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An increasing number of companies aim to enable their development teams to work in an agile manner. When introducing agile teams, companies face several challenges. This paper explores the kind of leadership needed to support teams to work in an agile way. One theoretical agile leadership concept describes a Scrum Master who is supposed to empower the team to lead itself. Empirical findings on such a leadership role are controversial. We still have not understood how leadership unfolds in a team that is by definition self-organizing. Further exploration is needed to better understand leadership in agile teams. Our goal is to explore how leadership changes while the team matures using the example of the Scrum Master. Through a grounded theory study containing 75 practitioners from 11 divisions at the Robert Bosch GmbH we identified a set of nine leadership roles that are transferred from the Scrum Master to the Development Team while it matures. We uncovered that a leadership gap and a supportive internal team climate are enablers of the role transfer process, whereas role conflicts may diminish the role transfer. To make the Scrum Master change in a mature team, team members need to receive trust and freedom to take on a leadership role which was previously filled by the Scrum Master. We conclude with practical implications for managers, Product Owners, Development Teams and Scrum Masters which they can apply in real settings., Robert Bosch Automotive Steering GmbH, Projekt DEAL

Waste management leads to the demolition of waste conducted by recycling and landfilling. Deep learning and the Internet of things (IoT) confer an agile solution in classification and real-time data monitoring, respectively. This paper reflects a capable architecture of the waste management system based on deep learning and IoT. The proposed model renders an astute way to sort digestible and indigestible waste using a convolutional neural network (CNN), a popular deep learning paradigm. The scheme also introduces an architectural design of a smart trash bin that utilizes a microcontroller with multiple sensors. The proposed method employs IoT and Bluetooth connectivity for data monitoring. IoT enables control of real-time data from anywhere while Bluetooth aids short-range data monitoring through an android application. To examine the efficacy of the developed model, the accuracy of waste label classification, sensors data estimation, and system usability scale (SUS) are enumerated and interpreted. The classification accuracy of the proposed architecture based on the CNN model is 95.3125%, and the SUS score is 86%. However, this smart system will be adjustable to household activities with real-time waste monitoring.

We investigate a general solution based on reinforcement learning for the agile satellite scheduling problem. The core idea of this method is to determine a value function for evaluating the long-term benefit under a certain state by training from experiences, and then apply this value function to guide decisions in unknown situations. First, the process of agile satellite scheduling is modeled as a finite Markov decision process with continuous state space and discrete action space. Two subproblems of the agile Earth observation satellite scheduling problem, i.e., the sequencing problem and the timing problem are solved by the part of the agent and the environment in the model, respectively. A satisfactory solution of the timing problem can be quickly produced by a constructive heuristic algorithm. The objective function of this problem is to maximize the total reward of the entire scheduling process. Based on the above design, we demonstrate that Q-network has advantages in fitting the long-term benefit of such problems. After that, we train the Q-network by Q-learning. The experimental results show that the trained Q-network performs efficiently to cope with unknown data, and can generate high total profit in a short time. The method has good scalability and can be applied to different types of satellite scheduling problems by customizing only the constraints checking process and reward signals.

Agile development methods are widely used among business enterprises. Since the introduction of the Agile Manifesto in 2001, several agile methods have been implemented, first in single-team set-ups and later in larger multi-team set-ups for complex Information Technology (IT) system development. However, the adoption of agile methods has been slow in the public sector. This is also reflected in the academic literature, as there are only a few studies discussing agile adoption in public organizations. This paper contributes to research on the use of agile practices specifically in the context of public organizations, and sheds light on the challenges a public organization may face while adopting these practices. The aim of this paper is to identify and categorize the challenges that may hinder efficient adoption and use of agile methods in public IT projects that include private software vendors. This research is based on a case study of a large governmental office. As a result, this paper presents several categories of identified challenges, the root causes of these challenges, and a discussion of the characteristics of these challenges for the public sector.

In the recent years, the advances in mobile technology have brought an exorbitant change in daily lifestyle of individuals. Smartphones/mobile devices are rampant in all aspects of human life. This has led to an extreme demand for developing software that runs on mobile devices. The developers have to keep up with this high demand and deliver high-quality app on time and within budget. For this, estimation of development and testing of apps play a pivotal role. In this paper, a Systematic Literature Review (SLR) is conducted to highlight development and testing estimation process for software/application. The goal of the present literature survey is to identify and compare existing test estimation techniques for traditional software (desktop/laptop) and for mobile software/application. The characteristics that make mobile software/application different from traditional software are identified in this literature survey. Further, the trend for developing the software is towards agile, thus this study also presents and compares estimation techniques used in agile software development for mobile applications. The analysis of literature review suggests filling a research gap to present formal models for estimating mobile application considering specific characteristics of mobile software.

The maturity of organisations is measured using process assessment models like the International Organization for Standardization (ISO)/IEC 33001. Product quality is refined with internal and external product quality characteristics based on models like the ISO/IEC 25010. With the shift from the Tailorism‐driven process orientation to a more people‐centric organization, the process and product quality dimensions have to be extended by the teamwork quality (TWQ) dimension. For the sake of systematic organization development, this new third quality dimension needs to be integrated into existing quality frameworks to achieve a holistic quality approach. This article introduces agile TWQ as the method of choice. It explains its design, implementation and evaluation in the large enterprise context of the Volkswagen AG. It provides insights into the effectivity of this approach in heterogeneous multi‐team settings, as well as into its strengths, weaknesses, and limitations.

