Duisburg, Universiẗat, Diss., 2002.

M.Sc. (Computer Science) / Since the late 1980's CASE ("Computer-Aided Software Engineering") is a common concept in the world of information technology. Nevertheless, many people in the information technology environment do not know what CASE is, or have different concepts about CASE. The author also found a variety of definitions for CASE in literature. This variety of concepts and definitions was the first problem the author investigated. Although many people know about CASE, companies are slow in adopting CASE and the tools are not used to their full potential. This was the second problem the author investigated. To address these problems, the research is divided in two logical parts. The author initiated this study with literature research regarding CASE in which the above mentioned problems were identified. The author found the solution to the first problem in literature and by attending CASE conferences. Guidelines to help with the second problem was derived from bits and pieces of information found in literature regarding the installation and use of CASE tools. It was also derived from practical experience during the last six months of study at a company busy with the installation of a CASE tool. To address the first problem, the different aspects surrounding CASE was investigated. The author tried to provide answers to the following questions: What is CASE? What is the logical components and functions of CASE? How can CASE be classified? CASE and integration - what is the difference between CASE, I-CASE and IPSE? Where does CASE fit in the software environment? In the last chapter of this first part, AD/Cycle from IBM (ISM in South Africa) is discussed as an industry standard for the CASE environment. To address the second problem, the author proposed a methodology covering the initiation phase to the maintenance phase of the implementation of CASE tools in a company. The methodology consists of four phases, namely, initiation, evaluation and selection, installation and training, and maintenance. In the initiation phase, the use of CASE tools to solve system development problems like the system backlog, bad productivity and poor system quality, are initiated. In the evaluation and selection phase, the different vendors and products on the market are evaluated against the needs of the company. The product which was the best suited for those needs was selected and acquired. In the installation and training phase, that product was installed in the information technology environment ...

M.Com. (Informatics) / Research into formalised methods for software engineering has resulted in many solutions to the known problems of software development. One of these problems is the difficulty involved In managing the cost of software development. Though attempts are made to solve the problem of budget and schedule overruns during project management, there still seems to be a lack of useful formal methods and approaches. In this dissertation such a formalised approach is presented. This approach Is based on the principle that cost should be actively managed just like any other aspect of software development. Within this framework the management of cost is defined as a process of identifying, estimating, measuring and controlling those factors that Influence the cost of development. Many methods exists through which the estimation of cost can be facilitated. The fact that such methods are available does not seem to solve the problem because cost management Involves more than just cost estimation. The research done to formalise this approach includes a discussion on the background of software engineering and the state of the science. It also includes an investigation Into the use of development metrics. The cost of software development is analyzed to determine the influence of different environmental factors on cost. A few estimation models are also discussed to determine the useability of such methods during cost management. A synopsis of how these subjects are covered In this dissertation is as follows: Chapter one serves as an Introduction to the research by giving a background to the development of software engineering. The limitations of current practices are emphasized and certain research questions are formulated. Chapter two discusses formal methods of development in the form of process models as a basis for the management of development cost. This chapter also analyzes development metrics as a method of measurement during development and cost management. The analysis provides as a framework for the identification and application of metrics during the process of cost management. Chapter three defines the extent of development cost and analyzes all factors contributing to the cost of software. The chapter discusses each of these factors by examining the possible influence of each on the effort of development and the Interdependence of these factors. Chapter four discusses a case study to be applied during discussions In the rest of the dissertation. Chapter five examines different approaches to the estimation of software development cost. The chapter serves as an introduction to subsequent chapters that deal with specific estimation models. Chapter six discusses an estimation model developed by Blokdijk. The chapter gives an overview of the principles Involved in and the application of the model.

