Steps Towards a Method for the Formal Modeling of Dynamic Objects

Fragments of a method to formally specify object-oriented models of a universe of discourse are presented. The task of finding such models is divided into three subtasks, object classification, event specification, and the specification of the life cycle of an object. Each of these subtasks is further subdivided, and for each of the subtasks heuristics are given that can aid the analyst in deciding how to represent a particular aspect of the real world. The main sources of inspiration are Jackson System Development, algebraic specification of data- and object types, and algebraic specification of processes

MEASURING APPLICATION DOMAIN KNOWLEDGE: RESULTS FROM A PRELIMINARY EXPERIMENT

Conceptual models are used in IS development for capturing and specifying requirements. However, the mere understanding of the syntax or semantics of a modeling language is not the most crucial factor. More relevant is pragmatic knowledge about the application domain. The problem that this paper addresses is how one can verify that a shared understanding of the application domain exists. In our study we show that domain-specific languages are an indicator for separating novices from experts in a given application domain. Novices and experts can be distinguished based on the domain-specific language they use. We demonstrate that these different language communities can be observed empirically by employing latent semantic analysis (LSA) as an instrument and by measuring semantic similarity. The separation of groups using LSA is also possible if the terminology, the application domain, or the expert-layperson-status of the examined group are unknown. Therefore the separation based on domain-specific languages is independent of the domain under consideration or the prior knowledge of the researcher. This provides a useful measurement instrument for studying the role of application domain knowledge in future research

A method for building and evaluating formal specifications of object-oriented conceptual models of database systems

This report describes a method called MCM (Method for Conceptual Modeling) for building and evaluating formal specifications of object-oriented models of database system behavior. An important aim of MCM is to bridge the gap between formal specification and informal understanding. Building a MCM model is a process that moves from the informal to the formal, evaluating the model is a process that moves back from the formal to the informal. First, a general framework for information system development methods is given, that is used to indicate which elements are needed to build a particular information system development method. In general, the following elements are needed (see figure 0.1) l. Requirements determination methods that can be used to determine the information needs of the environment, and to find functional and nonfunctional requirements specifications. 2. Conceptual modeling methods that can be used to elaborate the statement of functional require­ ments into a formal specification of observable system behavior. 3. Implementation methods that can be used to transform the conceptual model specification into an implementation within the constraints indicated by the nonfunctional requirements. 4. Project management methods that can be used to manage the development process in the presence of limited resources and a potentially disturbing environment. MCM is a conceptual modeling method, and must therefore in any information system development project be supplemented with three other kinds of methods. MCM contains three kinds of methods (figure 0.1). 1. Observation methods to find relevant data about the required database system. 2. Induction methods that allow one to go from a finite set of data about required system behavior to a conceptual model that represents all of this behavior. 3. Evaluation methods that allow one to test the quality of a specification of a conceptual model. In this report, I concentrate on induction and evaluation methods and merely make a list of relevant observation methods. The induction methods listed in figure 0.1 are not exhaustive. MCM can be viewed as a framework within which methods and techniques for conceptual modeling can be plugged. Some of these methods and techniques are mentioned in this report but not elaborated. There are three kinds of evaluation methods, that deal with the validity of the conceptual model, the utility of the specified behavior, and the quality of the use that is made of the available modeling constructs. Prototyping and animation are briefly discussed as evaluation methods. The quality checks, however, are listed exhaustively. The result of following MCM is a conceptual model. In the philosophy of MCM, a conceptual model consists of three components (see figure 0.2): 1. The UoD model is a model of the part of reality represented by the database system. 2. The DBS model represents DBS behavior, such as the queries to be asked from the DBS, the user interface, the contents and layout of reports produced by the DBS, etc. 3. A model of the boundary between the DBS and the UoD. This is a list of all possible transactions that the DBS can engage in, plus the function that this behavior has for the user of the DBS

OBTENCIÓN DE CONOCIMIENTO EMPÍRICO SOBRE LA CALIDAD DE CASOS DE USO

Estudio secundario empírico diseñado para identificar qué aspectos de los Casos de Uso son evaluados, así como el formato de descripción y el dominio donde son experimentados.Ferrando Moragues, JA. (2010). OBTENCIÓN DE CONOCIMIENTO EMPÍRICO SOBRE LA CALIDAD DE CASOS DE USO. http://hdl.handle.net/10251/13970Archivo delegad

Three Roles of Conceptual Models in Information System Design and Use

This paper attempts to draw together results from information systems\ud research, linguistic theory, and methodology in order to present a unified\ud framework in which to understand conceptual models. Three different roles\ud of conceptual models (CM's) in the design and use of information systems\ud (IS's) are investigated. The descriptive role of a CM is that it is an abstract\ud representation of the universe of discourse (UoD) of the IS; the normative\ud role of a CM is that it contains prescriptions for the behavior of entities in the UoD. A third role of CM's emerges when a computer is viewed as a\ud symbol-manipulating machine capable of performing speech acts like commanding and promising. These acts are commands or promises only against a background of shared conventions, which is stored in a shared CM. A CM playing this role is called institutional. This paper is an abstract of Wieringa [1989]