Deployment Cycle Research Articles

Increasing software deployment speed in agile environments through automated configuration management

In today's fast-paced software development landscape, the ability to deploy applications rapidly while maintaining high quality is crucial for Agile teams. This paper explores the impact of Automated Configuration Management (ACM) on enhancing software deployment speed within Agile environments. By examining the complexities of modern software systems and the challenges associated with manual configuration processes, the study underscores the necessity of automation to streamline workflows and reduce errors. Key ACM tools such as Ansible, Puppet, and Chef are discussed and their role in facilitating efficient configuration management. The integration of ACM with Continuous Integration (CI) and Continuous Deployment (CD) practices is highlighted as a pivotal strategy for achieving faster deployment cycles and improved software reliability. Additionally, the paper emphasizes the importance of fostering a DevOps culture, where collaboration between development and operations teams enhances the overall efficiency of the software delivery pipeline. Ultimately, the findings present a roadmap for Agile teams seeking to implement automated solutions, offering practical recommendations to optimize their deployment processes and adapt to the evolving demands of the market.

Orchestration Workflows in Distributed Systems: A Systematic Analysis of Efficiency Optimization and Service Coordination

This article presents a comprehensive analysis of orchestration workflows in modern software architectures, examining their role in optimizing service efficiency and coordination across distributed systems. Through a systematic investigation of implementation patterns and operational strategies, we demonstrate how orchestrated workflows enhance service integration, automate complex processes, and improve system reliability. The article employs a mixed-method approach, combining quantitative performance metrics from real-world implementations with qualitative analysis of architectural patterns across diverse enterprise environments. The findings reveal that organizations implementing robust orchestration workflows experienced a 47% reduction in service integration failures, 35% improvement in resource utilization, and 62% faster deployment cycles. The article also identifies critical success factors in orchestration implementation, including dynamic resource management, automated error handling, and comprehensive monitoring frameworks. Furthermore, The article proposes a novel framework for evaluating orchestration effectiveness in cloud-native environments, considering factors such as service mesh integration, container orchestration, and distributed tracing. This article contributes to the growing body of knowledge in service optimization by providing empirical evidence of orchestration benefits and offering practical guidelines for implementing scalable, resilient software systems through advanced workflow orchestration strategies.

Continuous Integration and Continuous Deployment (CI/CD) Optimization

The advent of Continuous Integration and Continuous Deployment (CI/CD) has fundamentally altered the landscape of software development, enabling teams to deliver updates with unprecedented speed and reliability. By automating the integration of code changes from multiple developers into a central repository, CI/CD practices ensure that software is continuously tested and deployed. This ongoing cycle not only facilitates quicker release cycles but also enhances collaboration among team members and fosters a culture of shared responsibility for code quality. Despite these advancements, organizations face significant challenges in optimizing their CI/CD pipelines. As software systems grow in complexity, the demand for swift and dependable deployments intensifies. This paper explores various techniques and strategies for optimizing CI/CD processes to minimize deployment times while maintaining system reliability. Key optimization methods discussed include: Parallelization of Build Processes: This technique involves breaking down the build process into smaller, independent tasks that can be executed concurrently. By leveraging distributed computing resources, organizations can significantly reduce build times, allowing for faster iterations and deployments. Dependency Caching: Caching dependencies can drastically decrease build times by reusing previously downloaded components. This approach not only speeds up the build process but also minimizes network load and enhances the overall efficiency of the CI/CD pipeline. Incremental Builds: Unlike full builds that compile the entire codebase, incremental builds focus on compiling only the changes made since the last build. This strategy reduces the amount of work needed for each build, accelerating the overall development process. The paper also delves into advanced rollback mechanisms such as blue-green deployments and canary releases. Blue-green deployments allow teams to maintain two identical production environments, enabling smooth transitions and quick rollbacks in case of issues. Canary deployments, on the other hand, introduce new features to a small subset of users before a full rollout, allowing teams to monitor the impact and catch potential failures early. Additionally, automated rollback mechanisms play a vital role in maintaining system reliability, ensuring that any failed deployments can be reverted swiftly to avoid downtime and user disruption. The impact of automation tools on deployment speed and error reduction is another critical aspect examined in this research. Automation frameworks can streamline various stages of the CI/CD process, from code integration to testing and deployment, minimizing human error and ensuring consistent, repeatable processes. By implementing robust automation strategies, organizations can not only accelerate their deployment cycles but also improve overall software quality.

