This book constitutes the refereed proceedings of the 8th European Workshop on Software Process Technology, EWSPT 2001, held in Witten, Germany, in June 2001. The 18 revised full papers presented were carefully reviewed and selected from 31 submissions. Among the areas addressed are process evolution, experiences, mobility and distribution, UML process patterns, and process improvement.
This book describes an approach to software management based on establishing an infrastructure that serves as the foundation for the project. This infrastructure defines people roles, necessary technology, and interactions between people and technology. This infrastructure automates repetitive tasks, organizes project activities, tracks project status, and seamlessly collects project data to provide measures necessary for decision making. Most importantly, this infrastructure sustains and facilitates the improvement of human-defined processes. The methodology described in the book, which is called Automated Defect Prevention (ADP) stands out from the current software landscape as a result of two unique features: its comprehensive approach to defect prevention, and its far-reaching emphasis on automation. ADP is a practical and thorough guide to implementing and managing software projects and processes. It is a set of best practices for software management through process improvement, which is achieved by the gradual automation of repetitive tasks supported and sustained by this flexible and adaptable infrastructure, an infrastructure that essentially forms a software production line. In defining the technology infrastructure, ADP describes necessary features rather than specific tools, thus remaining vendor neutral. Only a basic subset of features that are essential for building an effective infrastructure has been selected. Many existing commercial and non-commercial tools support these, as well as more advanced features. Appendix E contains such a list.
This book constitutes the joint refereed proceedings of two colocated events: the First International Conference on the Quality of Software Architectures (QoSA 2005) and the Second International Workshop on Software Quality (SOQUA 2005) held in Erfurt, Germany, in September 2005. The 18 revised full papers presented were carefully reviewed and selected from 48 submissions. For QoSA 2005 only 12 papers - of the 31 submitted - were accepted for presentation; they are concerned with research and experiences that investigate the influence a specific software architecture has on software quality aspects. The papers are organized in topical sections on software architecture evaluation, formal approaches to model-driven QoS-handling, modelling QoS in software architectures, software architectures applied, architectural design for QoS, and model-driven software reliability estimation. The 6 papers accepted for SOQUA 2005 - from 17 submissions - mainly focus on quality assurance and on software testing. They are organized in topical sections on test case selection, model-based testing, unit testing, and performance testing.
This collection of 45 papers and 13 posters from the September 2002 conference focuses on the software and hardware that will enable cluster computing. The researchers discuss task management, network hardware, programming clusters, and scalable clusters. Among the topics are experience in offloadin"
Software and Systems Traceability provides a comprehensive description of the practices and theories of software traceability across all phases of the software development lifecycle. The term software traceability is derived from the concept of requirements traceability. Requirements traceability is the ability to track a requirement all the way from its origins to the downstream work products that implement that requirement in a software system. Software traceability is defined as the ability to relate the various types of software artefacts created during the development of software systems. Traceability relations can improve the quality of a product being developed, and reduce the time and cost of development. More specifically, traceability relations can support evolution of software systems, reuse of parts of a system by comparing components of new and existing systems, validation that a system meets its requirements, understanding of the rationale for certain design and implementation decisions, and analysis of the implications of changes in the system.
An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.