Social companion robots are getting more attention to assist elderly people to stay independent at home and to decrease their social isolation. When developing solutions, one remaining challenge is to design the right applications that are usable by elderly people. For this purpose, co-creation methodologies involving multiple stakeholders and a multidisciplinary researcher team (e.g., elderly people, medical professionals, and computer scientists such as roboticists or IoT engineers) are designed within the ACCRA (Agile Co-Creation of Robots for Ageing) project. This paper will address this research question: How can Internet of Robotic Things (IoRT) technology and co-creation methodologies help to design emotional-based robotic applications? This is supported by the ACCRA project that develops advanced social robots to support active and healthy ageing, co-created by various stakeholders such as ageing people and physicians. We demonstra this with three robots, Buddy, ASTRO, and RoboHon, used for daily life, mobility, and conversation. The three robots understand and convey emotions in real-time using the Internet of Things and Artificial Intelligence technologies (e.g., knowledge-based reasoning).

Robotics and artificial intelligence (AI) are revolutionizing all spheres of human life. From industrial processes to graphic design, the implementation of automated intelligent systems is changing how industries work. The spread of robots and AI systems has triggered academic institutions to closely examine how these technologies may affect the humanity—this is how the fields of roboethics and AI ethics have been born. The identification of ethical issues for robotics and AI and creation of ethical frameworks were the first steps to creating a regulatory environment for these technologies. In this paper, we focus on regulatory efforts in Europe and North America to create enforceable regulation for AI and robotics. We describe and compare ethical principles, policies, and regulations that have been proposed by government organizations for the design and use of robots and AI. We also discuss proposed international regulation for robotics and AI. This paper tries to highlight the need for a comprehensive, enforceable, and agile policy to ethically regulate technology today and in the future. Through reviewing existing policies, we conclude that the European Unition currently leads the way in defining roboethics and AI ethical principles and implementing them into policy. Our findings suggest that governments in Europe and North America are aware of the ethical risks that robotics and AI pose, and are engaged in policymaking to create regulatory policies for these new technologies.

As the most fundamental infrastructure in the current Internet, the Border Gateway Protocol (BGP) supports the inter-connectivity of different Autonomous Systems (ASs) and then the reachability can be achieved from any network in the Internet. However, due to the lack of security consideration during its original design, the BGP suffers from multiple security threats. Another challenge is that it cannot support the future sophisticated applications with deterministic routing. In this article, we propose a novel BGP management architecture, namely BGPChain, which is based on the blockchain in order to establish a secure, smart, and agile routing infrastructure for the future Internet.

Different types of agile approaches and LEAN methodologies have guided the development of solutions based on a minimum viable product mainly from the product design and development body of the knowledge. However, these approaches offer generic practices for a wide variety of solutions. This study presents an original proposal that provides a vertical solution for the conception of a minimum viable multimedia system, with a practice expressed in the graphic notation language of Essence. The study presents a contribution through a case study related to the clarity about the flow of activities, techniques, and specific tools that the practitioners must use to define a minimum viable multimedia system. This work also contributes to the criteria unification of the teamwork to carry out the follow-up of the progress in realizing the activities necessary to complete the job needed for the conception of the minimum viable multimedia system, using an MS-value sub-alpha.

Purpose The application of agility principles and methodologies on Enterprise Architecture (EA) is a promising field. This paper aims to provide an in-depth study of the Agile Enterprise Architecture (AEA) by studying EA practitioners’ perspectives to propose a foundational framework for AEA. Design/methodology/approach The authors formulate a foundational framework that defines the AEA motivators, enablers and blockers using the agile manifesto as one of the AEA enablers where a total of 156 EA stakeholders with at least one year of experience in enterprise architecture were surveyed, and a set of hypotheses was analyzed and tested based on the proposed framework. The authors also develop a quantitative method to evaluate the agility index of the EA based on the introduced framework. Findings The research results show with significance that enterprise architects perceive positively the application of the agility methodologies on the enterprise architecture. This perception is primarily affected by the enterprise size, the EA dependency and the agile methodologies awareness. The findings also indicate that AEA is primarily motivated by the Business and IT Change Ready and Responsive EA. Finally, an EA Agility Index (EAAI) was designed to assess the agility application of the EA based on the three forces, i.e. motivators, enablers and blockers. Research limitations/implications Because of the chosen research approach and the sample size, the research results may lack generalizability. Also, EAAI designed was not thoroughly tested. Practical implications The paper includes implications for the design and development of an EA Agility Index, and the need to increase the awareness of the agility methodologies to overcome the blocker of the unfamiliarity with the agile methodologies implying that the current business models in enterprise must be more aligned with the agile methodologies. Originality/value While there are efforts to develop AEA frameworks, one of the major findings of the literature review conducted is that there is evident research gap in the literature on the perception and associated factors of the EA stakeholders on having an agile enterprise architecture. This paper attempts to fill this gap.

