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The nine papers in this special section focus on new developments in agile software and reports on applications for its use. A key aspect for the extensive use of agile software is that it supports developers with coping with the growing uncertainty and turbulence in technological and market environments. Feedback and change are at the core of Agile for a dynamic, evolving, and organic, rather than static, predefined, and mechanistic development process advocated by waterfall management. To create timely, high-quality, cost-efficient, and innovative solutions, Agile developers organized in small, colocated, autonomous teams, build and test software in rapid iterative cycles, actively involving users to gather feedback, updating the project scope, and plan "on-the-fly," using face-to-face communication as opposed to documentation. These papers contribute to the state-of-the-art of agile research by offering a rich, up-todate account of the dynamics occurring when expanding Agile into "not-just-software" contexts of the key challenges and perils related to the scaling and of the possible solutions to them. [ABSTRACT FROM AUTHOR]

In this paper, a self-adaptive protection system is proposed for adjusting the time dial (TD) of reclosers found in electrical power distribution systems (EPDSs). The self-adjustment is carried out in both phase and ground protection. The methodology considers the fuses along the feeder to obtain the fuse-saving philosophy. This feature allows less interference on the protection system already implemented by the electrical power distribution utilities. This methodology also allows using other frameworks, such as the estimation of the fault distance. The software used for computer modeling and simulation was PSCAD™/EMTDC™. The flexibility provided by the method, which allows the incorporation of new logic and changes in decision-making, resulted in an adaptive method with a good performance against different locations, types, and fault impedance. It also resulted in better coordination between the protection devices (PDs). The results compared with well-coordinated conventional protection have shown significant performance gain with the adaptive system. [ABSTRACT FROM AUTHOR]

Thanks to relatively small public and secret keys, the Supersingular Isogeny Key Encapsulation (SIKE) protocol made it into the third evaluation round of the post-quantum standardization project of the National Institute of Standards and Technology (NIST). Even though a large body of research has been devoted to the efficient implementation of SIKE, its latency is still undesirably long for many real-world applications. Most existing implementations of the SIKE protocol use the Montgomery representation for the underlying field arithmetic since the corresponding reduction algorithm is considered the fastest method for performing multiple-precision modular reduction. In this paper, we propose a new data representation for supersingular isogeny-based Elliptic-Curve Cryptography (ECC), of which SIKE is a sub-class. This new representation enables significantly faster implementations of modular reduction than the Montgomery reduction, and also other finite-field arithmetic operations used in ECC can benefit from our data representation. We implemented all arithmetic operations in C using the proposed representation such that they have constant execution time and integrated them to the latest version of the SIKE software library. Using four different parameters sets, we benchmarked our design and the optimized generic implementation on a 2.6 GHz Intel Xeon E5-2690 processor. Our results show that, for the prime of SIKEp751, the proposed reduction algorithm is approximately 2.61 times faster than the currently best implementation of Montgomery reduction, and our representation also enables significantly better timings for other finite-field operations. Due to these improvements, we were able to achieve a speed-up by a factor of about 1.65, 2.03, 1.61, and 1.48 for SIKEp751, SIKEp610, SIKEp503, and SIKEp434, respectively, compared to state-of-the-art generic implementations. [ABSTRACT FROM AUTHOR]

Since modern cyber-physical power systems are vulnerable to coordinated wide-area cyber attacks, it is necessary to mitigate the potential risk as much as possible. At the planning stage, the defender can utilize software diversity, which is a common phenomenon that the cyber software of different substations comes from different competing vendors. Therefore, different kinds of software may not be exposed to the same zero-day security loophole, preventing the attacker from taking charge of multiple substations at the same time. In this paper, the optimal scheme of software deployment considering long-term risk mitigation is studied. Firstly, the framework of diversity-based cyber defense against malicious attacks is formulated. Secondly, the risk index based on representative attack patterns is constructed, which is the objective to be minimized. Thirdly, considering that the deployment scheme is long-term stable while the operating mode varies with time, we construct a multiobjective nonlinear stochastic programming to mitigate the average risk of operating modes. Then the optimization problem is solved by the multiobjective genetic algorithm. Lastly, results of the IEEE 39-node CPPS and and the Virtual European Grid demonstrate that the proposed method can considerably reduce the attack risk. [ABSTRACT FROM AUTHOR]