Military Family-Centred Resilience-Building Programming Across the Deployment Cycle: A Scoping Review.

Background: There is international agreement that military families (MFs)-active service members, reservists, veterans, and their families-must be resilient to overcome military life adversities. Resilience is defined either as skillsets or as processes implicating multi-systems in a socio-ecological context. While research on resilience-building specific to children and families who face adversity is growing, there is a paucity of evidence on MF-centred resilience-building. Objective: This review describes the evidence on such resilience-building programming and determines if adversity is considered a barrier or facilitator to resilience-building. Methods: This scoping review yielded 4050 peer-reviewed articles from database inception until December 2023, found in 12 databases. Articles were deduplicated, leaving 1317 that were independently screened for eligibility by two reviewers. Disagreements were resolved through discussion with a third reviewer. Findings: Of these articles, 27 were included; 5 additional articles were also included from other sources. The vast majority of included studies (91%) were conducted in the United States. These 32 articles were organised into categories, including demographics, research methodologies used, resilience program descriptors, and outcomes. Conclusions: Our results reveal that programs on building MF resilience vary widely, often measuring non-resilience health and social outcomes. We provide preliminary insights for MF health and policy. Our review findings will be invaluable for further evidence-based programming that builds resilience in MFs.

Ensuring Security and Compliance in Agile Cloud Infrastructure Projects

Purpose: This research paper investigates strategies for ensuring security and compliance in agile cloud infrastructure projects. Methodology: The study synthesizes current literature, industry reports, and expert insights to provide a comprehensive overview of the topic. Findings: Key challenges identified include rapid deployment cycles, shared responsibility models, and data sovereignty concerns. The research proposes strategies such as shift-left security approaches, continuous compliance monitoring, and automated security testing. The importance of organizational culture shifts and the evolving role of cloud service providers in shared security responsibilities are highlighted. Unique Contribution to Theory, Policy and Practice: The paper offers recommendations for practitioners navigating the complex landscape of security and compliance in agile cloud projects. It provides insights into integrating security and compliance into agile methodologies, leveraging cloud-native security tools, and the potential impact of AI and machine learning on cloud security.

Unlocking Interactive Learning: Building a Robust Quiz Portal with MERN Stack Technology"

Online learning has become increasingly popular in the digital era, necessitating innovative platforms to effectively engage students. This research outlines the development and implementation of an interactive quiz portal utilizing the MERN (MongoDB, Express.js, React.js, and Node.js) stack to enhance learning outcomes. The portal features a user-friendly interface for easy navigation and access to a diverse range of quizzes on various subjects. To ensure scalability, performance, and real-time interactions, Node.js handles backend operations, React.js manages dynamic interfaces, Express.js is used for server-side development, and MongoDB stores data. The portal includes instant feedback mechanisms, gamification elements, and personalized user profiles to enhance user motivation and involvement. Furthermore, adaptive algorithms are employed to adjust quiz content based on user proficiency levels. This paper presents the design, development, and implementation of an online test platform using the MERN (MongoDB, Express, React, and Node.js) stack. The portal functions as an all-inclusive platform for administering tests, assessments, and learning evaluations in an online setting. The portal provides smooth integration of frontend and backend activities, guaranteeing strong performance and user interaction, by utilizing the adaptability and scalability of the MERN stack. The portal enables quick development and deployment cycles with the help of MongoDB's document-based data storage, Express.js's effective middleware and routing, React.js's dynamic UI components, and Node.js's event-driven architecture. To improve user experience and learning results, features including interactive feedback mechanisms, real-time performance monitoring, quiz design and administration, and user authentication are easily integrated.

Virtual Simulation Design and Debugging of Lift-and-Transverse Stereo Garage Based on the Digital Twin

In the face of the challenges of limited urban space and the continuous increase of vehicles, stereo garages have been widely used as a solution in cities. In order to improve the automation and intelligence level of the stereo garage, this paper applies the digital twin technology to the lift-and-transverse stereo garage. A five-dimensional model of a digital twin has been developed based on an actual stereo garage. Combined with S7-PLCSIM Advanced, Botu TIA Portal, and NX MCD to build a virtual simulation platform, realizing the virtual simulation design and debugging of the digital twin-based stereo garage. This approach allows to test and optimize operational processes without relying on physical equipment, reducing labor and field debugging costs, shortening deployment cycles, and significantly reducing development costs. In addition, MCD allows real-time monitoring and control of security risks and failures detected. Finally, the feasibility of the virtual simulation and debugging scheme based on digital twin is verified by comparing the operation data of the virtual model and the actual stereo garage, which provides new ideas for the intelligent development of stereo garage but also can be used as an important reference for the development of equipment in other areas.

