David E. Monarchi

Theoretical foundations for conceptual modelling in information systems development

Conceptual modelling in information systems development is the creation of an enterprise model for the purpose of designing the information system. It is an important aspect of systems analysis. The value of a conceptual modelling language (CML) lies in its ability to capture the relevant knowledge about a domain. To determine which constructs should be included in a CML it would be beneficial to use some theoretical guidelines. However, this is usually not done. The purpose of this paper is to promote the idea that theories related to human knowledge can be used as foundations for conceptual modelling in systems development. We suggest the use of ontology, concept theory, and speech act theory. These approaches were chosen because: (1) they deal with important and different aspects relevant to conceptual modelling and (2) they have already been used in the context of systems analysis. For each approach we discuss: the rationale for its use, its principles, its application to conceptual modelling, and its limitations. We also demonstrate the concepts of the three approaches by analysing an example. The analysis also serves to show how each approach deals with different aspects of modelling.

A software complexity model of object-oriented systems

Abstract A model for the emerging area of software complexity measurement of OO systems is required for the integration of measures defined by various researchers and to provide a framework for continued investigation. We present a model, based in the literature of OO systems and software complexity for structured systems. The model defines the software complexity of OO systems at the variable, method, object, and system levels. At each level, measures are identified that account for the cohesion and coupling aspects of the system. Users of OO techniques perceptions of complexity provide support for the levels and measures.

Effectiveness of traditional software metrics for object-oriented systems

An acceptable measure of software quality must quantify software complexity. Traditional software metrics such as lines of code, software science and cyclomatic complexity are investigated as possible indicators of complexity of object-oriented systems. This research reports the effects of polymorphism and inheritance on the complexity of object-oriented systems are measured by the traditional metrics. The results of this research indicate that traditional metrics are applicable to the measurement of the complexity of object-oriented systems.<<ETX>>

Analyzing unstructured text data: Using latent categorization to identify intellectual communities in information systems

The Information Systems field is structured by the research topics emphasized by communities of journals. The Latent Categorization Method categorized and automatically named IS research topics in 14,510 abstracts from 65 Information Systems journals. These topics were clustered into seven intellectual communities based on publication patterns. The technique develops categories from the data itself, it is replicable, is relatively insensitive to the size of the text units, and it avoids many of the problems that frequently accompany human categorization. As such LCM provides a new approach to analyzing a wide array of textual data.

A Mathematical Approach to Categorization and Labeling of Qualitative Data: the Latent Categorization Method

As text databases increasingly become available to researchers, the limits to human cognition are rapidly reached. Focusing on examining objective realities, this paper introduces the latent categorization method, a novel new research method for analysis of large and midsize data sets. This method clusters text artifacts and extracts the words that were most important in creating the clusters. Further, it demonstrates a set of techniques for extracting knowledge from a representative data set involving 6135 abstracts from a variety of business-related journals.

Ensuring the quality of conceptual representations

High quality data and process representations are critical to the success of system development efforts. Despite this importance, quantitative methods for evaluating the quality of a representation are virtually nonexistent. This is a major shortcoming. However, there is another approach. Instead of evaluating the quality of the final representation, the representation process itself can be evaluated. This paper views the modeling process as a communication channel. In a good communication channel, sufficient error prevention, error detection, and error correction mechanisms exist to ensure that the output message matches the input message. A good modeling process will also have mechanisms for preventing, detecting, and correcting errors at each step from observation to elicitation to analysis to final representation. This paper describes a theoretically-based set of best practices for ensuring that each step of the process is performed correctly, followed by a proof of concept experiment demonstrating the utility of the method for producing a representation that closely reflects the real world.

An Interactive Multiple Objective Decision-Making Aid Using Nonlinear Goal Programming

A nonlinear goal programming approach is embedded within an interactive framework allowing the decision maker to direct the algorithm’s search for a satisfactory alternative. Particular consideration has been given to the psychological assumptions required in this approach, especially the Gestalt nature of perception, the information-dependent nature of acceptability, and the serial aspects of the selection process.

Methodology standards: help or hindrance?

Over the last 12 months there has been growing interest in the possible “standardization” and/or “convergence” of object-oriented analysis and design methodologies. The key issues discussed by the panellists focus on whether standardization NOW is to be encouraged or resisted whether standards are a help or a hindrance to the further maturation of 00 methodologies. Each panellist has been closely associated with the development of an 00 lifecycle methodology. Some of the issues raised include:

Journeys up the mountain: Different paths to learning object-oriented programming

Abstract Among the challenges facing companies transitioning from structured to object-oriented (OO) programming is how (and whether) to retrain existing procedural programmers. Common wisdom has it that old-time programmers can be retrained in object technology only with great difficulty, but new programmers lack experience building large systems and the knowledge of the business. This paper describes a study of students learning OO programming where the participants ranged in experience from a single semester of programming to over 10 years of professional programming. The purpose of this study was to explore how students learn OO programming by observing them between their first exposure to OO programming and the time they finally “get it.” We identified five categories of learners who each took a different path to learning OO programming, encountered different obstacles, and adopted different learning strategies. We describe some factors that may play a part in helping and/or hindering a students progress and that may be used to predict a students learning category. We conclude with suggestions for alternative training program strategies that may be appropriate for each category and with directions for future research.

Performance of the Durbin-Watson Test and WLS Estimation When the Disturbance Term Includes Serial Dependence in Addition to First-Order Autocorrelation

Abstract Monte Carlo simulation is used to study the power of the Durbin-Watson test and the properties of the corresponding weighted least squares (WLS) estimates when there is serial correlation in the disturbance term, in addition to first-order autocorrelation. The results indicate that the Durbin-Watson test detects first-order autocorrelation, even when other forms of serial dependence are also present. However, routine use of WLS estimation when the Durbin-Watson test is significant may result in inaccurate and inefficient parameter estimates. Therefore, this procedure should be used with caution unless there is a priori knowledge concerning the nature of any serial dependence in the disturbance terms.