PurposeThe purpose of this study is to understand how IT capabilities for knowledge management and process integration can build a firm's agile process capabilities for sensing, strategic decision and responding. The study also investigates how the three agile capabilities affect firm performance in different competitive environments.Design/methodology/approachThis study conducted a large-scale field survey with firms in the United States. Survey invitations were sent to business executives of the target firms. A total of 254 complete samples were collected for our hypotheses test.FindingsThe results confirm the overall significant roles of IT capabilities in the three agile capabilities. The results further reveal that the IT capability for knowledge management has a higher influence on sensing capability, while the IT capability for process integration has a higher influence on responding capability. Moreover, strategic decision and responding capabilities are more important in the high market competition. However, in the low market competition, sensing capability becomes more important while responding capability demonstrates a negative impact on firm performance.Originality/valueThis study helps both academics and practitioners better understand a firm's IT-agility-performance mechanism. Particularly, our findings guide how to achieve agile capabilities and what to focus on under the different levels of market competition.

The open-source hardware community contributes a variety of processors and accelerators, but combining them effectively into a complete System-on-Chip (SoC) remains a difficult task. We present a design flow for the seamless hardware and software integration of accelerators into a complete SoC and for its evaluation through rapid FPGA-based prototyping. By leveraging ESP, our open-source platform for agile heterogeneous SoC design, we demonstrate FPGA prototypes of various SoC designs, featuring the NVIDIA Deep Learning Accelerator and the Ariane RISC-V 64-bit processor core.

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT), or AIoT, has breathed a new life into IoT operations and human-machine interactions. Currently, resource-constrained IoT devices usually cannot provide sufficient capability for data storage and processing so as to support building modern AI models. An intuitive solution is to integrate cloud computing technology into AIoT and exploit the powerful and elastic computing as well as the storage capacity of the servers on the cloud end. Nevertheless, the network bandwidth and communication latency increasingly become serious bottlenecks. The emerging edge computing can complement the cloud-based AIoT in terms of communication latency, and hence attracts more and more attention from the AIoT area. In this paper, we present an industrial edge-cloud collaborative computing platform, namely Sophon Edge, that helps to build and deploy AIoT applications efficiently. As an enterprise-level solution for the AIoT computing paradigm, Sophon Edge adopts a pipeline-based computing model for streaming data from IoT devices. Besides, this platform supports an iterative way for model evolution and updating so as to enable the AIoT applications agile and data-driven. Through a real-world example, we demonstrate the effectiveness and efficiency of building an AIoT application based on the Sophon Edge platform.

Machine-based classification usually involves some computer programs, known as algorithms, developed using several mathematical formulations to accelerate the automated classification process. Along with the exponential increase in the size and computational complexity of the data today, such optimized, robust, agile and reliable computational algorithms are required which can efficiently carry out these conforming classification tasks. In this review paper, deterministic optimization techniques have been analysed that are efficiently employed for machine learning applications. In this review, systematic literature review approach has been adopted in which 200 research articles were downloaded from which 100 latest articles has been selected based on the most commonly employed neural networks’ techniques. Moreover, the reported neural networks techniques based on Back Propagation Neural Network (BPNN), Recurrent Neural Networks (RNNs) Algorithm and Levenberg-Marquardt (LM) with several hybridized classification algorithms based on optimization techniques have been indicated that are commonly used to optimize and benefit the classification process.

The aim of this article is to analyze the challenges and success factors on organizations’ path to agile transformation, as frequently discussed in the literature and encountered in business practice. The research conducted proved that large-scale agile transformations require a dedicated approach with set of tools and best practices in place. The implementation challenges and barriers have been categorized into method-, organization-, culture- and technology-oriented groups. As a result of an in-depth analysis carried on for the purpose of this paper, a dedicated methodology of agile transformation has been proposed to ease the implementation process.

According to the statistics, the majority of IT projects run 50–150 percent over budget, which indicates the importance of managing its cost. In agile methodologies which are widely used in software development, little attention is given to cost management. Lack of specialized cost management tools in agile practices raises the question of the feasibility of adapting traditional project management methods and techniques. The purpose of the research is to improve the quality of IT projects cost control processes by developing a project cost management model using the Agile Earned Value Management method. The paper discusses the EVM techniques which have been adopted to provide the benefits of traditional EVM in Agile projects. There are some misconceptions that EVM techniques are too difficult to perform effectively on projects implemented using agile approaches (i.e. Scrum framework). The challenges are primarily associated with the fact that the EVM method requires creating a complete description of project tasks and a detailed schedule of their execution at the initial stage allowing accurate estimates of the actual data and monitoring the project progress from start to completion. On the other hand, Scrum emphasizes the need for incremental, multi-level planning and discourages planning software projects down to the lowest level of decomposition in the early stages. The reason for this is the high degree of ambiguity inherent in complex software systems, and the high probability of changes that make fully defining the requirements up front nearly impossible. However, upon closer examination of Sprint attributes, such as fixed duration, fixed backlog, cost measurement of sprint tasks, the ultimate goal of delivering a minimum viable product – leads us to the conclusion that Sprint can be considered as a subproject to which the mechanism of the EVM method can be applied using the same metrics. The paper further summarizes the main provisions and guidelines of the AgileEVM method, based on which its process model is developed. The inputs of the model are initial release baseline parameters and data captured at the completion of each Sprint: Planned Sprints (PS); Planned Release Points (PRP); Budget at Complete (BAC); Points Completed (PC), Points Added (PA), and Sprint Cost (SC). The controls are the AgileEVM method guidelines. The mechanisms are project manager and necessary software (MS Excel, MS Project). At the output of the model we obtain forecast indicators: Estimate to Complete (ETC), Estimate at Complete (EAC), Number of Total Sprints (N), and Release Date (RD). The final conclusion of the conducted research is that the application of the Earned Value Management method to projects implemented with Scrum enables the project manager and the project team with a valuable tool to monitor the progress of their work and to take appropriate measures.

