Matthias Jarke

Toward reference models for requirements traceability

Requirements traceability is intended to ensure continued alignment between stakeholder requirements and various outputs of the system development process. To be useful, traces must be organized according to some modeling framework. Indeed, several such frameworks have been proposed, mostly based on theoretical considerations or analysis of other literature. This paper, in contrast, follows an empirical approach. Focus groups and interviews conducted in 26 major software development organizations demonstrate a wide range of traceability practices with distinct low-end and high-end users of traceability. From these observations, reference models comprising the most important kinds of traceability links for various development tasks have been synthesized. The resulting models have been validated in case studies and are incorporated in a number of traceability tools. A detailed case study on the use of the models is presented. Four kinds of traceability link types are identified and critical issues that must be resolved for implementing each type and potential solutions are discussed. Implications for the design of next-generation traceability methods and tools are discussed and illustrated.

Fundamentals of Data Warehouses

From the Publisher: Data warehouses have captured the attention of practitioners and researchers alike. But the design and optimization of data warehouses remains an art rather than a science. This book presents a comparative review of the state of the art and best current practice of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, update propagation, metadata management, quality assessment, and design optimization. Also, based on results of the European Data Warehouse Quality project, it offers a conceptual framework by which the architecture and quality of data warehouse efforts can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modeling, and artificial intelligence. For researchers and database professionals in academia and industry, the book offers an excellent introduction to the issues of quality and metadata usage in the context of data warehouses.

ConceptBase—a deductive object base for meta data management

Deductive object bases attempt to combine the advantages of deductive relational databases with those of object-oriented databases. We review modeling and implementation issues encountered during the development of ConceptBase, a prototype deductive object manager supporting the Telos object model. Significant features include: 1) The symmetric treatment of object-oriented, logic-oriented and graph-oriented perspectives, 2) an infinite metaclass hierarchy as a prerequisite for extensibility and schema evolution, 3) a simple yet powerful formal semantics used as the basis for implementation, 4) a client-server architecture supporting collaborative work in a wide-area setting. Several application experiences demonstrate the value of the approach especially in the field of meta data management.

A proposal for a scenario classification framework

The requirements engineering, information systems and software engineering communities recently advocated scenario-based approaches which emphasise the user/system interaction perspective in developing computer systems. Use of examples, scenes, narrative descriptions of contexts, mock-ups and prototypes-all these ideas can be called scenario-based approaches, although exact definitions are not easy beyond stating that these approaches emphasise some description of the real world. Experience seems to tell us that people react to ‘real things’ and that this helps in clarifying requirements. Indeed, the widespread acceptance of prototyping in system development points to the effectiveness of scenario-based approaches. However, we have little understanding about how scenarios should be constructed, little hard evidence about their effectiveness and even less idea about why they work.The paper is an attempt to explore some of the issues underlying scenario-based approaches in requirements engineering and to propose a framework for their classification. The framework is a four-dimensional framework which advocates that a scenario-based approach can be well defined by itsform, content, purpose andlife cycle. Every dimension is itself multifaceted and a metric is associated with each facet. Motivations for developing the framework are threefold: (a) to help in understanding and clarifying existing scenario-based approaches; (b) to situate the industrial practice of scenarios; and (c) to assist researchers develop more innovative scenario-based approaches.

The future of e-learning: a shift to knowledge networking and social software

The main aim of Knowledge Management (KM) is to connect people to quality knowledge as well as people to people in order to peak performance. This is also the primary goal of Learning Management (LM). In fact, in the world of e-learning, it is more widely recognised that how learning content is used and distributed by learners might be more important than how it is designed. In the last few years, there has been an increasing focus on social software applications and services as a result of the rapid development of Web 2.0 concepts. In this paper, we argue that LM and KM can be viewed as two sides of the same coin, and explore how Web 2.0 technologies can leverage knowledge sharing and learning and enhance individual performance whereas previous models of LM and KM have failed, and present a social software driven approach to LM and KM.

