimed advantages and disadvantages of rapid releases are scarce. [ABSTRACT FROM AUTHOR]

The Agile nature allows changes within the development procedure which can sometimes be non-predictable and affect the cost and time of the software. Face-to-face communication appears to be a faster process in Agile Software Development (ASD) in practice, but issues such as understandability and communicativeness cause ambiguity between the customer and the developer. Among the existing works, achieving light but sufficient documentation in ASD remains a challenge. Most previous studies have simply highlighted the issues associated with less documentation, its limitations, and challenges, but no proper solution has yet been proposed. As an initial step in our theoretical study, we conducted a systematic literature review (SLR) to identify the related components and subcomponents that are applicable in supporting Agile documentation. As such, the fundamental concepts related to software documentation have been studied in order to align with documentation in ASD. The identification of these components can be useful in achieving the concept of "light but sufficient" documentation in Agile, which will aid in achieving customer satisfaction. [ABSTRACT FROM AUTHOR]

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]

Despite of many criticisms, agile software development (Beck et al., Manifesto for Agile Software Development, , []) philosophy has been proved to be quite successful to increase the project success rate up to a significant extent. The primary reasons behind the criticism of agile are the strong violation of the traditional disciplined software engineering theories, principles and practices. The goal of this research paper is to establish the fact that agility may also be achieved by following traditional process models especially with BRIDGE (Mandal, 2009 IEEE International Advance Computing Conference (IACC 2009) Patiala, India, []) process model. Hence, the aim of this paper is to integrate the agile and traditional disciplined software development process models and establish the compatibility between both the approaches. At the beginning, we have explored the objectives and principles of agile software development. Next, we briefly discussed the BRIDGE process model and further justified that-following BRIDGE process model, the philosophy of agile may also be achieved and conclude that BRIDGE model has both the capability of traditional software development process model as well as of the agile process. [ABSTRACT FROM AUTHOR]

In globally distributed software development, does it matter being agile rather than structured? To answer this question, this paper presents an extensive case study that compares agile (Scrum, XP, etc.) vs. structured (RUP, waterfall) processes to determine if the choice of process impacts aspects such as the overall success and economic savings of distributed projects, the motivation of the development teams, the amount of communication required during development, and the emergence of critical issues. The case study includes data from 66 projects developed in Europe, Asia, and the Americas. The results show no significant difference between the outcome of projects following agile processes and structured processes, suggesting that agile and structured processes can be equally effective for globally distributed development. The paper also discusses several qualitative aspects of distributed software development such as the advantages of nearshore vs. offshore, the preferred communication patterns, and the effects on project quality. [ABSTRACT FROM AUTHOR]

There is wide acceptance in the software engineering field that industry and research can gain significantly from each other and there have been several initiatives to encourage collaboration between the two. However there are some often-quoted challenges in this kind of collaboration. For example, that the timescales of research and practice are incompatible, that research is not seen as relevant for practice, and that research demands a different kind of rigour than practice supports. These are complex challenges that are not always easy to overcome. Since the beginning of 2013 we have been using an approach designed to address some of these challenges and to bridge the gap between research and practice, specifically in the agile software development arena. So far we have collaborated successfully with three partners and have investigated three practitioner-driven challenges with agile. The model of collaboration that we adopted has evolved with the lessons learned in the first two collaborations and been modified for the third. In this paper we introduce the collaboration model, discuss how it addresses the collaboration challenges between research and practice and how it has evolved, and describe the lessons learned from our experience. [ABSTRACT FROM AUTHOR]

This paper presents a polarization agile antenna design that can be helpful for underwater communication, using the integrated structure of power divider and phase shifter to feed a square patch antenna. The purpose of this research is to discover new ways of communication by developing a polarization agile antenna, integrated feeding structure that can generate two equal-amplitude signals with fast phase switching between 90 ∘ and 270 ∘ , realizing the agility control for the dual circular polarization of the square patch antenna. Compared with the traditional polarization-agile antennas with the individual power divider and phase shifter networks, the proposed design has the advantages of good amplitude, phase and polarization imbalance performances, a simple control circuit, low insertion loss, and compact design which proves it to be best underwater communication. [ABSTRACT FROM AUTHOR]

As the international market environment changes more and more fierce, the potential for enterprises to improve their ability to adapt to market changes and improve their competitiveness will become smaller and smaller, and the difficulty will increase, such as product delivery speed, quality, cost and service. The level will obviously be constrained by the relationship between product manufacturers and suppliers of raw materials and components, product distributors, etc. More and more enterprises are beginning to effectively carry out internal management changes, and the traditional competitive relationship among enterprises gradually transforming into a new type of partnership. The supply chain plays an increasingly important role in the process of enterprise competition. High-level supply chain operation and management are the key to successful operation of the company. The supply chain is a complex system, which requires members to reduce the "bullwhip effect" through information sharing, to achieve decision synchronization, reduce inventory, and improve market response. Therefore, information sharing is an important part of supply chain research. The competition in the century is the competition between supply chains. The end-customer's individualization of products, the increasing requirements for diversification, and the increasing uncertainty of the economic environment have prompted enterprises to pay more and more attention to the coordination of relations among members of the supply chain. The key to coordinate the supply chain is to realize information sharing. This paper proposes an architecture of agile supply chain management system based on the multi-agent information sharing under the guidance of self-organization theory. At the same time, the prototype of the supply chain management system was established by using web technology, distributed object technology (CORBA/DCOM) and related information resource organization and management technology. [ABSTRACT FROM AUTHOR]

Requirements communication plays a vital role in development projects in coordinating the customers, the business roles and the software engineers. Communication gaps represent a significant source of project failures and overruns. For example, misunderstood or uncommunicated requirements can lead to software that does not meet the customers' requirements, and subsequent low number of sales or additional cost required to redo the implementation. We propose that requirements engineering (RE) distance measures are useful for locating gaps in requirements communication and for improving on development practice. In this paper, we present a case study of one software development project to evaluate this proposition. Thirteen RE distances were measured including geographical and cognitive distances between project members, and semantic distances between requirements and testing artefacts. The findings confirm that RE distances impact requirements communication and project coordination. Furthermore, the concept of distances was found to enable constructive group reflection on communication gaps and improvements to development practices. The insights reported in this paper can provide practitioners with an increased awareness of distances and their impact. Furthermore, the results provide a stepping stone for further research into RE distances and methods for improving on software development processes and practices. [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]