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.

The analytic hierarchy process (AHP) is recognised as one of the most commonly applied methods in the multiple attribute decision-making (MADM) literature. In the AHP, encompassing uncertainty feature necessitates using suitable uncertainty theories, since dealing efficiently with uncertainty in subjective judgements is of great importance in real-world decision-making problems. The neutrosophic set (NS) theory and grey systems are two reliable uncertainty theories which can bring considerable benefits to uncertain decision-making. The aim of this study is to improve uncertain decision-making by incorporating advantages of the NS and grey systems theories with the AHP in investigating sustainability through agility readiness evaluation in large manufacturing plants. This study pioneers a combined neutrosophic-grey AHP (NG-AHP) method for uncertain decision-making modelling. The applicability of the hybrid NG-AHP method is shown in an illustrative real-case study for agility evaluations in the Iranian steel industry. The computational results indicate the effectiveness of the proposed method in adequately capturing uncertainty in the subjective judgements of decision makers. In addition, the results verify the significance of the research in group decision-making under uncertainty. The practical outcome reveals that, to become a more sustainable agile steel producer in the case country, they should first focus on the “organisation management agility” as the most significant criterion in the assessment followed by “manufacturing process agility,” “product design agility,” “integration of information system,” and “partnership formation capability,” respectively.

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.

PurposeThe concept of workforce agility has become increasingly popular in recent years. However, defining it has sparked much discussion and ambiguity. Recognizing this ambiguity, this paper aims to inductively develop a behavioral taxonomy of workforce agility.Design/methodology/approachThe authors interviewed 36 experts in the field of agility and used concept mapping and the critical incident technique to create a behavioral taxonomy.FindingsThe authors identified a behavioral taxonomy consisting of ten dimensions: (1) accepting changes, (2) decision making, (3) creating transparency, (4) collaboration, (5) reflection, (6) user centricity, (7) iteration, (8) testing, (9) self-organization, and (10) learning.Research limitations/implicationsThe authors’ research contributes to the literature in that it offers an inductively developed behavioral taxonomy of workforce agility with ten dimensions. It further adds to the literature by tying the notion of workforce agility to the performance literature.Practical implicationsThe authors’ results suggest that it might be beneficial for companies to take all workforce agility dimensions into account when creating an agile culture, starting agile projects, integrating agility into hiring decisions or evaluating employee performance.Originality/valueThis paper uses an inductive approach to define workforce agility as a set of behavioral dimensions, integrating the scientific as well as the practitioner literature on agility.

When developing a Learning Management System (LMS) using Scrum, we noticed that it was quite often necessary to redefine some system behaviour scenarios, due to ambiguities in the requirement specifications, or due to misinterpretations of stories reported by the Product Owners (POs). The definition of test suites was also cumbersome, resulting in test suites that were incomplete or did not at all comply with the system requirements. Based on this experience and to deal with these problems, in this paper, we propose the ScrumOntoBDD approach to agile software development, which combines Scrum, ontologies and Behaviour-Driven Development (BDD). This approach is centred on the concepts and techniques of Scrum and BDD and focuses on the planning and analysis phases of the software life cycle, since the BDD tools currently provide little support to these phases, while most of the problems during the LMS development were found exactly there. We claim that our approach improves the software development practices in this respect. Furthermore, ScrumOntoBDD employs ontologies in order to reduce ambiguities intrinsic to the use of a natural language as a BDD ubiquitous language. In this paper, we illustrate and systematically evaluate our approach, showing that it is beneficial since it improves the communication between members of an agile development team.

Purpose Blockchain and Internet of Things (IoT) technologies have recently gained much attention for Industry 4.0. With the emergence of disruptive technologies, it has become essential to redesign the business for innovations based on blockchain–IoT integrated architecture that helps organizations to improve agility in their operations. The paper aims to discuss this issue. Design/methodology/approach An industrial pump was Sensorized and IoTized to monitor its operations on real time and take predictive measures for managing these assets with more agility. The developed architecture was further extended for proposing the use of blockchain and how it can benefit the organization. Findings The known features of blockchain such as increasing the capacity of decentralization, trust-less transactions, security and allowing autonomous coordination of the devices along with the boons of IoT will help achieve the motto of improving agility in Industry 4.0. Originality/value This paper gives a new dimension to utilization of blockchain technology. blockchain along with IoT that gives a way forward for industries like manufacturing, oil and gas, engineering and construction, utilities, etc. to re-designing the business organization in a more agile way.

