Handbook of Software Fault Localization A comprehensive analysis of fault localization techniques and strategies In Handbook of Software Fault Localization: Foundations and Advances, distinguished computer scientists Prof. W. Eric Wong and Prof. T.H. Tse deliver a robust treatment of up-to-date techniques, tools, and essential issues in software fault localization. The authors offer collective discussions of fault localization strategies with an emphasis on the most important features of each approach. The book also explores critical aspects of software fault localization, like multiple bugs, successful and failed test cases, coincidental correctness, faults introduced by missing code, the combination of several fault localization techniques, ties within fault localization rankings, concurrency bugs, spreadsheet fault localization, and theoretical studies on fault localization. Readers will benefit from the authors’ straightforward discussions of how to apply cost-effective techniques to a variety of specific environments common in the real world. They will also enjoy the in-depth explorations of recent research directions on this topic. Handbook of Software Fault Localization also includes: A thorough introduction to the concepts of software testing and debugging, their importance, typical challenges, and the consequences of poor efforts Comprehensive explorations of traditional fault localization techniques, including program logging, assertions, and breakpoints Practical discussions of slicing-based, program spectrum-based, and statistics-based techniques In-depth examinations of machine learning-, data mining-, and model-based techniques for software fault localization Perfect for researchers, professors, and students studying and working in the field, Handbook of Software Fault Localization: Foundations and Advances is also an indispensable resource for software engineers, managers, and software project decision makers responsible for schedule and budget control.

This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering. Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.

ETAPS 2004 was the seventh instance of the European Joint Conferences on Theory and Practice of Software. ETAPS is an annual federated conference that was established in 1998 by combining a number of existing and new conferences. This year it comprised ?ve conferences (FOSSACS, FASE, ESOP, CC, TACAS), 23 satellite workshops, 1 tutorial, and 7 invited lectures (not including those that are speci?c to the satellite events). The events that comprise ETAPS address various aspects of the system - velopment process, including speci?cation, design, implementation, analysis and improvement. The languages, methodologies and tools that support these act- ities are all well within its scope. Di?erent blends of theory and practice are r- resented, with an inclination towards theory with a practical motivation on the one hand and soundly based practice on the other. Many of the issues involved in software design apply to systems in general, including hardware systems, and theemphasisonsoftwareisnotintendedtobeexclusive.

Local Area Networks (LANs) play a larger role in our lives today than ever before. For example, LANs provide us with the capability to realize automated banking services, with instant credit checking and numerous other diverse access and manipulation services. Users and developers of LAN products must understand the architecture of the hardware and software mechanisms to effectively design and use such systems. Most gains in LAN productivity will come from future software developments in systems management and applications. This book provides an introduction to the technology associated with Local Area Networks, emphasizing software aspects which have been secondary considerations to hardware in most existing texts. The book also provides a review of the technology needed to realize full service software products, such as computer-aided design and manufacturing systems, large publication systems, and integrated data service networks, and includes an exhaustive review of the products available today.

This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan Brachthäuser (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha's (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan's (FAU Erlangen-Nürnberg) work on Open Source Software Governance, Dominic Henze's (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess's (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren's (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller's (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel's (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter Wägemann's (FAU Erlangen-Nürnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern's (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris's (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics--which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work.

With a unique systematic coverage of next-generation databasing, this essential handbook gives computing professionals working in distributed systems a one-stop source of information and tips on the design, operation, and use of database management systems for a wide variety of applications.

This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.