This thesis proposes a novel approach, called Analogy-X to extend and improve the classical data-intensive analogy approach for software effort estimation. The Analogy-X approach combines the notions of distance matrix correlation found in ecology literature and statistic analysis techniques to provide useful inferential statistics to support analogy-based systems. Data-intensive analogy for software effort estimation has been proposed as a viable alternative to other prediction methods such as linear regression. In many cases, researchers found analogy outperformed algorithmic methods. However, the overall performance of analogy depends on the dataset quality or relevance of project cases to the target project, and the feature subset selected in the analogy-based model. Unfortunately, there is no mechanism to assess its appropriateness for a specific dataset, in most of the cases analogy will continue to execute regardless of the dataset quality. The Analogy-X approach is a set of procedures that utilize the principles of Mantel randomization test to provide inferential statistics to Analogy. Inspired by the Mantel correlation randomization test commonly used in ecology and psychology, Analogy-X uses the strength of correlation between the distance matrix of project features and the distance matrix of known effort values of the dataset to assess the suitability of the dataset for analogy, to identify the most appropriate feature subset, and to remove any atypical project cases from the dataset. The empirical studies show that Analogy-X is capable of: -- Detect extremely outlying project cases that will ultimately distort prediction outcomes using a sensitivity analysis strategy. -- Detect relevant project features that are useful to identify potential source analogues in a stepwise fashion similar to that of stepwise regression. -- Identifying whether analogy-based approach is appropriate for the dataset Analogy-X, thus is a robust solution, provides a sound statistical basis for analogy. It removes the need of using any forms of heuristic search and greatly improves its algorithmic performance. The studies also show that the Analogy-X approach is capable of removing the bottlenecks of performance in data-intensive analogy. The overall results obtained also suggest that a fully automated data-intensive analogy for software effort estimation can be implemented using the Analogy-X approach, and it is indeed an effective front end to analogy-based systems. The contribution of this work is significant since it provides an approach that will have major impact on the evolution of data-intensive analogy-based and case-based reasoning systems.

This thesis proposes a novel approach, called Analogy-X to extend and improve the classical data-intensive analogy approach for software effort estimation. The Analogy-X approach combines the notions of distance matrix correlation found in ecology literature and statistic analysis techniques to provide useful inferential statistics to support analogy-based systems. Data-intensive analogy for software effort estimation has been proposed as a viable alternative to other prediction methods such as linear regression. In many cases, researchers found analogy outperformed algorithmic methods. However, the overall performance of analogy depends on the dataset quality or relevance of project cases to the target project, and the feature subset selected in the analogy-based model. Unfortunately, there is no mechanism to assess its appropriateness for a specific dataset, in most of the cases analogy will continue to execute regardless of the dataset quality. The Analogy-X approach is a set of procedures that utilize the principles of Mantel randomization test to provide inferential statistics to Analogy. Inspired by the Mantel correlation randomization test commonly used in ecology and psychology, Analogy-X uses the strength of correlation between the distance matrix of project features and the distance matrix of known effort values of the dataset to assess the suitability of the dataset for analogy, to identify the most appropriate feature subset, and to remove any atypical project cases from the dataset. The empirical studies show that Analogy-X is capable of: -- Detect extremely outlying project cases that will ultimately distort prediction outcomes using a sensitivity analysis strategy. -- Detect relevant project features that are useful to identify potential source analogues in a stepwise fashion similar to that of stepwise regression. -- Identifying whether analogy-based approach is appropriate for the dataset Analogy-X, thus is a robust solution, provides a sound statistical basis for analogy. It removes the need of using any forms of heuristic search and greatly improves its algorithmic performance. The studies also show that the Analogy-X approach is capable of removing the bottlenecks of performance in data-intensive analogy. The overall results obtained also suggest that a fully automated data-intensive analogy for software effort estimation can be implemented using the Analogy-X approach, and it is indeed an effective front end to analogy-based systems. The contribution of this work is significant since it provides an approach that will have major impact on the evolution of data-intensive analogy-based and case-based reasoning systems.

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The principal purpose of the project is to enable ReMoTe support for multi-databases. ReMoTe stands for the Recursively Estimating Multi-Threaded Observation Technology Enterprise, which is a web-based computer aided software engineering tool for monitoring software development process. Development of ReMoTe is based on the RMT (Recursive Multi-Threaded) software life cycle developed by Scott Simon, a CSUSB alum, in his master's thesis in 1997. ReMoTe enables the monitoring of projects that use different databases in various locations. Central management can view the progress information of each project using a web browser no matter where the database or project team is located. In this project, three database software were supported, namely MySQL, Oracle, and Microsoft Access, and employed contemporary technologies such as JavaScript, PHP, and Open Database Connectivity (ODBC). Source codes are included.

