Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
29,991
result(s) for
"Software maintenance."
Sort by:
Challenges in Agile Software Maintenance for Local and Global Development: An Empirical Assessment
Agile methods have gained wide popularity recently due to their characteristics in software development. Despite the success of agile methods in the software maintenance process, several challenges have been reported. In this study, we investigate the challenges that measure the impact of agile methods in software maintenance in terms of quality factors. A survey was conducted to collect data from agile practitioners to establish their opinions about existing challenges. As a result of the statistical analysis of the data from the survey, it has been observed that there are moderately effective challenges in manageability, scalability, communication, collaboration, and transparency. Further research is required to validate software maintenance challenges in agile methods.
Journal Article
Kubernetes : up and running : dive into the future of infrastructure
\"Kubernetes is here to stay. In just five years, this container orchestrator has radically changed the way developers and ops personnel build, deploy, and maintain applications in the cloud. The updated edition of this popular book explains how Kubernetes can help your company achieve new levels of velocity, agility, reliability, and efficiency-- whether you're new to distributed systems or have been deploying cloud native apps for some time\"-- Provided by publisher.
Book
Industrial adoption of machine learning techniques for early identification of invalid bug reports
Despite the accuracy of machine learning (ML) techniques in predicting invalid bug reports, as shown in earlier research, and the importance of early identification of invalid bug reports in software maintenance, the adoption of ML techniques for this task in industrial practice is yet to be investigated. In this study, we used a technology transfer model to guide the adoption of an ML technique at a company for the early identification of invalid bug reports. In the process, we also identify necessary conditions for adopting such techniques in practice. We followed a case study research approach with various design and analysis iterations for technology transfer activities. We collected data from bug repositories, through focus groups, a questionnaire, and a presentation and feedback session with an expert. As expected, we found that an ML technique can identify invalid bug reports with acceptable accuracy at an early stage. However, the technique’s accuracy drops over time in its operational use due to changes in the product, the used technologies, or the development organization. Such changes may require retraining the ML model. During validation, practitioners highlighted the need to understand the ML technique’s predictions to trust the predictions. We found that a visual (using a state-of-the-art ML interpretation framework) and descriptive explanation of the prediction increases the trustability of the technique compared to just presenting the results of the validity predictions. We conclude that trustability, integration with the existing toolchain, and maintaining the techniques’ accuracy over time are critical for increasing the likelihood of adoption.
Journal Article
Empirical Validation of Three Software Metrics Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Processes
Empirical validation of software metrics suites to predict fault proneness in object-oriented (OO) components is essential to ensure their practical use in industrial settings. In this paper, we empirically validate three OO metrics suites for their ability to predict software quality in terms of fault-proneness: the Chidamber and Kemerer (CK) metrics, Abreu's Metrics for Object-Oriented Design (MOOD), and Bansiya and Davis' Quality Metrics for Object-Oriented Design (QMOOD). Some CK class metrics have previously been shown to be good predictors of initial OO software quality. However, the other two suites have not been heavily validated except by their original proposers. Here, we explore the ability of these three metrics suites to predict fault-prone classes using defect data for six versions of Rhino, an open-source implementation of JavaScript written in Java. We conclude that the CK and QMOOD suites contain similar components and produce statistical models that are effective in detecting error-prone classes. We also conclude that the class components in the MOOD metrics suite are not good class fault-proneness predictors. Analyzing multivariate binary logistic regression models across six Rhino versions indicates these models may be useful in assessing quality in OO classes produced using modern highly iterative or agile software development processes.
Journal Article
Serverless Integration Design Patterns with Azure
A practical guide that helps you progress to using modern integration methods and leverage new cloud capability models Key Features * Design critical hybrid integration solutions for your organization * Gain in-depth knowledge of how to build cloud-native integration solutions * Leverage cognitive services to build smart cloud solutions Book Description With more enterprises adapting cloud-based and API-based solutions, application integration has become more relevant and significant than ever before. Parallelly, Serverless Integration has gained popularity, as it helps agile organizations to build integration solutions quickly without having to worry about infrastructure costs. With Microsoft Azure's serverless offerings, such as Logic Apps, Azure Functions, API Management, Azure Event Grid and Service Bus, organizations can build powerful, secure, and scalable integration solutions with ease. The primary objective of this book is to help you to understand various serverless offerings included within Azure Integration Services, taking you through the basics and industry practices and patterns. This book starts by explaining the concepts of services such as Azure Functions, Logic Apps, and Service Bus with hands-on examples and use cases. After getting to grips with the basics, you will be introduced to API Management and building B2B solutions using Logic Apps Enterprise Integration Pack. This book will help readers to understand building hybrid integration solutions and touches upon Microsoft Cognitive Services and leveraging them in modern integration solutions. Industry practices and patterns are brought to light at appropriate opportunities while explaining various concepts. What you will learn * Learn about the design principles of Microsoft Azure Serverless Integration * Get insights into Azure Functions, Logic Apps, Azure Event Grid and Service Bus * Secure and manage your integration endpoints using Azure API Management * Build advanced B2B solutions using Logic Apps, Enterprise Integration Pack * Monitor integration solutions using tools available on the market * Discover design patterns for hybrid integration Who this book is for Serverless Integration Design Patterns with Azure is for you if you are a solution architect or integration professional aiming to build complex cloud solutions for your organization. Developers looking to build next-level hybrid or cloud solutions will also find this book useful. Prior programming knowledge is necessary.
