DevOps Implementation and Integration of GitHub, Jenkins, and Virtual Machines for CI/CD

Achieving comprehensive code quality and ensuring software reliability are critical goals in modern software engineering. This paper delves into advanced strategies that encompass both technical and organizational practices, aiming to enhance code quality and boost software reliability. Key strategies include the implementation of rigorous code review processes, adoption of automated testing frameworks, and the utilization of static and dynamic code analysis tools. Firstly, rigorous code review processes are fundamental for maintaining high standards of code quality. By fostering a collaborative environment where peer reviews are routine, teams can catch potential issues early, ensure adherence to coding standards, and promote knowledge sharing. This practice not only improves code quality but also enhances team cohesion and expertise. Secondly, automated testing frameworks are indispensable in achieving comprehensive test coverage and reducing the incidence of bugs. Unit tests, integration tests, and end-to-end tests, when automated, provide continuous feedback and ensure that code changes do not introduce new defects. This continuous testing approach is crucial for maintaining software reliability, especially in agile and DevOps environments where rapid iterations are common. Furthermore, the integration of static and dynamic code analysis tools into the development pipeline offers additional layers of quality assurance. Static analysis tools inspect the codebase for potential vulnerabilities, code smells, and compliance with coding standards without executing the program. Dynamic analysis tools, on the other hand, evaluate the software during runtime to detect memory leaks, concurrency issues, and performance bottlenecks. Together, these tools provide a comprehensive assessment of the code’s health and reliability. Moreover, fostering a culture of continuous improvement and learning within the development team is essential. Regular training sessions, workshops, and knowledge-sharing activities help in keeping the team updated with the latest advancements in software engineering practices and tools. Encouraging a mindset of quality-first and reliability among developers ensures long-term benefits and sustainability. In conclusion, achieving comprehensive code quality and ensuring software reliability require a multifaceted approach that integrates rigorous code reviews, automated testing frameworks, and both static and dynamic analysis tools. Coupled with a strong culture of continuous learning and improvement, these strategies collectively contribute to the development of robust, reliable, and high-quality software systems. Keywords: Software Reliability, Code Quality, Advanced, Strategies, Comprehensive.

Affinity is common among Virtual Machines (VMs) in cloud environments. If VMs collaborating on a job are split in geographically distributed clouds, the low bandwidth and high latency inter-cloud communication via a wide area network (WAN) will dramatically degrade the system performance. A potential solution is migrating all of the VMs collaborating on a job in parallel, so as to avoid wide area communication. However, if the job is too large, it becomes impractical to migrate all of the VMs simultaneously due to limited WAN bandwidth and high block dirty rate. We propose a migration optimization mechanism called Clique Migration to partition a large group of VMs into subgroups based on the traffic affinities among VMs. Then, subgroups are migrated one at a time. Based on Clique Migration, we propose and implement two algorithms called R-Min-Cut and Kmeans-SF. Analysis of the traffic trace of 68 VMs in an IBM production cluster shows that our algorithms can reduce inter-cloud traffic by 25% to 60%, when the degree of parallel migration is from 2 to 32. Tests of MPI multi-Ping Ping benchmark running on simulated inter-cloud environments, show that our algorithms can significantly shorten the period during which applications undergo performance degradation. Tests of MPI Reduce scatter benchmark show that R-Min-Cut can keep the performance during migration at 26% to 75% of the non-migration scenario.

This paper describes an efficient and robust approach to provide a safe execution environment for an entire operating system, such as Linux, and all its applications. The approach, which we call Secure Virtual Architecture (SVA), defines a virtual, low-level, typed instruction set suitable for executing all code on a system, including kernel and application code. SVA code is translated for execution by a virtual machine transparently, offline or online. SVA aims to enforce fine-grained (object level) memory safety, control-flow integrity, type safety for a subset of objects, and sound analysis. A virtual machine implementing SVA achieves these goals by using a novel approach that exploits properties of existing memory pools in the kernel and by preserving the kernel's explicit control over memory, including custom allocators and explicit deallocation. Furthermore, the safety properties can be encoded compactly as extensions to the SVA type system, allowing the (complex) safety checking compiler to be outside the trusted computing base. SVA also defines a set of OS interface operations that abstract all privileged hardware instructions, allowing the virtual machine to monitor all privileged operations and control the physical resources on a given hardware platform. We have ported the Linux kernel to SVA, treating it as a new architecture, and made only minimal code changes (less than 300 lines of code) to the machine-independent parts of the kernel and device drivers. SVA is able to prevent 4 out of 5 memory safety exploits previously reported for the Linux 2.4.22 kernel for which exploit code is available, and would prevent the fifth one simply by compiling an additional kernel library.