Agile software development has large success rate due to its benefits and promising nature but natively where the size of the project is small. Requirement engineering (RE) is crucial as in each software development life cycle, “Requirements” play a vital role. Though agile provides values to customer’s business needs, changing requirement, and interaction, we also have to face impediments in agile, many of which are related to requirement challenges. This article aims to find out the challenges being faced during requirement engineering of agile projects. Many research studies have been conducted on requirement challenges which are somehow biased, no suggestions are given to improve the agile development process, and the research does not highlight large-scale agile development challenges. Hence, this article covers all the challenges discussed above and presents a comprehensive overview of agile models from requirement engineering perspective. The findings and results can be very helpful for software industry to improve development process as well as for researchers who want to work further in this direction.

PurposeQuality management standards (e.g. ISO 9001) lead to process conformance in the realization of quality goods and services; however, they can be rather document intensive. This paper investigates documentation practices used for aligning “light-weight” Scrum methods with ISO 9001 in a leading healthcare software firm.Design/methodology/approachThe authors investigated how “light-weight” Scrum approaches fit with organizational documentation practices for ISO 9001 compliance in one leading healthcare software development firm. Three investigative rounds were conducted with software professionals having different Scrum roles to understand their challenges in maintaining process documentation with Scrum methods.FindingsISO standards stipulate certain mandatory documentation as evidence that certain pre-defined processes are followed in the build-up of quality goods and services. However, this may result in “heavy-weight” document driven approaches that interfere with “light-weight” Scrum methods. Case study findings reveal tensions faced by software professionals in maintaining the ISO 9001 documentation. That is, while some level of documentation is considered useful, software professionals consider certain other documentation tasks to be excessive and cumbersome. Further, many operational documents were written retrospectively for administrative compliance, leading to reduced, incomplete and ambiguous descriptions.Practical implicationsThe study provides much value for practitioners in adapting their documentation with ongoing operational processes. Further, the critique on current ISO 9001 implementations in Agile environments has implications for future documentation practice.Originality/valueThe empirically drawn findings showcase some of the challenges in maintaining ISO 9001 documentation within Scrum projects. The study has contributed to both theory and practice in relation to the co-existence of ISO drawn standards with Agile approaches used for software development.

Writing reliable software is hard. No matter how determined we all are to avoid it, we do make mistakes and at a fairly predictable rate. What makes a software system reliable is not determined just by the care we take in planning and structuring a design but also by the methods we use in catching those pesky bugs that come along for the ride. For safety-critical code, the use of strong static source code analyzers has become an essential part of the development process. The best analyzers are based on solid theory and maintained by large teams of highly skilled developers. The tools can patiently trace through complex execution paths to reveal a range of subtle bugs, although, of course, only the types of bugs the tools have been trained on. The tools can be slow and costly, though, and the warnings they generate are sometimes difficult for humans to evaluate accurately.

High dependability software systems must be developed and maintained using rigorous safety-assurance practices. By leveraging traceability, we can visualize and analyze changes as they occur, mitigate potential hazards, and support greater agility.

With the increasing popularity and applications of 2.5-D integration, both chip and packaging industries are making significant progress in this direction. In advanced high-density 2.5-D packages, package redistribution layers become similar to chiplet back-end-of-line routing layers, and the gap between them scales down with pin density improvement. Chiplet–package interactions become significant and severely affect system performance and reliability. Moreover, 2.5-D integration offers opportunities to apply novel design techniques. The traditional die-by-die design approach neither carefully considers these interactions nor fully exploits the cross-boundary design opportunities. In this article, we present a holistic chiplet–package co-optimization flow for high-density 2.5-D packaging technologies with little performance overhead and zero pipeline-depth increase. Our holistic extraction can capture all parasitics from chiplets and the package and improve system performance through iterative optimizations. Both drop-in and pay-as-you-use design methodologies are implemented for agile development and quick turn-around time. To prove the effectiveness of our flow, we implement several design cases of a microcontroller system in TSMC 65-nm technology. Our design methodologies can reduce the performance gap by 85% with respect to the 2-D reference design after holistic optimizations. We demonstrate design flexibility and development cost-saving by presenting several flavors of a three chiplets system. To validate our flow in silicon, we tape-out a chip in TSMC 65-nm technology with measured data and validated functionality.

Although the skills of robot manipulators are becoming technically more complex, the unprecedented cost-effective access to recently unveiled intelligent robots has the potential to unleash as yet unimagined automation capabilities. A key technology behind this opportunity for companies to gain a competitive edge through an informed and intelligent robotized automation is the robotic digital twin (RDT). As such, the RDT will be instrumental in mirroring targeted properties of a physical robot to obtain a digital sibling flexibly harnessed in virtual testbeds to understand, predict, and shape the robot performance. However, these objectives remain challenging to well-established simulators. This is because the architectural and functional capabilities they support are not sufficiently in-line with ever-growing and varying demands for agile and cost-efficient manipulations. As a consequence, robot stakeholders can hardly use RDTs to unlock opportunities and meet needs from prospective markets. This article contributes to addressing this gap. We introduce a novel concept for the development of a RDT that helps create and add value to current and future robotized cyber–physical applications. Hereinafter, referred to as the value-driven RDT (vdRDT), it systematically captures the robot dynamics and purposefully farms data, about which its services reason, to facilitate insight and deliver capabilities as well as benefits to stakeholders. Experiment results show that vdRDTs enlarge the scope of, adapt to, and revitalize robotized applications carried out in different fields.

