Software Project Estimation. The Fundamentals for Providing High Quality Information to Decision Makers

An effective, quantitative approach for estimating and managing software projects How many people do I need? When will the quality be good enough for commercial sale? Can this really be done in two weeks? Rather than relying on instinct, the authors of Software Measurement and Estimation offer a new, tested approach that includes the quantitative tools, data, and knowledge needed to make sound estimations. The text begins with the foundations of measurement, identifies the appropriate metrics, and then focuses on techniques and tools for estimating the effort needed to reach a given level of quality and performance for a software project. All the factors that impact estimations are thoroughly examined, giving you the tools needed to regularly adjust and improve your estimations to complete a project on time, within budget, and at an expected level of quality. This text includes several features that have proven to be successful in making the material accessible and easy to master: * Simple, straightforward style and logical presentation and organization enables you to build a solid foundation of theory and techniques to tackle complex estimations * Examples, provided throughout the text, illustrate how to use theory to solve real-world problems * Projects, included in each chapter, enable you to apply your newfound knowledge and skills * Techniques for effective communication of quantitative data help you convey your findings and recommendations to peers and management Software Measurement and Estimation: A Practical Approach allows practicing software engineers and managers to better estimate, manage, and effectively communicate the plans and progress of their software projects. With its classroom-tested features, this is an excellent textbook for advanced undergraduate-level and graduate students in computer science and software engineering. An Instructor Support FTP site is available from the Wiley editorial department.

The book presents a comprehensive discussion on software quality issues and software quality assurance (SQA) principles and practices, and lays special emphasis on implementing and managing SQA. Primarily designed to serve three audiences; universities and college students, vocational training participants, and software engineers and software development managers, the book may be applicable to all personnel engaged in a software projects Features: A broad view of SQA. The book delves into SQA issues, going beyond the classic boundaries of custom-made software development to also cover in-house software development, subcontractors, and readymade software. An up-to-date wide-range coverage of SQA and SQA related topics. Providing comprehensive coverage on multifarious SQA subjects, including topics, hardly explored till in SQA texts. A systematic presentation of the SQA function and its tasks: establishing the SQA processes, planning, coordinating, follow-up, review and evaluation of SQA processes. Focus on SQA implementation issues. Specialized chapter sections, examples, implementation tips, and topics for discussion. Pedagogical support: Each chapter includes a real-life mini case study, examples, a summary, selected bibliography, review questions and topics for discussion. The book is also supported by an Instructor’s Guide.

The one resource needed to create reliable software This text offers a comprehensive and integrated approach to software quality engineering. By following the author's clear guidance, readers learn how to master the techniques to produce high-quality, reliable software, regardless of the software system's level of complexity. The first part of the publication introduces major topics in software quality engineering and presents quality planning as an integral part of the process. Providing readers with a solid foundation in key concepts and practices, the book moves on to offer in-depth coverage of software testing as a primary means to ensure software quality; alternatives for quality assurance, including defect prevention, process improvement, inspection, formal verification, fault tolerance, safety assurance, and damage control; and measurement and analysis to close the feedback loop for quality assessment and quantifiable improvement. The text's approach and style evolved from the author's hands-on experience in the classroom. All the pedagogical tools needed to facilitate quick learning are provided: * Figures and tables that clarify concepts and provide quick topic summaries * Examples that illustrate how theory is applied in real-world situations * Comprehensive bibliography that leads to in-depth discussion of specialized topics * Problem sets at the end of each chapter that test readers' knowledge This is a superior textbook for software engineering, computer science, information systems, and electrical engineering students, and a dependable reference for software and computer professionals and engineers.

A concise, engineering-oriented resource that provides practical support to IT professionals and those responsible for the quality of the software or systems they develop Software quality stems from two distinctive, but associated, topics in software engineering: software functional quality and software structural quality. This book studies the tenets of both of these notions, which focus on the efficiency and value of a design, respectively. It addresses engineering quality on both the application and system levels with attention to information systems (IS) and embedded systems (ES) as well as recent developments. Software Quality Engineering introduces the basic concepts of quality engineering like the nature of the engineering process, quality models and measurements, and evaluation quality, and provides a step-by-step overview of the application of software quality engineering in commonly recognized phases of the software development process. It also discusses management of software quality engineering processes, with special attention to budget, planning, conflict resolution, and traceability of quality requirements. Targeted at graduate engineering students and software quality specialists, Software Quality Engineering: Provides an analysis of interdependence between software functionality and its quality Includes a list of software quality engineering “to-dos” and models of software quality requirements traceability Covers the practical use of related ISO/IEC JTCI/SC7 standards

Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.

This book introduces Software Quality Assurance (SQA) and provides an overview of standards used to implement SQA. It defines ways to assess the effectiveness of how one approaches software quality across key industry sectors such as telecommunications, transport, defense, and aerospace. Includes supplementary website with an instructor’s guide and solutions Applies IEEE software standards as well as the Capability Maturity Model Integration for Development (CMMI) Illustrates the application of software quality assurance practices through the use of practical examples, quotes from experts, and tips from the authors

An easy to implement, practical, and proven risk management methodology for project managers and decision makers Drawing from the author's work with several major and mega capital projects for Royal Dutch Shell, TransCanada Pipelines, TransAlta, Access Pipeline, MEG Energy, and SNC-Lavalin, Project Risk Management: Essential Methods for Project Teams and Decision Makers reveals how to implement a consistent application of risk methods, including probabilistic methods. It is based on proven training materials, models, and tools developed by the author to make risk management plans accessible and easily implemented. Written by an experienced risk management professional Reveals essential risk management methods for project teams and decision makers Packed with training materials, models, and tools for project management professionals Risk Management has been identified as one of the nine content areas for Project Management Professional (PMP®) certification. Yet, it remains an area that can get bogged down in the real world of project management. Practical and clearly written, Project Risk Management: Essential Methods for Project Teams and Decision Makers equips project managers and decision makers with a practical understanding of the basics of risk management as they apply to project management. (PMP and Project Management Professional are registered marks of the Project Management Institute, Inc.)

Why another book on software project management? For some time, the fields of project management, computer science, and software development have been growing rapidly and concurrently. Effective support for the enterprise demands the merging of these efforts into a coordinated discipline, one that incorporates best practices from both systems development and project management life cycles. Robert K. Wysocki creates that discipline in this book–a ready reference for professionals and consultants as well as a textbook for students of computer information systems and project management. By their very nature, software projects defy a «one size fits all» approach. In these pages you will learn to apply best-practice principles while maintaining the flexibility that's essential for successful software development. Learn how to make the planning process fit the need * Understand how and why software development must be planned on a certainty-to-uncertainty continuum * Categorize your projects on a four-quadrant model * Learn when to use each of the five SDPM strategies–Linear, Incremental, Iterative, Adaptive, and Extreme * Explore the benefits of each strategic model and what types of projects it supports best * Recognize the activities that go into the Scoping, Planning, Launching, Monitoring/Controlling, and Closing phases of each strategy * Apply this knowledge to the specific projects you manage * Get a clear picture of where you are and how to get where you want to go

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.

Introduction to Information Literacy for Students presents a concise, practical guide to navigating information in the digital age. Features a unique step-by-step method that can be applied to any research project Includes research insights from professionals, along with review exercises, insiders' tips and tools, search screen images utilized by students, and more Encourages active inquiry-based learning through the inclusion of various study questions and exercises Provides students with effective research strategies to serve them through their academic years and professional careers Ensures accessibility and a strong instructional approach due to authorship by a librarian and award-winning English professor