Model-driven development is a well-known practice in modern software engineering. A wide variety of different tools exist, which support model-driven development. Usually, these tools do not provide dedicated support for agile modeling, as they can be used with any development process. In this paper, we present an extension to our UML-based modeling tool Valkyrie which allows free-hand diagram sketching. Thus, it addresses agile modeling as whiteboards and papers can now be replaced with tablet computers or other touch-enabled (hand-held) devices.

Modern software engineering tools, technologies and approaches can radically speed up the development and engineering of multi-tier cloud applications and may be applied to the cloud/edge/fog computing paradigm. The engineering of such cloud applications must take into account Non-Functional Requirements (NFRs), such as end-user, software and cloud infrastructure requirements for low-power computing, performance, availability, elasticity, operational cost and similar. Such requirements should be identified and considered early in the software engineering process and decisions must be taken on their trade-offs, e.g. greater service availability while balancing operational costs. This paper introduces a new multi-criteria decision making approach via the use of the Pareto method to aid the software engineers with NFR trade-off adjustment possibilities. Adjustment possibilities may include geographic distribution of application tiers, horizontal and vertical scaling of virtual resources (such as Virtual Machines and containers) and similar. This work builds on top of technologies and tools developed under the SWITCH and ENTICE projects. The impact of this approach is the ability to fully tailor the adjustments of non-functional properties of the multi-tier cloud application according to the decisions of its engineer. An early warning system cloud application is used to present the approach.

Leading paradigms to develop and operate applications such as continuous delivery, configuration management, and the merge of development and operations (DevOps) are the foundation for various techniques and tools to implement automated deployment. To expose such applications as services (SaaS) to users and customers these approaches are typically used in conjunction with Cloud computing to automatically provision and manage underlying resources such as storage or virtual machines. A major class of these automation approaches follows the idea of converging toward a desired state of a resource (e.g., a middleware component deployed on a virtual machine). This is achieved by repeatedly executing idempotent scripts until the desired state is reached. Because of major drawbacks of this approach, we present an alternative deployment automation approach based on compensation and fine-grained snapshots using container virtualization. We further perform an evaluation comparing both approaches in terms of difficulties at design time and performance at runtime.

The centrally controlled beamline system for synchrotron radiation lithography has been investigated using the SORTEC storage ring(l GeV). From a practical standpoint, the recently built beamlines aim at attaining a centrally controlled beamline system, which is also serially interfaced with the storage ring. In operating the beamlines, not only local control, but also a central control notion is adopted. The central beamline control system comprises a beamline main computer and a programmable sequence controller (PSC) link. The local beamline control system consists of a PSC, a control panel, and a personal computer. The beamline main computer collects each beamline status datum through the PSC link, receiving the storage ring data from the main computer of the 1 GeV synchrotron radiation (SR) source. A novel oscillating mirror mechanism is proposed, in which the mirror chamber, driven by a combination of a cam mechanism and pulse motor installed in air, is oscillated to scan the mirror, thus producing high reliability and compact design. In addition, a practical beamline structure is offered which fulfills system vacuum protection and protects operators from radiation exposure.

