Intentional Perspectives on Information Systems Engineering

This chapter is an overview of the development of the information systems domain since its infancy. This domain is recognized as very important for the development of private companies and public organisations and therefore it more and more needs solid concepts and sharp ways of thinking. This chapter relates some breakthroughs and tries to place the IS domain in the centre of several worlds. From a simple mediator between the activities world and the informatics world, IS becomes a creator of values, in particular with the emergence of services. But, it requires a shift with several dimensions in the usual way of thinking about activities and informatics and this is the origin of the difficulty. IS complexity comes from its trans-disciplinary nature, which requires several different models to describe it. Besides, all these models must be articulated together to constitute a coherent IS – that is a farandole of models. When a model changes, due to its environment, the other models have to change too in order to keep the farandole coherent. The IS is then sustainable.

The increasing penetration of computers into all aspects of human activity makes it desirable that the interplay among software, data and the domains where computers are applied is made more transparent. An approach to this end is to explicitly relate the modeling concepts of the domains, e.g., natural science, technology and business, to the modeling concepts of software and data. This may make it simpler to build comprehensible integrated models of the interactions between computers and non-computers, e.g., interaction among computers, people, physical processes, biological processes, and administrative processes. This chapter contains an analysis of various facets of the modeling environment for information systems engineering. The lack of satisfactory conceptual modeling tools seems to be central to the unsatisfactory state-of-the-art in establishing information systems. The chapter contains a proposal for defining a concept of information that is relevant to information systems engineering.

Requirements have remained a key source of difficulty since the dawn of computing. Complicating this fact, recent substantive changes in systems development and associated requirements processes – as reflected in reliance on packaged software components, off-shore development, and software-as-a-service – demand a reappraisal of requirements challenges. Yet, there are few empirical studies focusing on what current requirements challenges are, why they emerge and how they affect requirements engineering (RE) efforts. In the present study, we assess the cognitive, social, and complexity-based impediments to effective requirements discovery through two exploratory case studies of large, multi-party development projects. We develop a rich understanding of the requirements challenges facing these development efforts, how these challenges interact and affect the requirements engineering process and outcomes. The analyses reveal significant consistency in the primary challenges of large RE efforts and the profoundly systemic nature of requirements-related impediments. Several recommendations for research and practice of RE are developed.

Small and medium-sized enterprises (SMEs) are important drivers for innovation. In particular, project-driven SMEs that closely cooperate with their customers have specific needs in regard to information engineering of their development process. They need a fast requirements capture since this is most often included in the (unpaid) offer development phase. At the same time, they need to maintain and reuse the knowledge and experiences they have gathered in previous projects extensively as it is their core asset. The situation is complicated further if the application field crosses disciplinary boundaries. To bridge the gaps and perspectives, we focus on shared goals and dependencies captured in models at a conceptual level. Such a model-based approach also offers a smarter connection to subsequent development stages, including a high share of automated code generation. In the approach presented here, the agent- and goal-oriented formalism i ^* is therefore extended by domain models to facilitate information organization. This extension permits a domain model-based similarity search, and a model-based transformation towards subsequent development stages. Our approach also addresses the evolution of domain models reflecting the experiences from completed projects. The approach is illustrated with a case study on software-intensive control systems in an SME of the automotive domain.

With the emergence of mergers, acquisitions, and collaborative enterprises, the issues of alignment and interoperability in inter-organization information systems have become more complex than before. We propose a two level development approach driven by the intentional level and going to the process model level. Alignment and interoperability requirements are first decided at the intentional level. That is, (a) the intention of the inter-organizational system To Be is properly aligned with intentions of the individual systems that come together, and (b) the intentions of the individual systems must interoperate. Thereafter, at the process model level, process model of the system To Be needs to be properly aligned to its intention and the process models of the participating organizational systems interoperate. We develop a Two-dimensional framework to represent this. This framework drives a development method to support inter-organizational system development. We illustrate this method in a supply chain system example.

This chapter presents research progress in Requirements Engineering (RE) for enterprise systems (ES) with a view to formulating current challenges and a promising research agenda for the future. In the field of ES, many RE approaches have been launched and tried out in the past decade, however most of them are over-expensive and their effectiveness is unpredictable. Our goal in this chapter is to make an inventory of the approaches discussed in literature, to evaluate the quality of evidence available regarding whether these approaches actually worked, and to identify promising directions for future RE research efforts. Our results indicate (i) that while there are significant achievements, the primary goal of RE for ES is only partly achieved and (ii) that the field is likely to remain very challenging due to the increasingly more pronounced cross-organizational aspects of RE in ES projects (e.g. cross-organizational coordination, trust). At the same time, the need for practical, efficient and effective RE approaches will grow as the importance of ES in today’s extended enterprises is growing.