IPC (Inter-Process Communication) is a widely used operating system (OS) technique that allows one process to invoke the services of other processes. The IPC participants may share the same OS (internal IPC) or use a separate OS (external IPC). Even though a long line of researches has optimized the performance of IPC, it is still a major factor of the run-time overhead of IPC-intensive applications. Furthermore, there is no one-size-fits-all solution for both internal and external IPC. This paper presents SkyBridge, a general communication technique designed and optimized for both types of IPC. SkyBridge requires no involvement of the privileged software (the kernel or the hypervisor) and enables a process to directly switch to the virtual address space of the target process, regardless of whether they are running on the same OS or not. We have implemented SkyBridge on two microkernels (seL4 and Google Zircon) as well as an open-source serverless hypervisor (Firecracker). The evaluation results show that SkyBridge improves the latency of internal IPC and external IPC by up to 19.6x and 1265.7x, respectively. [ABSTRACT FROM AUTHOR]

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. We hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences. [ABSTRACT FROM AUTHOR]

This paper makes the first effort on proposing a fog computing empowered architecture together with a dedicated scheduling algorithm for data dissemination in software defined heterogeneous vehicular ad-hoc networks (VANETs). Specifically, the architecture supports both the logically centralized control via the cloud node in the core network and the distributed data dissemination via the fog nodes at the network edge. A problem called fog assisted cooperative service (FACS) is formulated, which takes network coding and vehicular caching into consideration, and aims at minimizing the overall service delay via the cooperation of vehicle-to-cloud (V2C), vehicle-to-fog (V2F) and vehicle-to-vehicle (V2V) communications. Further, we derive an equivalence problem of FACS and prove that FACS is NP-hard. On this basis, we propose a Clique Searching based Scheduling (CSS) algorithm at the SDN controller, which considers the heterogeneous communication interfaces and vehicle mobility in scheduling, and enables the collaborative data encoding and transmission among the cloud, fog nodes and vehicles. The complexity analysis demonstrates the feasibility of the proposed algorithm. Finally, we build the simulation model and give a comprehensive performance evaluation based on real vehicular trajectories extracted from different time and space. The simulation results conclusively demonstrate the superiority of the proposed solution. [ABSTRACT FROM AUTHOR]

A steady increase in available processing power continues to drive advances in video compression technology. The recently completed Versatile Video Coding (VVC) standard aims to double the compression efficiency of HEVC and deliver a same quality of video at half the bitrate. To achieve this goal, VVC includes several new methods that improve coding efficiency at the cost of increased complexity. This paper provides a complexity analysis of VVC and its VTM reference software. Whereas VVC is more complex than HEVC, it remains readily implementable in software on current generation processors. Performance of practical decoders are reported, showing that real-time decoding of 8K content is feasible. An encoder is also presented, showing that most of the compression gains of VVC over HEVC can be obtained at a small fraction of the resources needed by the VTM encoder under common test conditions. [ABSTRACT FROM AUTHOR]

Benchmarking provides an essential ground base for adequately assessing and comparing evolutionary computation methods and other optimization algorithms. It allows us to gain insights into strengths and weaknesses of different existing techniques, and consequently design more efficient optimization approaches. The need for good benchmarking practices opens up a broad range of complementary research questions, arising as a byproduct of challenges encountered when optimization methods are assessed. From the selection of representative benchmark problem instances, different algorithms, and suitable performance metrics, over efficient experimentation, to a sound evaluation of the benchmark data, these research questions lie at the core of establishing a well-designed and standardized benchmarking procedure. [ABSTRACT FROM AUTHOR]

The Nordic e-Infrastructure Collaboration on Earth System Modeling Tools is a small community comprising members with diverse backgrounds, skills, and interests. Largely dependent on temporary staff to develop, operate, and maintain large scientific codes, this community devised strategies to enhance software reusability and sustainability. These strategies include collaborating with other communities for support, adopting Open Science as well as findable, accessible, interoperable, and reusable principles to optimize resource usage, growing essential knowledge within the community, and setting up a community of practice to facilitate onboarding and offboarding. The strategies also promote inclusiveness, foster external collaboration, and recognize technical contributions. [ABSTRACT FROM AUTHOR]

The first approaches to conceptualizing software ecosystems (SECO) appeared more than 15 years ago, and few studies have addressed proprietary SECO. In a proprietary SECO, organizations are concerned with keeping their assets protected by intellectual property. We first report on a longitudinal literature study to understand how the governance mechanisms work and organizations handle incidents in SECOs, updating a previous systematic literature review covering from 2006 to 2015 with new studies from 2016 to 2020. Next, we investigated the governance mechanisms in a proprietary SECO of a large international organization through a participative case study. Moreover, we gathered information on governance in practice and defined strategies to implement governance mechanisms measured by health metrics, as follows: 1) observation: analyzing the behavior of the participants in the face of problematic situations; 2) interviews: collecting participants’ information on the adoption of governance mechanisms; and 3) opinion survey: verifying the level of participants’ perception about the new strategies related to proprietary SECO governance mechanisms. Based on the results, we derived practical implications and contributions to provide a research agenda for academics and practitioners, such as workforce capacity planning in order to gain a competitive advantage in the market. [ABSTRACT FROM AUTHOR]