In the age of the cloud-native, container technology, referred as OS-level virtualization, is increasingly adopted to deploy cloud applications. Compared with virtual machines, containers are lightweight and flexible in resource management. An important quality-of-service (QoS) class in container management is burstable container, whose resource limits are higher than the actual requests allowing a container to expand whenever demands ramp up and additional resources become available. However, efficiently managing burstable containers is challenging, especially for CPU resources. On the one hand, burstable containers should maintain sufficient concurrency, in the form of threads, to utilize extendable CPU resources. On the other hand, the degree of concurrency necessary for utilizing peak CPU resources leads to suboptimal performance when a container's CPU allocation is constrained. In this paper, we recommend that the number of threads in burstable containers should always be set to the CPU limit to guarantee extensibility. However, modern operating systems (OSes) fall short of efficiently managing thread oversubscription. First, the OS CPU scheduler is inefficient for scheduling excessive threads and lacks container awareness. Second, the existing blocking synchronization supported by the OS kernel is inefficient in handling the sleep and wakeup of excessive threads. Finally, the non-blocking synchronization may waste CPUs performing busy waiting when more than one thread in the run queue. To this end, we present a user-level adaptive container scheduler and two OS mechanisms, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">virtual blocking</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">busy-waiting detection</i> , to avoid inefficiency in managing burstable containers without requiring program code changes. Experimental results show that our approaches can keep burstable containers efficient while allowing the applications in containers to take advantage of additional CPUs. The performance gain under high system load is up to 29.7×.

There are some problem for Strip transmission process, such as low deviation information accuracy , poor reliability, poor control results,the electro-hydraulic servo central position control system of Strip based on the principle of differential capacitance was designed. The differential connection is used for eliminating signal drift and the nonlinear characteristics，high frequency power supply is used for reducing output impedance and improving the system bandwidth, double shielded is used for eliminating the impact of parasitic capacitance, the electro-hydraulic servo central position control system based on fuzzy PID is designed. Research shows that the measuring circuit and control system are with high precision, good reliability, maintenance-free advantages.