Scenario Management: An Interdisciplinary Approach

Scenario management (SM) means different things to different people, even though everyone seems to admit its current importance and its further potential. In this paper, we seek to provide an interdisciplinary framework for SM from three major disciplines that use scenarios – strategic management, human–computer interaction, and software and systems engineering – to deal with description of current and future realities. In particular, we attempt to answer the following questions: How are scenarios developed and used in each of the three disciplines? Why are they becoming important? What are current research contributions in scenario management? What are the research and practical issues related to the creation and use of scenarios, in particular in the area of requirements engineering? Based on brainstorming techniques, this paper proposes an interdisciplinary definition of scenarios, frameworks for scenario development, use and evaluation, and directions for future research.

Architecture and quality in data warehouses: An extended repository approach

Abstract Most database researchers have studied data warehouses (DW) in their role as buffers of materialized views, mediating between update-intensive OLTP systems and query-intensive decision support. This neglects the organizational role of data warehousing as a means of centralized information flow control. As a consequence, a large number of quality aspects relevant for data warehousing cannot be expressed with the current DW meta models. This paper makes two contributions towards solving these problems. Firstly, we enrich the meta data about DW architectures by explicit enterprise models. Secondly, many very different mathematical techniques for measuring or optimizing certain aspects of DW quality are being developed. We adapt the Goal-Question-Metric approach from software quality management to a meta data management environment in order to link these special techniques to a generic conceptual framework of DW quality. The approach has been implemented in full on top of the ConceptBase repository system and has undergone some validation by applying it to the support of specific quality-oriented methods, tools, and application projects in data warehousing.

Requirements tracing

Requirem TRacing I n this ever-changing business and technology environment, the risk of inconsistencies in systems development and evolution multiplies. Experience reuse becomes a necessity in order to control quality, costs, and time, even when personnel changes. Requirements tracing is emerging as an effective bridge that aligns system evolution with changing stakeholder needs. It also helps uncover unexpected problems and innovative opportunities, and lays the groundwork for corporate knowledge management. However, few organizations fully recognize—or even understand—the true potential of the new methods and tools in requirements tracing. A network of projects worldwide has investigated the issues, studied advanced industry solutions, and developed research prototypes in order to provide a more coherent view of where we are moving. Far removed from its time-honored definition as a fuzzy early phase of systems development, requirements engineering is now recognized as the key tool to establish a vision of system-related change in its technical, cognitive, and social context [5]. In other words, it is the task of requirements engineering to proceed along three dimensions: managing the convergence of stakeholder interests toward agreement on key system goals and constraints; achieving a sufficient shared understanding of the issues involved in realizing the system vision, such as its functionality, nonfunctional properties, intended and unintended side effects; and documenting this understanding in adequate representation formats, for human information sharing as well as for computerized system development [6]. The intended result of this process is a structured but evolving set of agreed, well understood, and carefully documented requirements. Requirements traceability, then, is defined as the ability to describe and follow the life of a requirement, in both a forward and backward direction, ideally through the whole systems life cycle [3]. Four kinds of traceability links are typically distinguished with respect to their process relationships to requirements [1]:

DAIDA: an environment for evolving information systems

We present a framework for the development of information systems based on the premise that the knowledge that influences the development process needs to somehow be captured, represented, and managed if the development process is to be rationalized. Experiences with a prototype environment developed in ESPRIT project DAIDA demonstrate the approach. The project has implemented an environment based on state-of-the-art languages for requirements modeling, design and implementation of information systems. In addition, the environment offers tools for aiding the mapping process from requirements to design and then to implementation, also for representing decisions reached during the development process. The development process itself is represented explicitly within the system, thus making the DAIDA development framework easier to comprehend, use, and modify.

Managing multiple requirements perspectives with metamodels

Stakeholder conflicts can be productive in requirements engineering. Capturing, monitoring, and resolving multiple perspectives is difficult and time consuming when done by hand. Our experience with ConceptBase shows that a simple but customizable metamodeling approach, combined with an advanced query facility, produces higher quality requirements documents in less time.