November 26, 2020

Download Ebook Free The Art And Science Of Analyzing Software Data

The Art and Science of Analyzing Software Data

The Art and Science of Analyzing Software Data
Author : Christian Bird,Tim Menzies,Thomas Zimmermann
Publisher : Elsevier
Release Date : 2015-09-02
Category : Computers
Total pages :672
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The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. Presents best practices, hints, and tips to analyze data and apply tools in data science projects Presents research methods and case studies that have emerged over the past few years to further understanding of software data Shares stories from the trenches of successful data science initiatives in industry

Product-Focused Software Process Improvement

Product-Focused Software Process Improvement
Author : Michael Felderer,Daniel Méndez Fernández,Burak Turhan,Marcos Kalinowski,Federica Sarro,Dietmar Winkler
Publisher : Springer
Release Date : 2017-11-10
Category : Computers
Total pages :632
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This book constitutes the refereed proceedings of the 18th International Conference on Product-Focused Software Process Improvement, PROFES 2017, held in Innsbruck, Austria, in November/December 2017. The 17 revised full papers presented together with 10 short papers, 21 workshop papers. 3 posters and tool demonstrations papers, and 4 tutorials were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on : Agile software Development; Data science and analytics; Software engineering processes and frameworks; Industry relevant qualitative research; User and value centric approaches; Software startups; Serum; Software testing.

Perspectives on Data Science for Software Engineering

Perspectives on Data Science for Software Engineering
Author : Tim Menzies,Laurie Williams,Thomas Zimmermann
Publisher : Morgan Kaufmann
Release Date : 2016-07-14
Category : Computers
Total pages :408
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Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains

Sharing Data and Models in Software Engineering

Sharing Data and Models in Software Engineering
Author : Tim Menzies,Ekrem Kocaguneli,Burak Turhan,Leandro Minku,Fayola Peters
Publisher : Morgan Kaufmann
Release Date : 2014-12-22
Category : Computers
Total pages :406
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Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data

Data Science and Big Data Analytics

Data Science and Big Data Analytics
Author : EMC Education Services
Publisher : John Wiley & Sons
Release Date : 2015-01-05
Category : Computers
Total pages :432
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Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Transportation Systems Planning

Transportation Systems Planning
Author : Konstadinos G. Goulias
Publisher : CRC Press
Release Date : 2002-12-26
Category : Technology & Engineering
Total pages :456
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Transportation engineering and transportation planning are two sides of the same coin aiming at the design of an efficient infrastructure and service to meet the growing needs for accessibility and mobility. Many well-designed transport systems that meet these needs are based on a solid understanding of human behavior. Since transportation systems are the backbone connecting the vital parts of a city, in-depth understanding of human nature is essential to the planning, design, and operational analysis of transportation systems. With contributions by transportation experts from around the world, Transportation Systems Planning: Methods and Applications compiles engineering data and methods for solving problems in the planning, design, construction, and operation of various transportation modes into one source. It is the first methodological transportation planning reference that illustrates analytical simulation methods that depict human behavior in a realistic way, and many of its chapters emphasize newly developed and previously unpublished simulation methods. The handbook demonstrates how urban and regional planning, geography, demography, economics, sociology, ecology, psychology, business, operations management, and engineering come together to help us plan for better futures that are human-centered. The text reviews projects from an initial problem statement to final policy action and associated decision-making and examines policies at all levels of government, from the city to the national levels. Unlike many other handbooks which are encyclopedic reviews, Transportation Systems Planning extends far beyond modeling in engineering and economics to present a truly transdisciplinary approach to transportation systems planning.

The Art of Data Science

The Art of Data Science
Author : Roger D. Peng,Elizabeth Matsui
Publisher : Unknown
Release Date : 2016-06-08
Category : Business & Economics
Total pages :170
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"This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science."--Leanpub.com.