As software products increasingly become part of larger ecosystems, research and development (R&D) units of software producers organize themselves around projects to become more responsive to the environment. Organizations participating in software ecosystems must continuously adapt and adjust their software development and maintenance processes to drive both medium-term and long-term innovation. Agile methods and practices are widely adopted to guide the collaboration within and between project teams in software development. Moreover, when successfully attained, agility can drive innovation by enabling software development organizations to cope with technological changes and exploit emerging opportunities in software ecosystems. In this article, we focus on how organizations attain agility in the maintenance and development of software products. To answer this question, we conduct a longitudinal case study of Agile Scrum implementation in the R&D unit of a major supplier of telecommunication equipment. We investigate the emerging tensions and highlight practices used to balance these tensions in the Agile Scrum implementation. We identify four capabilities and ten practices that support effective collaboration and coordination in the development and maintenance of software products. The study offers practical guidance for R&D managers to attain agility in software ecosystems. [ABSTRACT FROM AUTHOR]

Firm survival in dynamic software markets depends on collaboration with ecosystem complementors and exploitative and/or explorative innovation. Such activities have been widely accepted as crucial antecedents for collaboration success, but few studies have analyzed the configurational effects of collaborative modes effect on firm performance. Based on a sample of 224 software firms and fuzzy set qualitative comparative analysis, results show that four causal configurations equivalently explain high innovation performance, in which exploitation, exploration, and collaboration with academic and governmental institutes are proven to be core causal conditions. Theoretically, this article contributes to the literature on collaborative innovation in terms of causality research and collaborative pathways but also enriches the literature on software ecosystems regarding partnerships and collaborative processes. Practical guidance and flexible choices for software firms to achieve high innovation performance are provided by offering four equivalent configurations. [ABSTRACT FROM AUTHOR]

The IEEE Computer Society's lineup of 12 peer-reviewed technical magazines covers cutting-edge topics ranging from software design and computer graphics to Internet computing and security, from scientific applications and machine intelligence to visualization and microchip design. Here are highlights from recent issues. [ABSTRACT FROM AUTHOR]

Software plays a central role in scientific discovery. Improving how we develop and use software for research can have both broad and deep impacts on a spectrum of challenges and opportunities society faces today. The emergence of the research software engineer (RSE) role correlates with the growing complexity of scientific challenges and the diversity of software team skills. In this article, research software science (RSS), an idea related to RSE and particularly suited to research software teams, is described. RSS promotes the use of scientific methodologies to explore and establish broadly applicable knowledge. Using RSS, we can pursue sustainable, repeatable, and reproducible software improvements that positively impact research software toward improved scientific discovery. [ABSTRACT FROM AUTHOR]

Ethereum is the single largest programmable blockchain platform today. Ethereum nodes operate the blockchain, relying on a vast supply chain of third-party software dependencies. In this article, we perform an analysis of the software supply chain of Java Ethereum nodes and distill the challenges of maintaining and securing this blockchain technology. [ABSTRACT FROM AUTHOR]

More program functions are no longer written in code but learned from a huge number of data samples using a machine learning (ML) algorithm. We present an overview of current techniques to manage complex software and discuss how this applies to ML models. [ABSTRACT FROM AUTHOR]

Software defect prediction aims to predict defect-prone code regions automatically before defects are discovered. Accurate prediction helps software practitioners to prioritize their testing efforts. In recent decades, dozens of approaches have been put forward and acquired good results in this field. However, in practical scenarios, many projects have limited labeled instances; more than that, most of these labeled instances are nondefective. The lack of training data and class imbalance problem together bring serious challenges to software defect prediction tasks. So far, few of prevailing approaches can well handle these two difficulties simultaneously. One important reason is that they do not pay adequate attention to several key instances, which are difficult to classify in a small imbalanced dataset. This article introduces the concept of “instance hardness” to integrate various difficulties of imbalance classification tasks. Based on it, a novel imbalance learning framework named self-paced ensemble of ensembles (SPE $^{2}$) is proposed to perform software defect prediction. SPE $^{2}$ aims to generate a strong ensemble of ensembles by self-paced harmonizing instance hardness via undersampling. Finally, SPE $^{2}$ is extensively compared with eight imbalance learning approaches on ten open-source defect datasets. Experiments indicate that SPE $^{2}$ improves the performance and achieves better and more significant F-measure values than its existing counterparts, based on Brunner’s statistical significance test and Cliff’s effect sizes. [ABSTRACT FROM AUTHOR]