Every software development company makes software development based on a specific approach. There are a number of approaches to software development, both disciplined and agile. Each approach includes a set of different activities. Sometimes, the specific nature of a company’s work requires a specific approach, but the need to make work more efficient, faster and better requires implementing activities of other approaches. Then hybrid software development approaches come in. The paper presents an expert survey to examine the most important software development activities, the combinations of development approaches that are used in software development processes and the way of upgrading existing approaches. The evaluated activities of software development process are classified according to their nature – whether they correspond with a team, organisation, documentation, development, and testing. The conclusions are also made on the practices that are required most – disciplined, Agile or hybrid.

Now that drones have evolved from bulky platforms to agile devices, a challenge is to combine multiple drones into an integrated autonomous system, offering functionality that individual drones cannot achieve. Such multidrone systems require connectivity, communication, and coordination. We discuss these building blocks along with case studies and lessons learned.

Effort estimation is an essential task in a software project as it helps to establish feasible plans for the implementation of a project. It largely influences success or failure of the project. Project planning becomes more efficient with accurate effort estimates, thus providing a number of benefits to the organization. Estimating effort in agile projects has been a challenging task for researchers. Several studies exist in that domain. While some have considered people-related factors, others have catered for project-related factors for estimating effort. Others have adopted machine learning (ML) techniques to produce an accurate estimation. This paper presents a model to estimate and predict effort in a sprint using ML techniques while considering various factors that affect a sprint. The model has been evaluated using various regression algorithms, namely linear regression, K-nearest neighbor, decision tree, polynomial kernel, radius basis function and multi-layer perception (MLP). The model has produced more reliable estimates, with low error values using MLP algorithm.

Increased competitiveness of the market enforces companies to respond quickly and appropriately to sudden changes in the market in order to adapt to continuously updated conditions of business environment and keep their survivals. Agility concept rises at this level due to necessity of coping with unpredictable changes and uncertainty. Agility enables the firms responsiveness in a quick and an effective way to the set of interdependent changes required in design, production, marketing and organization of the companies. This study addresses agile supplier selection problem. Hierarchical fuzzy technique for order preference by similarity to ideal solution approach (TOPSIS) is proposed for agile supplier selection problem in an airline company.

Scrum is currently the most widely used agile methodology. However, it is regarded as a framework rather than a concrete process. Unfortunately, the resources available on Scrum do not explicitly define its variable parts and do not offer proper guidance on how to resolve those variabilities. Process (re)configuration is thus left to Scrum Retrospective sessions; this can delay the vital decisions that can significantly improve the process before problems arise. This paper aims to address the problems associated with configuring/reconfiguring Scrum by identifying all the variabilities (variation points) in the Scrum framework, along with the situations where a variation point can be resolved by one or more specific variants. We propose a Software Process Line (SPrL) approach for achieving this: we have represented the process variabilities of Scrum as a Scrum metaprocess, which acts as the core process of a generic SPrL for Scrum. The situations in which each variation point of the metaprocess can be resolved by a specific variant have been identified. The metaprocess has been implemented in the Medini-QVT tool, along with transformation rules that provide the means for automatic resolution of the variabilities. The validity of the metaprocess has been evaluated through an industrial case study, the results of which show that the metaprocess is applicable in real situations. Furthermore, the results indicate that the processes instantiated from the metaprocess can improve the existing processes by proposing specific practices for addressing their shortcomings.

Software process standards and models are used in large- and medium-sized organizations to reach the Iron Triangle. In contrast, small and very small entities either ignore them or cannot apply them because these standards and models are technically and economically not affordable. Consequently, agile software development practices are usually used by small and very small organizations. The ISO/IEC 29110 series of standards and guides are now available for very small organizations, but their utilization with agile practices represents an agility-rigor reconciliation problem. In this research, we report the experimental evaluation of Scrum + EPG (a reconciled agile-rigorous software Project Management process from Scrum, and the Project Management process of the ISO/IEC 29110 series-Entry profile, documented in an Electronic Process Guide). Scrum + EPG was compared to Scrum EPG (a non-modified Scrum process also documented in an Electronic Process Guide). Thirty-two international academicians and practitioners, including experts and novices on agile practices, from Latin America, North America, and Asia–Pacific regions, evaluated six metrics of usability. A within-subjects design and Wilcoxon matched-pairs signed-rank tests were applied for collecting and analyzing the experimental data. The statistical results support the claim that the Scrum + EPG was considered a high-quality conciliated agile-rigorous software Project Management process for the Entry profile. Given the scarcity of similar studies and the need for reconciling agile-rigorous software development practices, this study contributes to a plausible solution for very small organizations. Finally, further empirical research is encouraged to confirm, update, and extend the results reported in this investigation.