Hydro-sedimentological drivers of fine sediment ingress in a gravel-bed river

Most studies investigating fine sediment ingress in gravel-bed rivers have been conducted at the laboratory scale, and even fewer have explored the ingress processes of flocculated particles. Here, an extensive in-situ sampling programme was undertaken to investigate hydro-sedimentological drivers of interstitial fine sediment accumulation and to evaluate fine sediment ingress directional mechanisms in a gravel-bed river located on the eastern slopes of the Rocky Mountains in southern Alberta. Three sediment trap designs were installed across seven deployment cycles at four sites along the river. Instantaneous discharge, suspended solids concentration, and particle size distributions (of suspended and ingressed particles) were measured, while relevant hydraulic parameters were modelled with a flow model (MOBED). Distinct patterns of ingress dynamics between non-cohesive and cohesive fractions of fine sediment were observed. While the assessed hydro-sedimentological parameters did not statistically explain the ingress rates of non-cohesive 0.5 – 2 mm particles, the opposite was observed for < 0.5 mm particles, which were mostly transported in flocculated form. For flocculated sediment, horizontal ingress accounted for ∼ 60 % of interstitial accumulation. Directional ingress mechanisms, however, were dependent on flow conditions for both particle size fractions, with vertical and horizontal accumulations becoming more important during higher and lower energy flows, respectively. Our observations demonstrate the importance of ingress for the interstitial accumulation of fine sediment, even during events with flow above the critical threshold conditions for fine sediment gravitational deposition. Despite the comparable ingress rates to other studies, no interstitial clogging was observed in this study, demonstrating the channel potential storage capacity, which has implications for legacy impacts from landscape disturbances in the Crowsnest River catchment.

Codevelopment and Deployment of a System for the Telemonitoring of Activities of Daily Living Among Older Adults Receiving Home Care Services: Protocol for an Action Design Research Study.

Telemonitoring of activities of daily living (ADLs) offers significant potential for gaining a deeper insight into the home care needs of older adults experiencing cognitive decline, particularly those living alone. In 2016, our team and a health care institution in Montreal, Quebec, Canada, sought to test this technology to enhance the support provided by home care clinical teams for older adults residing alone and facing cognitive deficits. The Support for Seniors' Autonomy program (SAPA [Soutien à l'autonomie des personnes âgées]) project was initiated within this context, embracing an innovative research approach that combines action research and design science. This paper presents the research protocol for the SAPA project, with the aim of facilitating the replication of similar initiatives in the future. The primary objectives of the SAPA project were to (1) codevelop an ADL telemonitoring system aligned with the requirements of key stakeholders, (2) deploy the system in a real clinical environment to identify specific use cases, and (3) identify factors conducive to its sustained use in a real-world setting. Given the context of the SAPA project, the adoption of an action design research (ADR) approach was deemed crucial. ADR is a framework for crafting practical solutions to intricate problems encountered in a specific organizational context. This project consisted of 2 cycles of development (alpha and beta) that involved cyclical repetitions of stages 2 and 3 to develop a telemonitoring system for ADLs. Stakeholders, such as health care managers, clinicians, older adults, and their families, were included in each codevelopment cycle. Qualitative and quantitative data were collected throughout this project. The first iterative cycle, the alpha cycle, took place from early 2016 to mid 2018. The first prototype of an ADL telemonitoring system was deployed in the homes of 4 individuals receiving home care services through a public health institution. The prototype was used to collect data about care recipients' ADL routines. Clinicians used the data to support their home care intervention plan, and the results are presented here. The prototype was successfully deployed and perceived as useful, although obstacles were encountered. Similarly, a second codevelopment cycle (beta cycle) took place in 3 public health institutions from late 2018 to late 2022. The telemonitoring system was installed in 31 care recipients' homes, and detailed results will be presented in future papers. To our knowledge, this is the first reported ADR project in ADL telemonitoring research that includes 2 iterative cycles of codevelopment and deployment embedded in the real-world clinical settings of a public health system. We discuss the artifacts, generalization of learning, and dissemination generated by this protocol in the hope of providing a concrete and replicable example of research partnerships in the field of digital health in cognitive aging. RR1-10.2196/52284.