work of W. Edwards Deming has convinced industry that must first measure quality and then emphasise process to improve quality. In response to Deming's arguments and in light of perception that software industry is unable to produce quality products on schedule, and within budget, more software development organisations are now emphasising process measurement, monitoring, and assessment. This paper describes what is meant by software process and discusses an approach for its measurement and improvement. INTRODUCTION Unreliable software makes big news, from emergency services disasters to social security payment blunders. Improved software quality is essential to ensure reliable products and services, and gain customer satisfaction. While software development has existed for more than four decades, we failed so far to make as an industry and as an engineering discipline rather than craft. Developing reliable and usable software that is delivered on and within budget still represents difficult endeavour for many organisations. As role of software becomes increasingly critical for businesses as well as for human lives, problems caused by software products that are late, over budget, or that do not work, become magnified. If lives are lost or people inconvenienced due to incapable computer software, news media is there to make big stories. Organisations are realising that their fundamental problems is immaturity of their software process. Robert Lai (1993) proposes that process improvement is second maturity wave of software industry. He states that the first wave of software was developed using waterfall model in 1970's. Today we are Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 216 Software Management in midst of second wave maturity movement as we attempt to formally define development process and best ways to continuously improve it (Lai 1993). Taking lead in this area has been Watts Humphrey (Humphrey 1989, 1990, 1991), and Software Engineering Institute (SEI) at Carnegie Mellon University. SEI started in 1986 to develop process maturity framework to help organisations appraise maturity of their software process, and to provide guidance for organisations to improve their software process capability. A brief description of framework was released in September 1987, including maturity questionnaire. SEI evolved model and questionnaire into 5 -Level Capability Maturity Model (CMM) in 1991. In February 1993, released CMM version 1.1 (Paulk et al 1993). This paper discusses software process and describes capability maturity model (CMM). It also shows how CMM can be used as basis to measure maturity of software process of an organisation and plan its improvement. SOFTWARE QUALITY AND PROCESS IMPROVEMENT In his book Quality is Free Phil Crosby states that: Quality is free. It is not gift, is free. What cost money are unqualify of things all actions that involve not doing jobs right first time (Crosby 1980). If such statement is true for many disciplines, is particularly true for evidence is abundant in number of software products which exceeded their budget, were produced late, failed to satisfy user requirements, and are full of bugs. demand for improved software quality is increasing to ensure reliable products and services. benefits of improved quality comes in form of reduction in failure costs. For software projects failure costs include (DTI 1992): • costs of correcting defects, both before and after delivery • overruns against and budget • unnecessary high maintenance costs • indirect costs which users incur due to poor quality software link between process maturity and software quality is expressed in premise that The quality of software system is governed by quality of process used to develop and maintain it. One stumbling block to improving software quality seems to be that not enough attention is paid to overall development process itself. While software professionals typically devote their to developing, testing or documenting software products, no one has prime responsibility for improving software process. Experience has shown that if Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 Managing Systems 217 no one is working on software process, orderly improvement is unlikely. process certainly won't improve itself, rather, most likely, will deteriorate over time. Continuous improvement can occur only if process infrastructure is in place. Watts Humphrey argues in an early article published in Datamation, April 1989 that: Without work on process, there will be little or no progress in improving software. THE SOFTWARE PROCESS Adopting process view of software development represents revolutionary change in perspective. A process orientation to software development involves elements of structure, focus, measurement, ownership, skills, and supporting technology. In this section we investigate what is meant by software process. What Is Software Process According to Webster's dictionary, process is a system of operations in producing something .. series of actions, changes, or functions that achieve an end result. Chambers Concise Dictionary defines process as a series of actions or events .. sequence of operations or changes undergone. IEEE defines process as a sequence of steps performed for given purpose. In general business context, process is defined as a structured, measured set of activities designed to produce specified output for particular customer or market (Davenport 1993). These definitions put strong emphasis on HOW work is done, in contrast to product focus's emphasis on WHAT. Accordingly, process can be considered as a specific ordering of work activities across and place, with beginning, an end, and clearly identified inputs and outputs: structure for action. In this paper we will adopt following definitions quoted in (Humphrey 1990, Paulk et al 1993) are intended to encompass software throughout its life, which covers new development, enhancement, and repair. software process is The set of activities, methods, and practices used in production and evolution of software. software engineering process is The total set of software engineering activities needed to transform user's requirements into software. Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 218 Software Management People and Software Process Software development is still people-intensive activity. Talented people are most important element in any software organisation. Even if you get best people available, if they do not follow common process, if everyone wrote in different programming languages, used different conventions, or didn't co-ordinate their design and code changes with their peers, results will be chaos. Successful software organisations have learned that even best professionals need structured and disciplined environment in which to do cooperative work. Software organisations that do not establish such disciplines condemn their people to endless hours of repetitively solving technically trivial problems. obvious fact is that attracting best people is vital, but is also essential to support them with an effectively managed software process. Technology and Software Process Another myth is widespread belief that some technologically advanced tool or method will provide magic answer to software crisis. This is not only wrong, but is dangerous. Organisations which jumped on bandwagon of CASE tools, and ended up in failure and wasted and effort have learned their lesson hard way. Just ask yourself before introducing technology: What do I want to automate? In absence of defined, practised, and managed process, introducing automation can lead to increased chaos. There are several factors which limit effective use of software technology: an illdefined process, inconsistent process implementation, and poor process management. Software technology cannot be fully effective until these problems have been properly addressed. Need for Defined Process If no effort is made to define and enhance software development process across whole organisation, each software development project latches on to its own tools, methods, and practices with little guidance available on how to use them. This ad hoc approach will not be sufficient to tackle task of developing complex software systems. goal of software process management is to enable organisations to produce software that meets cost, schedules, and quality objectives. principles are same that underpins statistical process control-principles that have been successfully used in controlling scientific experiments and in high -volume manufacturing operations. Statistical concepts have been found to be just as applicable to software development as they are to production of manufactured goods such as motor cars. Applying such concepts will only be possible if there is defined and managed process. Software Process Models Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517

Unit tests can be significantly sped up by running them in parallel over distributed execution environments, such as the cloud. However, manually setting up such environments and configuring the testing frameworks to effectively use them is cumbersome and requires specialized expertise that developers might lack. We present Cloud Unit Testing (CUT), a tool for automatically executing unit tests in distributed execution environments. Given a set of unit tests, CUT allocates appropriate computational resources, i.e., virtual machines or containers, and schedules the execution of tests over them. Developers do not need to change existing unit test code, and can easily control relevant aspects of test execution, including resource allocation and test scheduling. Additionally, during the execution CUT monitors and publishes events about the running tests which enables stream analytics. CUT and videos showcasing its main features are freely available at: https://www.st.cs.uni-saarland.de/testing/cut/