This paper proposes a new method of combining SAT with discrete event simulation. This new integration proved useful for designing a solver for capacity analysis in early phase railway construction design. Railway capacity is complex to define and analyze, and existing tools and methods used in practice require comprehensive models of the railway network and its timetables. Design engineers working within the limited scope of construction projects report that only ad-hoc, experience-based methods of capacity analysis are available to them. Designs often have subtle capacity pitfalls which are discovered too late, only when network-wide timetables are made—there is a mismatch between the scope of construction projects and the scope of capacity analysis, as currently practiced. We suggest a language for capacity specifications suited for construction projects, expressing properties such as running time, train frequency, overtaking and crossing. Such specifications can be used as contracts in the interface between construction projects and network-wide capacity analysis. We show how these properties can be verified fully automatically by building a special-purpose solver which splits the problem into two: an abstracted SAT-based dispatch planning, and a continuous-domain dynamics with timing constraints evaluated using discrete event simulation. The two components communicate in a CEGAR loop (counterexample-guided abstraction refinement). This architecture is beneficial because it clearly distinguishes the combinatorial choices on the one hand from continuous calculations on the other, so that the simulation can be extended by relevant details as needed. We describe how loops in the infrastructure can be handled to eliminate repeating dispatch plans, and use case studies based on data from existing infrastructure and ongoing construction projects to show that our method is fast enough at relevant scales to provide agile verification in a design setting. Similar SAT modulo discrete event simulation combinations could also be useful elsewhere where one or both of these methods are already applicable such as in bioinformatics or hardware/software verification.

PurposeThe purpose of this essay is to illustrate how project management “pull” and AI or analytics technology “push” are likely to result in incremental and disruptive evolution of project management capabilities and practices.Design/methodology/approachThis paper is written as a critical essay reflecting the experience and reflections of the author with many ideas drawn from and extending selected items from project management, artificial intelligence (AI) and analytics literatures.FindingsNeither AI nor sophisticated analytics is likely to elicit hands on attention from project managers, other than those producing AI or analytics-based artifacts or using these tools to create their products and services. However, through the conduit of packaged software support for project management, new tools and approaches can be expected to more effectively support current activities, to streamline or eliminate activities that can be automated, to extend current capabilities with the availability of increased data, computing capacity and mathematically based algorithms and to suggest ways to reconceive how projects are done and whether they are needed.Research limitations/implicationsThis essay includes projections of possible, some likely and some unlikely, events and states that have not yet occurred. Although the hope and purpose are to alert readers to the possibilities of what may occur as logical extensions of current states, it is improbable that all such projections will come to pass at all or in the way described. Nonetheless, consideration of the future ranging from current trends, the interplay among intersecting trends and scenarios of future states can sharpen awareness of the effects of current choices regarding actions, decisions and plans improving the probability that the authors can move toward desired rather than undesired future states.Practical implicationsProject managers not involved personally with creating AI or analytics products can avoid mastering detailed skill sets in AI and analytics, but should scan for new software features and affordances that they can use enable new levels of productivity, net benefit creation and ability to sleep well at night.Originality/valueThis essay brings together AI, analytics and project management to imagine and anticipate possible directions for the evolution of the project management domain.

The fast development of the so-called shared economy as well as collaborative networked organization increases the call for responsive and strongly interconnected production and delivery systems. The closer connection of information systems and control systems has to be achieved, as “Industry 4.0” developed by leading industries in Europe, USA and Asia requires to set new IT models in order to support agile collaborative business processes and production control processes. Whereas the service-based organizations and technologies, such as Service-Oriented Architecture, Web 2.0, Cloud and Everything as a Service technologies as well as Business models, have been successfully deployed to support agile systems relying on service selection, composition and orchestration, only few works have addressed cloud-based control systems. Despite the flexibility provided by the Internet of Thing, the integration of Cyber-Physical systems (CPS) in production control system is limited due to their lack of interoperability. To overcome this limit and provide a smooth integration of CPS systems in collaborative production process control, we propose a service-based control model integrating sensors, controllers and actuators. To support the Industry 4.0 digital transformation, including collaborative production process design and management, our Control as a Service model relies on control ontology. Our control ontology gathers IoT devices (sensors and actuators $$\ldots $$ ) and services, including their functional and non-functional properties description. Then, a Control as a Service architecture is designed to facilitate the development of cloud control system via two steps: service pre-selection/pre-composition, event-driven and context-aware service orchestration. The measurement of three core components, data manager, event manager and context manager, shows the feasibility of application of our Control as a Service model/architecture in a supply chain temperature control use case.

Agile approaches help software development project teams to better meet user needs and ensure flexibility in uncertain environments. But using agile approaches invites changes to the project and increases interactions between team members, which both cause interruptions in the workplace. While interruptions can help in task completion and increase process flexibility, they can also hinder employee productivity. We conducted an exploratory study of four agile software development teams. Our analysis identified (1) programming-related work impediments, (2) interaction-related interruptions, and (3) interruptions imposed by the external environment, which were managed by improved information retrieval and reduced team dependencies.

Integrating information and communication technologies in teaching and learning is recognized as a relevant and promising practice. However, integration can be complex, tedious, and draining. We propose an innovative approach for enhancing teaching and learning in a simple, pleasant, and effective way: repurposing a virtual world platform to develop a simulation-based training. Minecraft Education, a virtual world platform, was used to develop a simulation-based training on agile project management. So far, 153 university students have applied the Scrum framework to execute a simulated project in Minecraft Education. Results show that students’ perceived learning is very positive and that their learning experience was stimulating and challenging. Recommendations are formulated to guide practitioners and teachers adopting and adapting a “readymade” virtual world platform for teaching and learning.

