Commencing with the introduction, the book builds up the basic concepts of quality and software testing. It, then, elaborately discusses the various facets of verification and validation, methodologies of both static testing and dynamic testing of the software, covering the concepts of structured group examinations, control flow and data flow, unit testing, integration testing, system testing and acceptance testing. The text also focuses on the importance of the cost-benefit analysis of testing processes, test automation, object-oriented applications, client-server and web-based applications. The concepts of testing commercial off-the-shelf (COTS) software as well as object-oriented testing have been described in detail. Finally, the book brings out the underlying concepts of usability and accessibility testing. Career in software testing is also covered in the book.
The book is intended for the undergraduate and postgraduate students of computer science and engineering for a course in software testing.
Learn for software testing job opportunities on how automation frameworks designed and understand how to overcome limitations of not knowing such testing tools in the past Setup and use automation tools for twelve different automation frameworks such as Selenium, HP UFT (formerly QTP),Ranorex, RFT and other famous automation testing tools Learn how to deal with the advanced features of automation tools which will be helpful for software testing job opportunities! Understand how the most wanted automation technologies can be designed such as excel automation frameworks which will help for testing projects of leading clients across US,UK. Practice the sample projects using clear instructions from each chapter and apply for relevant software testing jobs in your desired location!
This highly structured text, in its second edition, provides comprehensive coverage of design techniques of algorithms. It traces the complete development of various algorithms in a stepwise approach followed by their pseudo-codes to build an understanding of their applications in practice. With clear explanations, the textbook intends to be much more comprehensive book on design and analysis of algorithm.
Commencing with the introduction, the book gives a detailed account of graphs and data structure. It then elaborately discusses the matrix algorithms, basic algorithms, network algorithms, sorting algorithm, backtracking algorithms and search algorithms. The text also focuses on the heuristics, dynamic programming and meta heuristics. The concepts of cryptography and probabilistic algorithms have been described in detail. Finally, the book brings out the underlying concepts of benchmarking of algorithms, algorithms to schedule processor(s) and complexity of algorithms.
New to the second Edition
New chapters on
• Matrix algorithms • Basic algorithms
• Backtracking algorithms • Complexity of algorithms
Several new sections including asymptotic notation, amortized analysis, recurrences, balanced trees, skip list, disjoint sets, maximal flow algorithm, parsort, radix sort, selection sort, topological sorting/ordering, median and ordered statistics, Huffman coding algorithm, transportation problem, heuristics for scheduling, etc., have been incorporated into the text.
Presenting the contributions of leading experts in their respective fields, Big Data: Algorithms, Analytics, and Applications bridges the gap between the vastness of Big Data and the appropriate computational methods for scientific and social discovery. It covers fundamental issues about Big Data, including efficient algorithmic methods to process data, better analytical strategies to digest data, and representative applications in diverse fields, such as medicine, science, and engineering. The book is organized into five main sections: Big Data Management—considers the research issues related to the management of Big Data, including indexing and scalability aspects Big Data Processing—addresses the problem of processing Big Data across a wide range of resource-intensive computational settings Big Data Stream Techniques and Algorithms—explores research issues regarding the management and mining of Big Data in streaming environments Big Data Privacy—focuses on models, techniques, and algorithms for preserving Big Data privacy Big Data Applications—illustrates practical applications of Big Data across several domains, including finance, multimedia tools, biometrics, and satellite Big Data processing
Overall, the book reports on state-of-the-art studies and achievements in algorithms, analytics, and applications of Big Data. It provides readers with the basis for further efforts in this challenging scientific field that will play a leading role in next-generation database, data warehousing, data mining, and cloud computing research. It also explores related applications in diverse sectors, covering technologies for media/data communication, elastic media/data storage, cross-network media/data fusion, and SaaS.
The proposed book expertly combines the finest database design material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of database design.
This book represents a quick and efficient way to unite valuable content from leading database design experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources.Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints.Details multiple relational models and modeling languages, enhancing the reader’s technical expertise and familiarity with design-related requirements specification. Coverage of both theory and practice brings all of the elements of database design together in a single volume, saving the reader the time and expense of making multiple purchases.
Terry Halpin, a pioneer in the development of ORM, blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible. Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model, and then, where needed, abstract ER and UML models from it. This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives.Presents the most indepth coverage of Object-Role Modeling available anywhere, including a thorough update of the book for ORM2, as well as UML2 and E-R (Entity-Relationship) modeling. Includes clear coverage of relational database concepts, and the latest developments in SQL and XML, including a new chapter on the impact of XML on information modeling, exchange and transformation. New and improved case studies and exercises are provided for many topics.
LogiQL’s declarative approach enables complex data structures and business rules to be simply specified and then automatically executed. It is especially suited to business applications requiring complex rules to be implemented efficiently, for example predictive analytics and supply chain optimization.
Suitable for both novices and experienced developers, the book is written in easy-to-understand language. It includes many examples and exercises throughout to illustrate the main concepts and consolidate understanding.
All relevant facts, constraints and derivation rules are expressed in controlled natural language sentences that are intelligible to users in the business domain being modeled. This allows ORM data models to be validated by business domain experts who are unfamiliar with ORM’s graphical notation. For the data modeler, ORM’s graphical notation covers a much wider range of constraints than can be expressed in industrial ER or UML class diagrams, and thus allows rich visualization of the underlying semantics.
Suitable for both novices and experienced practitioners, this book covers the fundamentals of the ORM approach. Written in easy-to-understand language, it shows how to design an ORM model, illustrating each step with simple examples. Each chapter ends with a practical lab that discusses how to use the freeware NORMA tool to enter ORM models and use it to automatically generate verbalizations of the model and map it to a relational database.
The 17 papers accepted for BPMDS were selected from 48 submissions and cover a wide spectrum of issues related to business process development, modeling, and support. They are grouped into sections on business process in the cloud, advanced BPM in an organizational context, similarity, variations and configuration, BPM and requirements engineering, humans and business process models, and BPM technologies using computational methods.
The 13 papers accepted for EMMSAD were chosen from 28 submissions and focus on exploring, evaluating, and enhancing current information modeling methods and methodologies. They are grouped in sections on modeling of enterprise architecture, modeling facts and rules, business process modeling, modeling of non-functional requirements, safety modeling and analysis, quality of models and modeling languages, and supporting the learning of conceptual modeling.
The 17 papers accepted for BPMDS 2009 were carefully reviewed and selected from 32 submissions. The topics addressed by the BPMDS workshop are business and goal-related drivers; model-driven process change; technological drivers and IT services; technological drivers and process mining; and compliance and awareness.
Following an extensive review process, 16 papers out of 36 submissions were accepted for EMMSAD 2009. These papers cover the following topics: use of ontologies; UML and MDA; ORM and rule-oriented modeling; goal-oriented modeling; alignment and understandability; enterprise modeling; and patterns and anti-patterns in enterprise modeling.
· Explains how to model databases with Microsoft® Visio for Enterprise Architects (VEA), focusing on tool features.
· Provides a platform-independent introduction to data modeling using both Object Role Modeling (ORM) and Entity Relationship Modeling (ERM), and includes practical advice on managing database projects.
· Additional ORM models, course notes, and add-ins available online.