Canadian Armed Forces Veterans' Perspectives on the Effects of Exposure to Children in Armed Conflict During Military Service: Protocol for a Qualitative Study.

The mental health of military personnel has garnered increased attention over the last few decades; however, the impacts of perpetuating, observing, or failing to prevent acts that transgress deeply held moral standards, referred to as moral injuries, are less understood, particularly in relation to encounters with children during deployment. This paper describes a multiphased research protocol that centers around the lived experiences of Canadian Armed Forces (CAF) Veterans to understand how encounters with children during military deployments impact the well-being and mental health of military personnel. This study has four objectives: (1) highlight the lived experiences of CAF Veterans who encountered children during military deployments; (2) improve understanding of the nature of experiences that military personnel faced that related to observing or engaging with children during military service; (3) improve understanding of the mental health impacts of encountering children during military service; and (4) use participatory action research (PAR) to develop recommendations for improving preparation, training, and support for military personnel deployed to contexts where encounters with children are likely. The research project has 2 main phases where phase 1 includes qualitative interviews with CAF Veterans who encountered children during military deployments and phase 2 uses PAR to actively engage Canadian Veterans with lived experiences of encountering children during military deployments, as well as health professionals and researchers to identify recommendations to better address the mental health effects of these encounters. As of January 26, 2024, a total of 55 participants and research partners have participated in the 2 phases of the research project. A total of 16 CAF Veterans participated in phase 1 (qualitative interviews), and 39 CAF Veterans, health professionals, and researchers participated in phase 2 (PAR). The results for phase 1 have been finalized and are accepted for publication. Data collection and analysis are ongoing for phase 2. Prioritizing and valuing the experiences of CAF Veterans has deepened our understanding of the intricate nature and impacts of potentially morally injurious events involving children during military deployments. Together with health professionals and researchers, the PAR approach empowers CAF Veterans to articulate important recommendations for developing and improving training and mental health support. This support is crucial not only during the deployment cycle but also throughout the military career, helping lessen the effects of moral injury among military personnel. DERR1-10.2196/57146.

Analysis Of DevOps Infrastructure Methodology and Functionality of Build Pipelines

The DevOps pipeline for infrastructure is a critical component in modern software development and operations practices. It involves automating the provisioning, configuration, and management of infrastructure resources, enabling organizations to achieve agility, scalability, and reliability. This paper presents a plagiarism-free analysis of the DevOps pipeline for infrastructure, conducted through comprehensive research, evaluation of industry best practices, and examination of case studies. The DevOps methodology would collapse without the use of a DevOps pipeline. The phrase is often used to discussions of the methods, procedures, and automation frameworks that go into the creation of software objects. Jenkins, an open-source Java program, is the most well-known DevOps pipeline and is often credited as the catalyst for the whole DevOps movement. Today, we have access to a plethora of DevOps pipeline technologies, such as Travis CI, GitHub Actions, and Argo. To keep up with the need for new and improved software systems, today's development organizations must overcome a number of obstacles. The research highlights key findings, including the importance of automation, infrastructure as code, continuous integration and delivery, security, and monitoring/logging capabilities. These practices have been shown to enhance efficiency, reduce errors, and accelerate deployment cycles. By evaluating tools and technologies, gathering user feedback, and analyzing performance metrics, organizations can identify gaps and develop a roadmap for pipeline improvement. To maintain academic integrity, this analysis adheres to proper citation and referencing practices. Paraphrasing and summarizing research findings and adding personal analysis and interpretations ensure the originality and authenticity of the analysis. Plagiarism detection tools are used to confirm the absence of unintentional similarities with existing content.

A Maturity Level Framework for Practicing Machine Learning Operations in CI/CD For Software Deployment

Significantly shorter software development and deployment cycles have been made possible by the adoption of continuous software engineering techniques in business operations, such as DevOps (Development and Operations). Data scientists and operations teams have recently become more and more interested in a practice known as MLO (Machine Learning Operations). However, MLO adoption in practice is still in its early stages, and there aren't many established best practices for integrating it into current software development methods. In order to give a frame that outlines the way necessary in espousing MLO and the stages through which business capes process as they come riper and sophisticated, we achieve a methodical literature study as well as a slate review of literature in this composition. We test this approach in three example businesses and demonstrate how they were able to embrace and incorporate MLO into their massive software development businesses. This study offers three contributions. To give an overview of the state of the art in MLO, we first examine recent publications. Based on this analysis, we create an MLO framework that outlines the steps taken in the ongoing creation of machine learning models. Second, we define the several stages that businesses go through as they develop their MLO practices in a maturity model. Third, we map the firms to the maturity model phases and test our methodology using three embedded systems case companies. The main objective is to create an MLO framework.

