Eric Yu – författare

Non-Functional Requirements in Software Engineering presents a systematic and pragmatic approach to `building quality into' software systems. Systems must exhibit software quality attributes, such as accuracy, performance, security and modifiability. However, such non-functional requirements (NFRs) are difficult to address in many projects, even though there are many techniques to meet functional requirements in order to provide desired functionality. This is particularly true since the NFRs for each system typically interact with each other, have a broad impact on the system and may be subjective. To enable developers to systematically deal with a system's diverse NFRs, this book presents the NFR Framework. Structured graphical facilities are offered for stating NFRs and managing them by refining and inter-relating NFRs, justifying decisions, and determining their impact. Since NFRs might not be absolutely achieved, they may simply be satisfied sufficiently (`satisficed'). To reflect this, NFRs are represented as `softgoals', whose interdependencies, such as tradeoffs and synergy, are captured in graphs. The impact of decisions is qualitatively propagated through the graph to determine how well a chosen target system satisfices its NFRs. Throughout development, developers direct the process, using their expertise while being aided by catalogues of knowledge about NFRs, development techniques and tradeoffs, which can all be explored, reused and customized. Non-Functional Requirements in Software Engineering demonstrates the applicability of the NFR Framework to a variety of NFRs, domains, system characteristics and application areas. This will help readers apply the Framework to NFRs and domains of particular interest to them. Detailed treatments of particular NFRs - accuracy, security and performance requirements - along with treatments of NFRs for information systems are presented as specializations of the NFRFramework. Case studies of NFRs for a variety of information systems include credit card and administrative systems. The use of the Framework for particular application areas is illustrated for software architecture as well as enterprise modelling. Feedback from domain experts in industry and government provides an initial evaluation of the Framework and some case studies. Drawing on research results from several theses and refereed papers, this book's presentation, terminology and graphical notation have been integrated and illustrated with many figures. Non-Functional Requirements in Software Engineering is an excellent resource for software engineering practitioners, researchers and students.

Non-Functional Requirements in Software Engineering presents a systematic and pragmatic approach to `building quality into' software systems. Systems must exhibit software quality attributes, such as accuracy, performance, security and modifiability. However, such non-functional requirements (NFRs) are difficult to address in many projects, even though there are many techniques to meet functional requirements in order to provide desired functionality. This is particularly true since the NFRs for each system typically interact with each other, have a broad impact on the system and may be subjective. To enable developers to systematically deal with a system's diverse NFRs, this book presents the NFR Framework. Structured graphical facilities are offered for stating NFRs and managing them by refining and inter-relating NFRs, justifying decisions, and determining their impact. Since NFRs might not be absolutely achieved, they may simply be satisfied sufficiently (`satisficed'). To reflect this, NFRs are represented as `softgoals', whose interdependencies, such as tradeoffs and synergy, are captured in graphs. The impact of decisions is qualitatively propagated through the graph to determine how well a chosen target system satisfices its NFRs. Throughout development, developers direct the process, using their expertise while being aided by catalogues of knowledge about NFRs, development techniques and tradeoffs, which can all be explored, reused and customized. Non-Functional Requirements in Software Engineering demonstrates the applicability of the NFR Framework to a variety of NFRs, domains, system characteristics and application areas. This will help readers apply the Framework to NFRs and domains of particular interest to them. Detailed treatments of particular NFRs - accuracy, security and performance requirements - along with treatments of NFRs for information systems are presented as specializations of the NFRFramework. Case studies of NFRs for a variety of information systems include credit card and administrative systems. The use of the Framework for particular application areas is illustrated for software architecture as well as enterprise modelling. Feedback from domain experts in industry and government provides an initial evaluation of the Framework and some case studies. Drawing on research results from several theses and refereed papers, this book's presentation, terminology and graphical notation have been integrated and illustrated with many figures. Non-Functional Requirements in Software Engineering is an excellent resource for software engineering practitioners, researchers and students.