M.Sc. (Computer Science) / This study addresses the topic of integration between CASE tools and software engineering methodologies. Specific attention is given to the object-oriented paradigm to solve the problem of integration. The component developed in this study to handle the integration is the so-called feedback loop mechanism. The feedback loop is the focus of the study. A number of CASE tools are available today. These tools help developers achieve specific aims and to solve specific problems. Similarly, a number of different software development methodologies abound. Due to the fact that these methodologies are usually not specific to the use of CASE tools, these methodologies can be used for a variety of development environments. The problem addressed by this study is the direct integration of CASE tools and software engineering methodologies. A number of studies have been carried out with regard to both CASE tools and software engineering methodologies. A discussion of current trends in both the CASE tool and methodology arenas is presented at the beginning of this study. Also, the problems experienced with more traditional approaches are discussed. Given that the feedback loop mechanism is developed during the course of this study, a detailed discussion is presented regarding the components to be used in the construction of the feedback loop. The object-oriented paradigm is presented as the best solution to the integration problem. In fact, the object-oriented paradigm forms the core of the feedback loop. By making use of the object-oriented approach, the processes involved in the integration of the CASE tool and the methodology may be mapped accurately. Repository structures such as relational tables and stored procedures, or triggers, are also used in the construction of the feedback loop...

<p>Researchers have developed framework for diagnosis analysis that are called “Model Based Diagnosis Systems”. These systems are very general in scope, covers a wide range of malfunctions uncovering and identifying repair measures. This thesis is an effort to diagnose complex and lengthy static source code. Without executing source code discrepancies can only be identified by finding procedural dependencies.</p><p>With respect to modern programming languages, many software bugs arise due to logical erroneous calculations or miss handling of data structures. Modern Integrated Development Environments (IDE) like Visual Studio, J-Builder and Eclipse etc are strong enough to analyze and parse static text code to identify syntactical and type conversion errors. Some of IDE’s can automatically fix such kind of errors or provide different possible suggestions to developer.</p><p>In this thesis we have analyzed and extracted functional dependencies of source code. This extracted information can increase programmer’s understanding about code when they are extremely large or complex. By modeling this information into a model system, reduces time to debug the code in case of any failure. This increases productivity in terms of software development and in debugger skills as well. The main contribution of this thesis is the use of model based diagnosis techniques on software functional dependency graphs and charts.</p><p>Keywords: Model Based Diagnosis Systems, Integrated Development Environments, Procedural Dependencies, Erroneous calculations, Call graphs, Directed graph markup language.</p>

Context: The need for empirical investigations in software engineering domain is growing immensely. Many researchers nowadays, conduct and validate their study using empirical evidences. Survey is one such empirical investigation method which enables researchers to collect data from the large population. Main aim of the survey is to generalize the findings. Many problems are faced by the researchers in the survey process. Survey outcomes also depend upon variables like sample size, response rate and analysis techniques. Hence there is need for the literature addressing all the possible problems faced and also the impact of survey variables on outcomes. Objectives: Firstly, to identify the common problems faced by the researchers from the existing literature and also analyze the impact of the survey variables. Secondly to collect the experiences of software engineering researchers regarding the problems faced and the survey variables. Finally come up with a checklist of all the problems and mitigation strategies along with the information about the impact of survey variables. Methods: Initially a systematic literature review was conducted, to identify the existing problems in the literature and to know the effect of response rate, sample size, analysis techniques on survey outcomes. Then systematic literature review results were validated by conducting semi-structured, faceto-face interviews with software engineering researchers. Results: We were successful in providing a checklist of problems along with their mitigation strategies. The survey variables dependency on type of research, researcher’s choices limited us from further analyzing their impact on survey outcomes. The face-to-face interviews with software engineering researchers provided validations to our research results. Conclusions: This research gave us deeper insights into the survey methodology. It helped us to explore the differences that exists between the state of art and state of practice towards problem mitigation in survey process.