In traditional software engineering research and practice, requirements are classified either as functional or non-functional. Functional requirements consist of all functions the system-to-be ought to support, and have been modeled in terms of box-and-arrow diagrams in the spirit of SADT. Non-functional requirements include desired software qualities for the system-to-be and have been described either in natural language or in terms of metrics. This orthodoxy was challenged in the mid-90 s by a host of proposals that had a common theme: all requirements are initially stakeholder goals and ought to be elicited, modeled and analyzed as such. Through systematic processes, these goals can be refined into specifications of functions the system-to-be needs to deliver, while actions assigned to external actors need to be executed. This view is dominating Requirements Engineering (RE) research and is beginning to have an impact on RE practice. We propose a next step along this line of research, by adopting the concept of conditional commitment as companion concept to that of goal. Goals are intentional entities that capture the needs and wants of stakeholders. Commitments, on the other hand, are social concepts that define the willingness and capability of an actor A to fulfill a predicate ϕ for the benefit of actor B, provided B (in return) fulfills predicate ψ for the benefit of actor A. In our conceptualization, goals are mapped to collections of commitments rather than functions, qualities, or actor assignments. We motivate the importance of the concept of commitment for RE through examples and discussion. We also contrast our proposal with state-of-the-art requirements modeling and analysis frameworks, such as KAOS, MAP, i ^* and Tropos.

Information systems are ubiquitous in our daily life. Thus, information systems need to work appropriately anywhere at any time for everybody. Conventional information systems engineering tends to engineer systems from the viewpoint of systems functionality. However, the diversity of the usage context requires fundamental change compared to our current thinking on information systems; from the functionality the systems provide to the goals the systems should achieve. The intentional approach embraces the goals and related aspects of the information systems. This chapter presents a method for capturing, structuring and reconciling diverse goals of multiple stakeholders. The heart of the method lies in the hierarchical structuring of goals by goal lattice based on the formal concept analysis, a semantic extension of the lattice theory. We illustrate the effectiveness of the presented method through application to the self-checkout systems for large-scale supermarkets.

The i ^* framework is a widespread formalism in the software engineering discipline that allows expressing intentionality of system actors. From the time it was issued, in the mid-90 s, a growing research community has adopted it either in its standard form or formulating variations in order to adapt it to some particular purpose. New methods, techniques and tools have made evolve the framework in a way that it may be currently considered quite mature from the scientific perspective. However, the i ^* framework has not been transferred to practitioners at the same extent yet: industrial experiences using i ^* are not many and have been mainly conducted by i ^* experts that are part of that very research community. Therefore, it may be argued that some steps are needed for boosting the adoption of i ^* by practitioners. In this chapter, we identify some scientific challenges whose overcoming could represent a step towards this goal. For each challenge, we present the problem that is addressed, its current state of the art and some envisaged lines of research.

In order to manage increasingly complex business and IT environments, organizations need effective instruments for representing and understanding this complexity. Essential among these instruments are enterprise models, i.e. computational representations of the structure, processes, information, resources, and intentions of organizations. One important class of enterprise models are value models, which focus on the business motivations and intentions behind business processes and describe them in terms of high level notions like actors, resources, and value exchanges. The essence of these value exchanges is often taken to be an ownership transfer. However, some value exchanges cannot be analyzed in this way, e.g. the use of a service does not influence ownership. The goal of this chapter is to offer an analysis of the notion of value exchanges, based on Hohfeld’s classification of rights, and to propose notation and practical modeling guidelines that make use of this analysis.

Enterprise Modeling (EM) has two main purposes: (1) Developing the business, which entails developing business vision, strategies, redesigning the way the business operates, developing the supporting information systems, etc., and (2) ensuring the quality of the business where the focus is on sharing the knowledge about the business, its vision and the way it operates, and ensuring the acceptance of business decisions through committing the stakeholders to the decisions made. In addition, EM has also shown to be useful as a general tool for articulating, discussing, and solving organizational problems. Based on a number of case studies, interviews and observations this chapter defines what is required from EM when adopted for these purposes and intentions respectively. More precisely, it addresses the following types of requirements: documents and models required as input, models that should be developed, requirements on the modeling language, requirements on the modeling process, tool requirements and model quality requirements. The defined requirements are then discussed taking a specific EM method, Enterprise Knowledge Development (EKD) as example.