Statistics

Statistics
Author : Alan Agresti
Publisher : Unknown
Release Date : 2013
Category : Statistics
Total pages :129
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The Art and Science of Interpreting Market Research Evidence

The Art and Science of Interpreting Market Research Evidence
Author : D. V. L. Smith,J. H. Fletcher
Publisher : John Wiley & Sons
Release Date : 2004-05-14
Category : Business & Economics
Total pages :248
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The Art and Science of Interpreting Market Research Evidence offers a complete account of the way today's researchers interpret evidence and apply it to decision making. David Smith and Jonathan Fletcher show how to assess your current deciphering processes, and present an innovative framework integrating quantitative and qualitative approaches for analysing complex data-sets. With its holistic approach to interpretation and its 10-step process for making it work in practice, this book will equip you with a deep understanding of data analysis and ultimately improve your judgment to produce better business decisions. "This is modern commercial research, where the mind of the researcher is finally acknowledged as admissible data. Prior knowledge, pragmatism, experience are all robust grist to the 'holistic' research mill. A must-read for anyone getting to grips with 21st century market research." Virginia Valentine, Semiotic Solutions

Analyzing Social Science Data

Analyzing Social Science Data
Author : David de Vaus
Publisher : SAGE
Release Date : 2002-09-17
Category : Social Science
Total pages :401
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Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE VARIABLE\PART SIX: HOW TO ANALYZE TWO VARIABLES\PART SEVEN: HOW TO CARRY OUT MULTIVARIATE ANALYSIS

Analyzing Art and Aesthetics

Analyzing Art and Aesthetics
Author : Anne Collins Goodyear,Margaret A. Weitekamp
Publisher : Smithsonian Institution
Release Date : 2013-10-30
Category : Art
Total pages :309
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This ninth volume of the Artefacts series explores how artists have responded to developments in science and technology, past and present. Rather than limiting the discussion to art alone, editors Anne Collins Goodyear and Margaret Weitekamp also asked contributors to consider aesthetics: the scholarly consideration of sensory responses to cultural objects. When considered as aesthetic objects, how do scientific instruments or technological innovations reflect and embody culturally grounded assessments about appearance, feel, and use? And when these objects become museum artifacts, what aesthetic factors affect their exhibition? Contributors found answers in the material objects themselves. This volume reconsiders how science, technology, art, and aesthetics impact one another.

Applied Data Science

Applied Data Science
Author : Martin Braschler,Thilo Stadelmann,Kurt Stockinger
Publisher : Springer
Release Date : 2019-06-13
Category : Computers
Total pages :465
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This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.

Fuzzing for Software Security Testing and Quality Assurance

Fuzzing for Software Security Testing and Quality Assurance
Author : Ari Takanen,Jared D. Demott,Charles Miller
Publisher : Artech House
Release Date : 2008
Category : Computer network resources
Total pages :287
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Learn the code cracker's malicious mindset, so you can find worn-size holes in the software you are designing, testing, and building. Fuzzing for Software Security Testing and Quality Assurance takes a weapon from the black-hat arsenal to give you a powerful new tool to build secure, high-quality software. This practical resource helps you add extra protection without adding expense or time to already tight schedules and budgets. The book shows you how to make fuzzing a standard practice that integrates seamlessly with all development activities. This comprehensive reference goes through each phase of software development and points out where testing and auditing can tighten security. It surveys all popular commercial fuzzing tools and explains how to select the right one for a software development project. The book also identifies those cases where commercial tools fall short and when there is a need for building your own fuzzing tools.

Data Analysis in the Cloud

Data Analysis in the Cloud
Author : Domenico Talia,Paolo Trunfio,Fabrizio Marozzo
Publisher : Elsevier
Release Date : 2015-09-15
Category : Computers
Total pages :150
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Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. Introduces data analysis techniques and cloud computing concepts Describes cloud-based models and systems for Big Data analytics Provides examples of the state-of-the-art in cloud data analysis Explains how to develop large-scale data mining applications on clouds Outlines the main research trends in the area of scalable Big Data analysis

The Art and Science of Learning from Data

The Art and Science of Learning from Data
Author : Alan Agresti,Chrstine A. Franklin,Bernhard Klingenberg
Publisher : Unknown
Release Date : 2020
Category : Statistics
Total pages :129
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"One of our goals in writing this book was to help make the conceptual approach more interesting and more readily accessible to students. At the end of the course, we want students to look back at their statistics course and realize that they learned practical concepts that will serve them well for the rest of their lives. We also want students to come to appreciate that in practice, assumptions are not perfectly satisfied, models are not exactly correct, distributions are not exactly normally distributed, and different factors should be considered in conducting a statistical analysis. The title of our book reflects the experience of data analysts, who soon realize that statistics is an art as well as a science"--