Multi-Layer Digital Services Increase Developers’ Requirements to Agriculture IoT Platforms

Highlights Digital ecosystems in agriculture enable a new class of digital services that span over several layers of the IoT stack. This work defines digital ecosystems in agriculture based on IoT layers and utilized technologies. An example for a multi-layer digital service is developed, deployed, and tested using the NEVONEX Ecosystem. Surveys reveal software providers require more platform functionalities and early iteration testing on real farms. Abstract. In recent years, digital platforms in agriculture went through a phase of acquisitions and consolidation, where big players like agrochemical companies (Agrichems) and agricultural equipment manufacturers (OEMs) worked on expanding their technology stacks to build strategic portfolios of digital service offerings. To operate farm equipment efficiently, a combination of platforms and technologies is often needed, leading to the emergence of digital Agri-ecosystems. With the rising implementation of IoT technology, digital Agri-ecosystems enable multi-layer digital services and break down established categories (cloud-based and embedded). Content providers and developers creating those digital services face three options: aggregated cloud APIs (application programming interfaces), engineering service providers with proprietary technology stacks, and dedicated IoT ecosystems offering agnostic end-to-end workflows for development and deployment (first known example: NEVONEX). It is not yet fully understood how using an end-to-end IoT ecosystem changes developer requirements in comparison to existing solutions. Therefore, in this study, an example of a multi-layer digital service is developed and tested. Expert interviews (n = 21) explore relevant developer experiences and requirements. A consecutive survey (n = 30; NEVONEX developer conference) validates the findings. Results show that IoT- ecosystems speed up development and deployment cycles, save resources, and improve interoperability in operations. Engineering service providers remain very important players. Partner management, communication, abstraction of interfaces, testing infrastructure, and early end-user input are required by developers. In conclusion, IoT- ecosystems are beneficial for multi-layer digital service development; however, to fully satisfy developers and content providers, adjustments to platform functionalities and better testing opportunities on real farms are needed. Keywords: Automation, Digital Ecosystem, Farm equipment, NEVONEX

DSE-Based Hardware Trojan Attack for Neural Network Accelerators on FPGAs.

Over the past few years, the emergence and development of design space exploration (DSE) have shortened the deployment cycle of deep neural networks (DNNs). As a result, with these open-sourced DSE, we can automatically compute the optimal configuration and generate the corresponding accelerator intellectual properties (IPs) from the pretrained neural network models and hardware constraints. However, to date, the security of DSE has received little attention. Therefore, we explore this issue from an adversarial perspective and propose an automated hardware Trojan (HT) generation framework embedded within DSE. The framework uses an evolutionary algorithm (EA) to analyze user-input data to automatically generate the attack code before placing it in the final output accelerator IPs. The proposed HT is sufficiently stealthy and suitable for both single and multifield-programmable gate array (FPGA) designs. It can also implement controlled accuracy degradation attacks and specified category attacks. We conducted experiments on LeNet, VGG-16, and YOLO, respectively, and found that for the LeNet model trained on the CIFAR-10 dataset, attacking only one kernel resulted in 97.3% of images being classified in the category specified by the adversary and reduced accuracy by 59.58%. Moreover, for the VGG-16 model trained on the ImageNet dataset, attacking eight kernels can cause up to 96.53% of the images to be classified into the category specified by the adversary and causes the model's accuracy to decrease to 2.5%. Finally, for the YOLO model trained on the PASCAL VOC dataset, attacking with eight kernels can cause the model to identify the target as the specified category and cause slight perturbations to the bounding boxes. Compared to the un-compromised designs, the look-up tables (LUTs) overhead of the proposed HT design does not exceed 0.6%.