Non-Functional Requirements in Software Engineering presents a systematic and pragmatic approach to `building quality into'' software systems. Systems must exhibit software quality attributes, such as accuracy, performance, security and modifiability. However, such non-functional requirements (NFRs) are difficult to address in many projects, even though there are many techniques to meet functional requirements in order to provide desired functionality. This is particularly true since the NFRs for each system typically interact with each other, have a broad impact on the system and may be subjective. To enable developers to systematically deal with a system''s diverse NFRs, this book presents the NFR Framework. Structured graphical facilities are offered for stating NFRs and managing them by refining and inter-relating NFRs, justifying decisions, and determining their impact. Since NFRs might not be absolutely achieved, they may simply be satisfied sufficiently (`satisficed''). To reflect this, NFRs are represented as `softgoals'', whose interdependencies, such as tradeoffs and synergy, are captured in graphs. The impact of decisions is qualitatively propagated through the graph to determine how well a chosen target system satisfices its NFRs. Throughout development, developers direct the process, using their expertise while being aided by catalogues of knowledge about NFRs, development techniques and tradeoffs, which can all be explored, reused and customized. Non-Functional Requirements in Software Engineering demonstrates the applicability of the NFR Framework to a variety of NFRs, domains, system characteristics and application areas. This will help readers apply the Framework to NFRs and domains of particular interest to them. Detailed treatments of particular NFRs - accuracy, security and performance requirements - along with treatments of NFRs for information systems are presented as specializations of the NFRFramework. Case studies of NFRs for a variety of information systems include credit card and administrative systems. The use of the Framework for particular application areas is illustrated for software architecture as well as enterprise modelling. Feedback from domain experts in industry and government provides an initial evaluation of the Framework and some case studies. Drawing on research results from several theses and refereed papers, this book''s presentation, terminology and graphical notation have been integrated and illustrated with many figures. Non-Functional Requirements in Software Engineering is an excellent resource for software engineering practitioners, researchers and students.

This book constitutes the refereed proceedings of the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, held in Grenoble, France, in June 2020.*The 33 full papers presented in this volume were carefully reviewed and selected from 185 submissions. The book also contains one invited talk in full paper length.The papers were organized in topical sections named: distributed applications; AI and big data in IS; process mining and analysis; requirements and modeling; and information systems engineering.Abstracts on the CAiSE 2020 tutorials can be found in the back matter of the volume.*The conference was held virtually due to the COVID-19 pandemic.

In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "How did our sales perform during the last quarter?" A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like "How are we doing right now?" Today the focus of BI users are looking into the future. "Given what I did before and how I am currently doing this quarter, how will I do next quarter?" Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text.

In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "How did our sales perform during the last quarter?" A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like "How are we doing right now?" Today the focus of BI users are looking into the future. "Given what I did before and how I am currently doing this quarter, how will I do next quarter?" Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text.

This book constitutes the refereed proceedings of the 32nd International Conference on Conceptual Modeling, ER 2014, held in Atlanta, GA, USA. The 23 full and 15 short papers presented were carefully reviewed and selected from 80 submissions. Topics of interest presented and discussed in the conference span the entire spectrum of conceptual modeling including research and practice in areas such as: data on the web, unstructured data, uncertain and incomplete data, big data, graphs and networks, privacy and safety, database design, new modeling languages and applications, software concepts and strategies, patterns and narratives, data management for enterprise architecture, city and urban applications.

This book constitutes the refereed proceedings of the 32nd International Conference on Conceptual Modeling, ER 2014, held in Atlanta, GA, USA. The 23 full and 15 short papers presented were carefully reviewed and selected from 80 submissions. Topics of interest presented and discussed in the conference span the entire spectrum of conceptual modeling including research and practice in areas such as: data on the web, unstructured data, uncertain and incomplete data, big data, graphs and networks, privacy and safety, database design, new modeling languages and applications, software concepts and strategies, patterns and narratives, data management for enterprise architecture, city and urban applications.

The 26th International Conference on Conceptual Modeling in Auckland, New Zealand, hosted six workshops which allowed participants to focus their p- sentations and discussions on advanced topics that cannot easily ?t the general conference scope. Thirteen good quality proposals were received and nine were selected. Due to the similarity of their scope, two pairs were suggested to merge, leading to seven proposals. One workshop attracted fewer submissions than expected, so that its selected papers were integrated into the conference. Finally, six wo- shopswerekept.Interestingly,fourofthem(FP-UML,ONISW,QoIS,SeCoGIS) were a sequel of workshops that were held in the last few years, while two were new (CMLSA, RIGiM), exhibiting both the maturity and the innovation of the workshops. Following the call for papers, we received 114 complete submissions, from which 40 quality papers wereselected, giving an acceptance rate of 35% (a fairly standard score for workshops). The following six workshops were organized: – ConceptualModellingforLifeSciencesApplications (CMLSA2007),chaired by Yi-Ping Phoebe Chen and Sven Hartmann. This workshopaddressed the speci?c challenges posed by the large data volumes, the complexity and the data and software heterogeneity involved by life science applications. – Foundations and Practices of UML (FP-UML 2007), chaired by Juan Trujillo and Je?rey Parsons. The third edition of this workshop gathered researchers and practitioners on topics related to data warehouses, security, model transformation, state diagrams development and model quality.