eBook
Working with Legacy Systems
Understand the crux of legacy systems — their architecture, analysis, and security constraints Key Features * Understand what are legacy systems and learn various strategies to maintain them * Deep dive into the basic and advanced architectures of legacy systems * Discover how to analyze and secure the legacy systems Book Description The latest edition to our range of products is Packt Select - the new range of books with a broad spectrum of information on unique topics. We have identified your requirements, searched for the best books available, and we now offer these to you. With these books, you'll enjoy a smooth learning experience with the usual Packt \"must-haves\" of real-world examples and best practices. New technologies are continuously being introduced in the I.T. industry. While learning those is important, maintaining legacy systems is equally necessary to ensure that the I.T infrastructure of your organization functions to its best abilities. Sound knowledge of techniques that can be used for maintaining legacy systems, can help you avoid many pitfalls. You'll begin the book with a quick understanding of what a legacy system looks like, how it works, and what are some common issues in it. Then, you'll explore the architecture of a legacy system in detail and learn each of its components. You'll learn and use various techniques to analyze a legacy system. After learning about the security constraints associated with legacy systems, you'll explore ways to overcome these constraints and secure the systems. Towards the end of the book, you'll learn how easily make changes in the legacy systems to enhance their performance. By the end of this book, you'll have skills and confidence to work with legacy systems and efficiently maintain them. What you will learn * Perform the static and dynamic analyses of legacy systems * Implement various best-practices to secure your legacy systems * Use techniques, such as data cleansing and process cleansing to stabilize your system * Apply structural changes in your legacy system to make it highly available * Identify and resolve common issues with legacy systems * Gain knowledge of various tests that can help secure and maintain your legacy systems Who this book is for This book is ideal for IT professionals, who want to understand the working and maintenance of the legacy systems. Prior knowledge of working with legacy systems is not needed to complete this book.
eBook
Software evolution and maintenance
Provides students and engineers with the fundamental developments and common practices of software evolution and maintenance Software Evolution and Maintenance: A Practitioner's Approach introduces readers to a set of well-rounded educational materials, covering the fundamental developments in software evolution and common maintenance practices in the industry. Each chapter gives a clear understanding of a particular topic in software evolution, and discusses the main ideas with detailed examples. The authors first explain the basic concepts and then drill deeper into the important aspects of software evolution. While designed as a text in an undergraduate course in software evolution and maintenance, the book is also a great resource forsoftware engineers, information technology professionals, and graduate students in software engineering. * Based on the IEEE SWEBOK (Software Engineering Body of Knowledge) * Explains two maintenance standards: IEEE/EIA 1219 and ISO/IEC14764 * Discusses several commercial reverse and domain engineering toolkits * Slides for instructors are available online Software Evolution and Maintenance: A Practitioner's Approach equips readers with a solid understanding of the laws of software engineering, evolution and maintenance models, reengineering techniques, legacy information systems, impact analysis, refactoring, program comprehension, and reuse.
eBook
Continuous integration, delivery, and deployment
The challenge faced by many teams while implementing Continuous Deployment is that it requires the use of many tools and processes that all work together. Learning and implementing all these tools (correctly) takes a lot of time and effort, leading people to wonder whether it's really worth it. This book sets up a project to show you the different steps, processes, and tools in Continuous Deployment and the actual problems they solve. We start by introducing Continuous Integration (CI), deployment, and delivery as well as providing an overview of the tools used in CI. You'll then create a web app and see how Git can be used in a CI environment. Moving on, you'll explore unit testing using Jasmine and browser testing using Karma and Selenium for your app. You'll also find out how to automate tasks using Gulp and Jenkins. Next, you'll get acquainted with database integration for different platforms, such as MongoDB and PostgreSQL. Finally, you'll set up different Jenkins jobs to integrate with Node.js and C# projects, and Jenkins pipelines to make branching easier. By the end of the book, you'll have implemented Continuous Delivery and deployment from scratch.
eBook
Predicting maintenance performance using object-oriented design complexity metrics
The Object-Oriented (OO) paradigm has become increasingly popular in recent years. Researchers agree that, although maintenance may turn out to be easier for OO systems, it is unlikely that the maintenance burden will completely disappear. One approach to controlling software maintenance costs is the utilization of software metrics during the development phase, to help identify potential problem areas. Many new metrics have been proposed for OO systems, but only a few of them have been validated. The purpose of this research is to empirically explore the validation of three existing OO design complexity metrics and, specifically, to assess their ability to predict maintenance time. This research reports the results of validating three metrics, Interaction Level (IL), Interface Size (IS), and Operation Argument Complexity (OAC). A controlled experiment was conducted to investigate the effect of design complexity (as measured by the above metrics) on maintenance time. Each of the three metrics by itself was found to be useful in the experiment in predicting maintenance performance.
Journal Article