Evaluating the Practical Viability of Aluminum-Air Batteries in Real-World Applications

The growing global population and petroleum use are contributing factors to serious environmental issues like climate change. Reducing dependency on petroleum can be achieved, for example, by producing big-capacity batteries that can be used in electrical applications. Because aluminum-air batteries have a theoretical energy density of 8.1 kWh kg1 , which is far higher than that of present lithium-ion batteries, they are considered promising for use in next-generation energy storage applications. An aluminum-air battery, which is a promising form of energy storage, uses aluminum as the anode and ambient air as the cathode. This abstract emphasizes the key characteristics of aluminum-air batteries while highlighting their potential advantages, challenges, and applications. These batteries appeal to a range of enterprises due to their high energy density, lightweight, and environmental friendliness. However, there are issues that need to be resolved, such as impediments to real-world deployment and short cycle times. Research to improve the performance and economic viability of aluminum-air batteries is underway, with a focus on uses in electric vehicles, portable gadgets, and renewable energy systems. This abstract provides a concise overview of this revolutionary energy storage technology with insights into its current state and potential. Key Words: Aluminum, Graphite, Non-toxic, Sodium Hydroxide, Eco- friendly, non-rechargeable.

Designing Secure and Robust E-Commerce Plaform for Public Cloud

&#x0D; &#x0D; &#x0D; &#x0D; The migration of e-commerce platforms to the public cloud has become a pivotal strategy for businesses seeking enhanced scalability, performance, and cost-efficiency. This paper explores the multifaceted design considerations critical to deploying robust e-commerce systems within the public cloud infrastructure. It delves into scalability, ensuring that platforms can handle varying loads with elasticity and grace. Security is examined as a paramount concern, addressing the need for stringent data protection, compliance with industry standards, and the implementation of best practices such as encryption and identity access management. Performance optimization is discussed, with a focus on leveraging content delivery networks and optimizing database operations to ensure swift customer experiences. The paper also covers reliability and availability, emphasizing the necessity of multi-regional deployment and sophisticated disaster recovery plans to guarantee uninterrupted service. Cost management is analyzed, highlighting the importance of understanding cloud pricing models and employing cost-effective resource utilization strategies. Data management is scrutinized, considering secure storage, privacy, and efficient data handling. User experience is identified as a critical component, with personalization and session management being key to customer satisfaction. The role of DevOps and automation in achieving efficient deployment cycles through continuous integration and delivery is outlined. The benefits of a microservices architecture are presented, along with the challenges of managing such distributed systems. Multi-tenancy and isolation are discussed in the context of security and resource optimization. Integration and APIs are explored for their role in facilitating extensibility and seamless third-party service incorporation. Compliance and legal considerations are addressed, underscoring the importance of data sovereignty and regular audits. Lastly, the paper touches on the incorporation of emerging technologies such as AI, ML, and IoT to stay at the forefront of innovation, and concludes with a discussion on environmental considerations for sustainable cloud practices. This comprehensive analysis provides a roadmap for businesses to navigate the complexities of cloud-based e-commerce, ensuring robust, secure, and efficient online retail operations.&#x0D; &#x0D; &#x0D; &#x0D;

Systematic Improvements to the Army's Deployment Cycle Resilience Training Using a Comprehensive, Iterative Process.

To support soldier readiness and mitigate the mental health consequences of deployments, Army regulation mandates soldiers to receive Deployment Cycle Resilience Training (DCRT) throughout their deployment cycle. A recent evaluation revealed several issues with the existing version that threatened the relevancy and usefulness of the training. The present article details the systematic approach taken by the Research Transition Office at the Walter Reed Army Institute of Research to revise the DCRT curriculum and presents the revision updates that are now included in DCRT version 3. Curriculum developers (n = 2) with subject matter expertise relevant to the project followed an iterative process that was critical to the efficacy of the revisions. Developers used the existing DCRT modules as the curriculum framework and utilized several materials to inform the revisions to include Army doctrine, data from the quality improvement evaluation conducted by the Walter Reed Army Institute of Research, and the current research related to the deployment cycle, resilience, and behavior change. Internal and external stakeholders (n = 31) provided iterative feedback to ensure each of the six modules met DCRT revision objectives. The revised DCRT curriculum was implemented in August 2021. The resulting revisions included an increase in inclusivity, an emphasis on growth opportunities, an integrative approach to the deployment cycle phases, and greater practical application. Additionally, the curriculum incorporates best practices found to enhance the delivery of resilience-based psychoeducational interventions, specifically within high-risk occupational settings like the military. The revisions outlined in this article enhance the training quality and potential effectiveness of DCRT, which can positively influence soldier and family readiness and mission success. Furthermore, the deliberate and iterative curriculum revision process can serve as a guide to other curriculum development projects, specifically within the military context. Implementation considerations and potential limitations are provided, and future directions are discussed to include the ongoing evaluation.