Competition is rife within BPO-IT service providers as outsourcing clients opt for providers’ that will add significant value to their operations. Thus, providers perceive DevOps as one way of improving the quality of clients’ services through in-house development of reliable software. Research findings indicate that DevOps involves internal reorganisation that could provide the best possible option to combine people, process and software development tools. The approach has been widely applied in software development companies purposely for continuous delivery of reliable software, and to add value to client’s services within provider’s domain. This paper presents the findings from a multi case study of DevOps implementation in BPO-IT service provider organisations. The findings suggest the inclusion of DevOps as an element of strategic IT planning to improve competitiveness by reducing costs and quality of services. The developed DevOps framework proposes a team of coordinating teams working together to improving client and providers’ performances combining IT management, software development and processing teams respectively. To illustrate the concept of the framework, a flowchart depicting a stepwise role of each team is developed, allowing for implementation of agility and flexibility into the process and continuous software delivery, reduced time of service delivery, and improved quality of services.

The rapid adoption of DevOps practices has transformed the software development landscape by emphasizing continuous integration, continuous delivery (CI/CD), and agile methodologies. However, this rapid pace of development often introduces significant security challenges, as traditional security testing methods struggle to keep up with the accelerated release cycles. To address these challenges, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into automated security testing has emerged as a promising solution. This paper explores the use of AI and ML to enhance automated security testing within DevOps environments, offering a comprehensive approach to identifying, predicting, and mitigating security vulnerabilities in real time. Automated security testing leverages AI and ML algorithms to analyze code, detect anomalies, and predict potential security threats. These technologies enable the continuous monitoring of codebases, allowing for the early identification of vulnerabilities before they are exploited. By incorporating AI-driven security testing into the CI/CD pipeline, organizations can ensure that security is not an afterthought but a continuous process integrated into every stage of the software development lifecycle. AI and ML models can be trained to recognize patterns associated with security risks, such as code injection, unauthorized access, and data leakage. These models continuously learn from new data, improving their accuracy over time and adapting to evolving threats. The dynamic nature of AI-driven security testing makes it particularly suited for DevOps environments, where frequent code changes and updates can introduce new vulnerabilities. Moreover, AI and ML can assist in automating complex tasks, such as threat modeling, risk assessment, and the prioritization of security issues, enabling security teams to focus on higher-order tasks that require human expertise.

Satisfactory software performance is essential for the adoption and the success of a product. In organizations that follow traditional software development models (e.g., waterfall), Software Performance Engineering (SPE) involves time-consuming experimental modeling and performance testing outside the actual production environment. Such existing SPE methods, however, are not optimized for environments utilizing Continuous Integration (CI) and Continuous Delivery (CD) that result in high frequency and high volume of code changes. We present a summary of lessons learned and propose improvements to the SPE process in the context of CI/CD. Our findings are based on SPE work on products A and B conducted over 5 years at an online services company X. We find that (a) SPE has mainly become a post hoc activity based on data from the production environment, (b) successful application of SPE techniques require frequent re-evaluation of priorities, and (c) engineers working on SPE require a broader skill set than one traditionally possessed by engineers working on performance.

The recent increase in electricity tariff and the introduction of feed-in tariff from renewable resources have increased the interest of energy consumers, such as those in commercial and residential buildings, in reducing their energy usage. This paper proposes a smart power socket and central control system that utilizes the Zigbee communication protocol to control energy usage. The system is designed such that smart sockets wirelessly provide the necessary data to a central controller. Then, the system analyzes the data to generate control commands to turn the devices attached to the smart socket ON or OFF. Experimental results show that the proposed smart socket can correctly read the power consumption of wirelessly connected devices from up to 18 m away without loss of data. The central controller can effectively control multiple sockets on the basis of a scheduled user program code. A 24-min implementation of the proposed energy management algorithm shows a reduction of 0.811 kWmin (0.0134 kWh) in energy usage after the use of the smart sockets as load controllers. Thus, the proposed smart socket system can be fully utilized in a home energy management system with a proper scheduling algorithm.