Software fault prediction models help the software quality assurance team to manage the resources optimally during software maintenance. Most of the recently proposed fault prediction approaches are helpful on labeled datasets only. Recently, several threshold-based software fault prediction approaches have been proposed. However, these approaches do not incorporate the distribution of software metrics for metric threshold derivation; hence, they demonstrate poor performance. To fill this gap, we develop an automated fault prediction approach, namely threshold clustering labeling/threshold clustering labeling plus (TCLP), which does not need a labeled dataset. It can identify the faulty and nonfaulty artifacts on unlabeled datasets by self-learning. Our proposed approach is an extension of the state-of-the-art technique known as CLAMI. Unlike CLAMI, we derive the metrics threshold using logarithmic transformation. Thereafter, we label the instances into binary classes (faulty/nonfaulty) using the metric threshold values. TCLP extends this approach one step further by performing fault prediction using a random forest algorithm. The empirical evaluation of the proposed approach on 28 datasets (with the different number of metrics and granularity) collected from five software groups shows that the proposed unsupervised method obtains significantly better results than those of the state-of-the-art methods. The proposed approach impressively enhances the performance of CLAMI in terms of accuracy, F-measure, and Mathew’s correlation coefficient. [ABSTRACT FROM AUTHOR]

We explore what potentially may happen to software by 2033, taking views from across the industry. Our central premise is that, by increasing problem-domain expressiveness, more real-world experiences can be captured and converted into digital simulators, which can form shareable models of knowledge. [ABSTRACT FROM AUTHOR]

The IEEE Computer Society's lineup of 12 peer-reviewed technical magazines covers cutting-edge topics ranging from software design and computer graphics to Internet computing and security, from scientific applications and machine intelligence to visualization and microchip design. Here are highlights from recent issues. [ABSTRACT FROM AUTHOR]

The IEEE Computer Society's lineup of 12 peer-reviewed technical magazines covers cutting-edge topics ranging from software design and computer graphics to Internet computing and security, from scientific applications and machine intelligence to visualization and microchip design. Here are highlights from recent issues. [ABSTRACT FROM AUTHOR]

Each January issue of Computer is devoted to invited articles offering forward-looking ideas. This 2022 issue discusses artificial intelligence hardware concerns, the future of software, the current state of open banking, future obstacles in deploying autonomous machines, ethical dimensions of social media, and a 200-year look back at the invention and contribution made by Charles Babbage. [ABSTRACT FROM AUTHOR]

The IEEE Computer Society's lineup of 12 peer-reviewed technical magazines covers cutting-edge topics ranging from software design and computer graphics to Internet computing and security, from scientific applications and machine intelligence to visualization and microchip design. Here are highlights from recent issues. [ABSTRACT FROM AUTHOR]

The broad scope of the IEEE Communications Magazine Series on Network Softwarization and Management covers two aspects of communication networks that have become highly relevant nowadays. On one hand, network softwarization advocates for architectures where software and programmability aspects in the implementation of network functions, protocols, and services are decoupled from the underlying infrastructure, fostering unprecedented levels of flexibility, abstraction, automation, and intelligence. On the other hand, network management aims at integrating fault, configuration, accounting, performance, and security (FCAPS) capabilities in the network, and supporting advanced autonomic and self-management features, often taking advantage of the potential offered by network softwarization. The intent of this Series is to provide a timely source of in-depth, cutting-edge articles on state-of-the-art technologies and solutions for network softwarization and management. [ABSTRACT FROM AUTHOR]

The 2021 VGTC Visualization Dissertation Award goes to Arjun Srinivasan. Arjun Srinivasan is a member of the Senior Research Staff at Tableau Software in Seattle. He received his Ph.D. from the Georgia Institute of Technology under the supervision of Regents Professor John Stasko. His dissertation bridges the fields of Information Visualization, Human-Computer Interaction, and Natural Language Processing to illustrate the potential of visualization interfaces combining natural language (NL) and direct manipulation (DM) for fluid and expressive human-data interaction experiences. [ABSTRACT FROM AUTHOR]