The role of program analysis in security vulnerability detection: Then and now

Program analysis techniques play an important role in detecting security vulnerabilities. In this paper we describe our experiences in developing a variety of tools that detect security vulnerabilities in an industrial setting. The main driving forces for adoption of program analysis tools by a development organisation are low false positive rate, ease of integration in the developer's workflow, scalability to handle industrial size systems and results that are easy to understand. Even if one the above dimensions is not supported, the tool will not be used in practice.We show how the analyses of program analysis tools have changed over more than a decade due to differences in languages, e.g., code written in systems-level languages like C tend to focus on memory-related vulnerabilities, in contrast to languages like Java, JavaScript and Python where the focus is more on injection vulnerabilities in web or cloud applications. Based on language, static or dynamic analysis approaches are needed, including hybrid approaches.We conclude with our vision on Intelligent Application Security – how program analysis tools will keep changing to enable the DevSecOps model given the fertile ground that the DevOps model provides today. We foresee different program analysis tools working together by sharing information, including the results they produce, while addressing newer security issues such as those related to supply chain issues. In this way, program analysis tools would be extended with relevant machine learning techniques and be integrated in all different phases of the code development, building, testing, deployment and monitoring cycle.

Python Dash for Well Data Validation, Visualization, and Processing

Open-source Python libraries play a critical role in facilitating the digital transformation of the energy industry by enabling quick deployment of intelligent data-driven solutions. In this paper, we demonstrate an example of using Dash, a Python framework introduced by Plotly for creating interactive web applications. A fit-for-purpose software was tailored for an in-house research project in well-data validation, visualization, and processing. The application automates quality control of different sets of well-log data files (DLIS/LIS or LAS) for completeness, validity, and repeatability. For this tedious and critical process, a human expert is required to perform tasks using well-log interpretation software. A typical digital log file may contain hundreds or thousands of data channels that are difficult are difficult to visualize and validate manually. Sometimes it takes multiple iterations of communication between the data provider and the data receiver to achieve a final valid deliverable copy. By utilizing open-source Python libraries, such as DLISIO (Equinor ASA, 2022) and LASIO (Inverarity, 2023), a web interface based on Plotly-Dash is developed to visualize and check all data channels automatically and then produce a compliance summary report in PDF or HTML format. The time for validating one DLIS file that has hundreds of data channels is significantly reduced. Implementation of this automated data quality control workflow demonstrates that open-source Python libraries can significantly reduce the time from development to the deployment cycle. Quick implementation of intelligent software based on Python Plotly-Dash enables customized solutions or workflows that further improve both the effectiveness and efficiency of routine data quality control processes.

Revisit security in the era of DevOps: An evidence‐based inquiry into DevSecOps industry

AbstractBy adopting agile and lean practices, DevOps aims to achieve rapid value delivery by speeding up development and deployment cycles, which however lead to more security concerns that cannot be fully addressed by an isolated security role only in the final stage of development.DevSecOpspromotes security as a shared responsibility integrated into the DevOps process that seamlessly intertwines development, operations, and security from the start throughout to the end of cycles. While some companies have already begun to embrace this new strategy, both industry and academia are still seeking a common understanding of the DevSecOps movement. The goal of this study is to report the state‐of‐the‐practice of DevSecOps, including the impact of DevOps on security, practitioners' understanding of DevSecOps, and the practices associated with DevSecOps as well as the challenges of implementing DevSecOps. The authors used a mixed‐methods approach for this research. The authors carried out a grey literature review on DevSecOps, and surveyed the practitioners of DevSecOps in industry of China. The status quo of DevSecOps in industry is summarized. Three major software security risks are identified with DevOps, where the establishment of DevOps pipeline provides opportunities for security‐related activities. The authors classify the interpretations of DevSecOps into three core aspects of DevSecOps capabilities, cultural enablers, and technological enablers. To materialise the interpretations into daily software production activities, the recommended DevSecOps practices from three perspectives—people, process, and technology. Although a preliminary consensus is that DevSecOps is regarded as an extension of DevOps, there is a debate on whether DevSecOps is a superfluous term. While DevSecOps is attracting an increasing attention by industry, it is still in its infancy and more effort needs to be invested to promote it in both research and industry communities.