(kein Abstract vorhanden) / Series: Schriftenreihe des Instituts für Transportwirtschaft und Logistik - Supply Chain Management

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Bachelor-Arbeit Univ. St. Gallen, 2005.

M.Sc. (Computer Science) / The data processing crisis in software development today can be ascribed firstly to insufficient requirements defmition, which results from a lack of communication between developer and user, and secondly to insufficient project management. During the last decade we succeeded in adding more control and discipline to the traditional software development life cycle, but requirements specification remains a problem. The traditional software development life-cycle is long and inflexible and the results do not satisfy the requirements of the user. The prototyping approach can be part of a solution to the problems posed by this situation. The author proposes a four-dimensional conceptual model as a framework for a Prototyping methodology that was developed as basis for this study. In business practice today, confusion exists as to what prototypes are the best to use - prototypes that are developed to become the complete system, or prototypes that are thrown away. Dimension one of the model is discussed in terms of type of prototype. With type of prototype is meant one of the different approaches to prototyping in the software development process. The author standardized on throw-away prototypes and evolutionary prototypes. The most general and well-known usage of prototyping is during the requirements :definition phase. However, this is not the only use of prototyping. Dimension two of the model describes the different areas of usage of prototyping, e.g. requirements definition, as technique during JAD sessions, during simulation, during the minimizing of risk and in the development of working models. The development of prototypes should be an easy and rapid process, however, this is dependent on the tools that are used in the process. Dimension three of the model is discussed in terms of tools.

The Software Engineering Research Center (SERC) Design Metrics Research Team at Ball State University has developed a design metric D(G) of the form:D(G) = D~ + DiWhere De is the architectural design metric (external design metric) and D; is the detailed design metric (internal design metric).Questions to be investigated in this thesis are:Why can D, be an indicator of the potential error modules?Why can D; be an indicator of the potential error modules?Are there any significant factors that dominate the design metrics?In this thesis, the report of the STANFINS data is evaluated by using correlation analysis, regression analysis, and several other statistical techiques. The STANFINS study is chosen because it contains approximately 532 programs, 3,000 packages and 2,500,000 lines of Ada.The design metrics study was completed on 21 programs (approximately 24,000 lines of code) which were selected by CSC development teams. Error reports were also provided by CSC personnel. / Department of Computer Science

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This study has presented a new model for predicting software reliability based on design metrics. An introduction to the problem of software reliability is followed by a brief overview of software reliability models. A description of the models is given, including a discussion of some of the issues associated with them. The intractability of validating life-critical software is presented. Such validation is shown to require extended periods of test time that are impractical in real world situations. This problem is also inherent in fault tolerant software systems of the type currently being implemented in critical applications today. The design metrics developed at Ball State University is proposed as the basis of a new model for predicting software reliability from information available during the design phase of development. The thesis investigates the proposition that a relationship exists between the design metric D(G) and the errors that are found in the field. A study, performed on a subset of a large defense software system, discovered evidence to support the proposition. / Department of Computer Science

Effective software engineering techniques are needed to increase the reliability of software systems, to increase the productivity of development teams, and to reduce the costs of software development. Companies search for an effective software engineering process as they strive to reach higher process maturity levels and produce better software. To aid in this quest for better methods of software engineering. the Design Metrics Research Team at Ball State University has analyzed university and industry software to be able to detect error-prone modules. The research team has developed, tested and validated their design metrics and found them to be highly successful. These metrics were typically collected and calculated by hand. So that these metrics can be collected more consistently, more accurately and faster, the Design Metrics Analyzer for Ada (DMA) was created. The DMA collects metrics from the files submitted based on a subprogram level. The metrics results are then analyzed to yield a list of stress points, which are modules that are considered to be error-prone or difficult for developers. This thesis describes the Design Metrics Analyzer, explains its output and how it functions. Also, ways that the DMA can be used in the software development life cycle are discussed. / Department of Computer Science

The Design Metrics Research Team in the Computer Science Department at Ball State University has been engaged in developing and validating quality design metrics since 1987. Since then a number of design metrics have been developed and validated. One of the design metrics developed by the research team is design balance (DB). This thesis is an attempt to validate the metric DB. In this thesis, results of the analysis of five systems are presented. The main objective of this research is to examine if DB can be used to evaluate the complexity of a software design and hence the quality of the resulting software. Two of the five systems analyzed were student projects and the remaining three were from industry. The five systems analyzed were written in different languages, had different sizes and exhibited different error rates. / Department of Computer Science