The 26th International Conference on Conceptual Modeling in Auckland, New Zealand, hosted six workshops which allowed participants to focus their p- sentations and discussions on advanced topics that cannot easily ?t the general conference scope. Thirteen good quality proposals were received and nine were selected. Due to the similarity of their scope, two pairs were suggested to merge, leading to seven proposals. One workshop attracted fewer submissions than expected, so that its selected papers were integrated into the conference. Finally, six wo- shopswerekept.Interestingly,fourofthem(FP-UML,ONISW,QoIS,SeCoGIS) were a sequel of workshops that were held in the last few years, while two were new (CMLSA, RIGiM), exhibiting both the maturity and the innovation of the workshops. Following the call for papers, we received 114 complete submissions, from which 40 quality papers wereselected, giving an acceptance rate of 35% (a fairly standard score for workshops). The following six workshops were organized: – ConceptualModellingforLifeSciencesApplications (CMLSA2007),chaired by Yi-Ping Phoebe Chen and Sven Hartmann. This workshopaddressed the speci?c challenges posed by the large data volumes, the complexity and the data and software heterogeneity involved by life science applications. – Foundations and Practices of UML (FP-UML 2007), chaired by Juan Trujillo and Je?rey Parsons. The third edition of this workshop gathered researchers and practitioners on topics related to data warehouses, security, model transformation, state diagrams development and model quality.

Conceptual modeling has long been recognized as the primary means to enable so- ware development in information systems and data engineering. Conceptual modeling provides languages, methods and tools to understand and represent the application domain; to elicit, conceptualize and formalize system requirements and user needs; to communicate systems designs to all stakeholders; and to formally verify and validate systems design on high levels of abstraction. The International Conference on Conceptual Modeling provides a premiere forum for presenting and discussing current research and applications in which the major emphasis is on conceptual modeling. Topics of interest span the entire spectrum of conceptual modeling including research and practice in areas such as theories of concepts and ontologies underlying conceptual modeling, methods and tools for - veloping and communicating conceptual models, and techniques for transforming conceptual models into effective implementations. The scientific program of ER 2008 featured several activities running in parallel. The core activity was the presentation of the 33 research papers published in this volume, which were selected by a large Program Committee (PC) Co-chaired by Qing Li, Stefano Spaccapietra and Eric Yu. We thank the PC Co-chairs, the PC members and the additional referees for the hard work done, often within a short time. Thanks are also due to Moira Norrie from ETH Zurich, Oscar Pastor from the Universitat Politècnica de València, and Amit Sheth from the Wright State Univ- sity for accepting our invitation to present keynotes.

Conceptual modeling has long been recognized as the primary means to enable so- ware development in information systems and data engineering. Conceptual modeling provides languages, methods and tools to understand and represent the application domain; to elicit, conceptualize and formalize system requirements and user needs; to communicate systems designs to all stakeholders; and to formally verify and validate systems design on high levels of abstraction. The International Conference on Conceptual Modeling provides a premiere forum for presenting and discussing current research and applications in which the major emphasis is on conceptual modeling. Topics of interest span the entire spectrum of conceptual modeling including research and practice in areas such as theories of concepts and ontologies underlying conceptual modeling, methods and tools for - veloping and communicating conceptual models, and techniques for transforming conceptual models into effective implementations. The scientific program of ER 2008 featured several activities running in parallel. The core activity was the presentation of the 33 research papers published in this volume, which were selected by a large Program Committee (PC) Co-chaired by Qing Li, Stefano Spaccapietra and Eric Yu. We thank the PC Co-chairs, the PC members and the additional referees for the hard work done, often within a short time. Thanks are also due to Moira Norrie from ETH Zurich, Oscar Pastor from the Universitat Politècnica de València, and Amit Sheth from the Wright State Univ- sity for accepting our invitation to present keynotes.

This Festschrift volume, published in honor of John Mylopoulos on the occasion of his retirement from the University of Toronto, contains 25 high-quality papers, written by leading scientists in the field of conceptual modeling.The volume has been divided into six sections. The first section focuses on the foundations of conceptual modeling and contains material on ontologies and knowledge representation. The four sections on software and requirements engineering, information systems, information integration, and web and services, represent the chief current application domains of conceptual modeling. Finally, the section on implementations concentrates on projects that build tools to support conceptual modeling. With its in-depth coverage of diverse topics, this book could be a useful companion to a course on conceptual modeling.

This Festschrift volume, published in honor of John Mylopoulos on the occasion of his retirement from the University of Toronto, contains 25 high-quality papers, written by leading scientists in the field of conceptual modeling.The volume has been divided into six sections. The first section focuses on the foundations of conceptual modeling and contains material on ontologies and knowledge representation. The four sections on software and requirements engineering, information systems, information integration, and web and services, represent the chief current application domains of conceptual modeling. Finally, the section on implementations concentrates on projects that build tools to support conceptual modeling. With its in-depth coverage of diverse topics, this book could be a useful companion to a course on conceptual modeling.