Background Queensland, Australia has been successful in containing the COVID-19 pandemic. Underpinning that response has been a highly effective virus containment strategy which relies on identification, isolation, and contact tracing of cases. The dramatic emergence of the COVID-19 pandemic rendered traditional paper-based systems for managing contact tracing no longer fit for purpose. A rapid digital transformation of the public health contact tracing system occurred to support this effort. Objectives The objectives of the digital transformation were to shift legacy systems (paper or standalone electronic systems) to a digitally enabled public health system, where data are centered around the consumer rather than isolated databases. The objective of this paper is to outline this case study and detail the lessons learnt to inform and give confidence to others contemplating digitization of public health systems in response to the COVID-19 pandemic. Methods This case study is set in Queensland, Australia. Universal health care is available. A multidisciplinary team was established consisting of clinical informaticians, developers, data strategists, and health information managers. An agile “pair-programming” approach was undertaken to application development and extensive change efforts were made to maximize adoption of the new digital workflows. Data governance and flows were changed to support rapid management of the pandemic. Results The digital coronavirus application (DCOVA) is a web-based application that securely captures information about people required to quarantine and creates a multiagency secure database to support a successful containment strategy. Conclusion Most of the literature surrounding digital transformation allows time for significant consultation, which was simply not possible under crisis conditions. Our observation is that staff was willing to adopt new digital systems because the reason for change (the COVID-19 pandemic) was clearly pressing. This case study highlights just how critical a unified purpose, is to successful, rapid digital transformation.

In this project, the challenge was to "deploy software faster than the coronavirus spread." In a project with such peculiar characteristics, several factors can influence success, but some clearly stand out: top management support, agility, understanding and commitment of the project team, and the technology used. Conventional development approaches and technologies would simply not be able to meet the requirements promptly.

Agile supply chains facilitate sustainability through higher effectiveness and lower wastage. Agile supply chain frameworks in extant literature are designed for static supply chains and high-granular data that are only available at fixed periods. With the increasing interest in the Internet of Things (IoT) and blockchain technology for supply chain visibility and trust and the potential availability of fine-granular real-time data from related sensor networks, there is a need to reconsider existing agile supply chain frameworks. IoT and blockchain technology together reinforce the provision of trusted visibility that facilitates ease of tracking and tracing that is required in agile supply chains. We study existing agile supply chain frameworks and their characteristics – both positive and negative – and use this information to develop an agile supply chain framework that incorporates recent developments in IoT and blockchain technology.

Agile methods adopted in the software industries have given a new edge as well as scope to software outcomes. To determine anomalies that has been triggered by analytic hierarchical process (AHP) o...

Innovation is essential to transform healthcare delivery systems, but in complex adaptive systems innovation is more than ‘light bulb events’ of inspired creativity. To achieve true innovation, organisations must adopt a disciplined, customer-centred process. We developed the process of Agile Innovation as an approach any complex adaptive organisation can adopt to achieve rapid, systematic, customer-centred development and testing of innovative interventions. Agile Innovation incorporates insights from design thinking, Agile project management, and complexity and behavioural sciences. It was refined through experiments in diverse healthcare organisations. The eight steps of Agile Innovation are: (1) confirm demand; (2) study the problem; (3) scan for solutions; (4) plan for evaluation and termination; (5) ideate and select; (6) run innovation development sprints; (7) validate solutions; and (8) package for launch. In addition to describing each of these steps, we discuss examples of and challenges to using Agile Innovation. We contend that once Agile Innovation is mastered, healthcare delivery organisations can habituate it as the go-to approach to projects, thus incorporating innovation into how things are done, rather than treating innovation as a light bulb event.

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.

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.

This study examines changing team cognition and cognitive artifact use as agile software development iterations progress to better understand team member interactions. The four case studies conducted observed the distributed cognition on the team changing from planning, managing, developing, and concluding tasks in iterations to deliver working functionality. Cognitive artifacts used throughout the iteration also changed. This study provides a clearer understanding of how and when team cognition and artifact use change as agile software development teams use artifacts to manage projects. Interactions between team members and artifacts move from individual to social interactions as the iteration progresses with frequent, short, continuous communication and interactions.

Nowadays agile and practical methods for lean manufacturing and production process reengineering are in urgent need for Small and Medium Enterprises (SMEs). However, due to the limitations in obtai...

PurposeNumerous approaches from the field of economics already exist for the improvement of business processes. In the field of software development, work has been done on improving development processes. For years, the focus here has been on agile approaches. Although various approaches for improving business processes exist, it is becoming increasingly difficult to adapt business processes to the fast-moving conditions of the market and the business environment. Agile approaches address this issue. Thus, not only software development processes, but also business processes should benefit from agile approaches.Design/methodology/approachTo this end, values and principles of the Agile Manifesto, agile methods such as Scrum, and various agile practices such as the Kanban board should be applied in business processes. This paper examines the work already done on this topic. With the help of a systematic literature review (SLR), literature studies dealing with the implementation of the agile approach in business processes are identified.FindingsThis paper presents, investigates and contrasts 12 primary sources dealing with agile and business processes and shows how they are different/ equal regarding three research questions.Originality/valueWe provide an overview of existing approaches handling the combination of agile and business processes to improve business processes.