Organizations constantly strive to improve their business performance; hence they make business process redesign efforts. So far, redesign has mainly been a human task, which relies on human reasoning and creativity, although various analysis tools can support it by identifying improvement opportunities. This chapter proposes an automated approach for learning from accumulated experience and improving business processes over time. The approach ties together three aspects of business processes: goals, context, and actual paths. It proposes a learning cycle, including a learning phase, where the relevant context is identified and used for making improvements in the process model, and a runtime application phase, where the improved process model is applied at runtime and actual results are stored for the next learning cycle. According to our approach, a goal-oriented process model is essential for learning to improve process outcomes.

In the context of Goal-Oriented Requirement Engineering (GORE) there are interesting modeling approaches for the analysis of complex scenarios that are oriented to obtain and represent the relevant requirements for the development of software products. However, the way to use these GORE models in an automated Model-Driven Development (MDD) process is not clear, and, in general terms, the translation of these models into the final software products is still manually performed. Therefore, in this chapter, we show an approach to automatically link GORE models and MDD processes, which has been elaborated by considering the experience obtained from linking the i ^* framework with an industrially applied MDD approach. The linking approach proposed is formulated by means of a generic process that is based on current modeling standards and technologies in order to facilitate its application for different MDD and GORE approaches. Special attention is paid to how this process generates appropriate model transformation mechanisms to automatically obtain MDD conceptual models from GORE models, and how it can be used to specify validation mechanisms to assure the correct model transformations.

Satisfiability is one of the properties that all conceptual schemas must have. Satisfiability applies to both the structural and the behavioral parts of a conceptual schema. Structurally, a conceptual schema is satisfiable if each base or derived entity and relationship type of the schema may have a non-empty population at certain time. Behaviorally, a conceptual schema is satisfiable if for each event type there is at least one consistent state of the information base and one event of that type with a set of characteristics such that the event constraints are satisfied, and the effects of the event leave the information base in a state that is consistent and satisfies the event postconditions. There has been a lot of work on automated reasoning procedures for checking satisfiability but it is well known that the problem of reasoning with integrity constraints and derivation rules in its full generality is undecidable. In this chapter, we explore an alternative approach to satisfiability checking, which can be used when conceptual schemas are developed in the context of an environment that allows their testing. The main contribution of this chapter is to show that when conceptual schemas can be tested then their satisfiability can be proved by testing.

Today, security concerns are at the heart of information systems, both at technological and organizational levels. With over 200 practitioner-oriented risk management methods and several academic security modelling frameworks available, a major challenge is to select the most suitable approach. Choice is made even more difficult by the absence of a real understanding of the security risk management domain and its ontology of related concepts. This chapter contributes to the emergence of such an ontology. It proposes and applies a rigorous approach to build an ontology, or domain model, of information system security risk management. The proposed domain model can then be used to compare, select or otherwise improve security risk management methods.

The methodological approaches to service design have started from extensions of conventional design methodologies and are moving towards more specific methods, which consider the complete service life cycle and the flexibility and adaptivity which are inherent in the use of services. In this chapter we discuss how an intentional perspective in service design can be helpful to increase the link between requirements and service construction and to make the development process more systematic.

Software Product Line Engineering (SPLE) is a reuse-driven development paradigm that has been applied successfully in information system engineering and other domains. Quality assurance of the reusable artifacts of the product line (e.g. requirements, design, and code artifacts) is essential for successful product line engineering. As those artifacts are reused in several products, a defect in a reusable artifact can affect several products of the product line. A central challenge for quality assurance in product line engineering is how to consider product line variability. Since the reusable artifacts contain variability, quality assurance techniques from single-system engineering cannot directly be applied to those artifacts. Therefore, different strategies and techniques have been developed for quality assurance in the presence of variability. In this chapter, we describe those strategies and discuss in more detail one of those strategies, the so called comprehensive strategy. The comprehensive strategy aims at checking the quality of all possible products of the product line and thus offers the highest benefits, since it is able to uncover defects in all possible products of the product line. However, the central challenge for applying the comprehensive strategy is the complexity that results from the product line variability and the large number of potential products of a product line. In this chapter, we present one concrete technique that we have developed to implement the comprehensive strategy that addresses this challenge. The technique is based on model checking technology and allows for a comprehensive verification of domain artifacts against temporal logic properties.

A method engineering approach is described for managing communication in RE processes based on Clark’s theory of common ground. The common ground framework is used to evaluate the affordances of different RE representations such as scenarios, storyboards and models. The contribution that representations make to RE activities is reviewed to suggest heuristics for selecting appropriate representations to develop mutual understanding of RE issues between different stakeholders. A meta-model for RE activities is proposed that describes the process of communication and developing mutual understanding driven from abstract and concrete views of the problem domain. The meta-model is applied to management of RE sessions from a method engineering perspective. Application of the framework is illustrated with a case study of health informatics application.