A general framework for positioning, evaluating and selecting the new generation of development tools.

This paper focuses on the evaluation and positioning of a new generation of development tools containing subtools (report generators, browsers, debuggers, GUI-builders, ...) and programming languages that are designed to work together and have a common graphical user interface and are therefore called environments. Several trends in IT have led to a pluriform range of developments tools that can be classified in numerous categories. Examples are: object-oriented tools, GUI-tools, upper- and lower CASE-tools, client/server tools and 4GL environments. This classification does not sufficiently cover the tools subject in this paper for the simple reason that only one criterion is used to distinguish them. Modern visual development environments often fit in several categories because to a certain extent, several criteria can be applied to evaluate them. In this study, we will offer a broad classification scheme with which tools can be positioned and which can be refined through further research.

AUTOMATING OUTPUT SIZE AND REUSABILITY METRICS IN AN OBJECT-BASED COMPUTER AIDED SOFTWARE ENGINEERING (CASE) ENVIRONMENT

Measurement of software development productivity is needed in order to control software costs, but it is discouragingly labor-intensive and expensive. Computer aided software engineering (CASE) technologies -- especially object-oriented, integrated CASE -- have the potential to support the automation of this measurement. In this paper, we discuss the conceptual development of automated analyzers for function point and software reusability measurement for object-based CASE. Both analyzers take advantage of the existence of a representation of the application system that is stored within an object repository, and that contains the necessary information about the application system. We also propose new metrics for software reusability measurement, including reuse leverage, reuse value and reuse classification. The functionality and analytic capabilities of state-of-the-art automated software metrics analyzers are illustrated in the context of an investment banking industry application.Information Systems Working Papers Serie

AUTOMATING OUTPUT SIZE AND REUSE METRICS IN A REPOSITORY-BASED COMPUTER AIDED SOFTWARE ENGINEERING (CASE) ENVIRONMENT

Measurement of software development productivity is needed in order to control software costs, but it is discouragingly labor-intensive and expensive. Computer aided software engineering (CASE) technologies -- especially repository-based, integrated CASE -- have the potential to support the automation of this measurement. In this paper, we discuss the development of automated analyzers for function point and software reuse measurement for object-based CASE. Both analyzers take advantage of the existence of a representation of the application system that is stored within an object repository, and that contains the necessary information about the application system. We also discuss metrics for software reuse measurement, including reuse leverage, reuse value and reuse classification, that are motivated by managerial requirements and the efforts, within industry and the IEEE, to standardize measurement. The functionality and the analytical capabilities of state-of-the-art automated software metrics analyzers are illustrated in the context of an investment banking industry application, that is similar to systems deployed at the New York City-based investment bank where these tools were developed and tested.Information Systems Working Papers Serie

AUTOMATING OUTPUT SIZE AND REUSE METRICS IN A REPOSITORY-BASED COMPUTER AIDED SOFTWARE ENGINEERING (CASE) ENVIRONMENT

Measurement of software development productivity is needed in order to control software costs, but it is discouragingly labor-intensive and expensive. Computer aided software engineering (CASE) technologies -- especially repository-based, integrated CASE -- have the potential to support the automation of this measurement. In this paper, we discuss the development of automated analyzers for function point and software reuse measurement for object-based CASE. Both analyzers take advantage of the existence of a representation of the application system that is stored within an object repository, and that contains the necessary information about the application system. We also discuss metrics for software reuse measurement, including reuse leverage, reuse value and reuse classification, that are motivated by managerial requirements and the efforts, within industry and the IEEE, to standardize measurement. The functionality and the analytical capabilities of state-of-the-art automated software metrics analyzers are illustrated in the context of an investment banking industry application, that is similar to systems deployed at the New York City-based investment bank where these tools were developed and tested.Information Systems Working Papers Serie

AUTOMATING SOFTWARE DEVELOPMENT PRODUCTIVITY METRICS

Measurement of software development productivity is needed in order to control software costs, but it is discouragingly labor-intensive and expensive. Computer aided software engineering (CASE) technologies -- especially object-oriented, integrated CASE -- have the potential to support the automation of this measurement. In this paper, we describe automated analyzers for function point and code reuse measurement. Both analyzers take advantage of the existence of a meta-model of the application system, stored within an object repository, which contains the necessary information about the application system. We also propose new metrics for code reuse analysis, including reuse leverage, reuse value and reuse classification. The state-of-the-art automated software metrics analyzers are illustrated in the context of an investment banking industry application.Information Systems Working Papers Serie

A new estimation methodology for reusable component-based software development projects

Bibliograhy: leaves 118-121.Estimating the duration of software development projects is a difficult task. There are many factors that can derail software projects. However, estimation forms the fundamental part of planning and costing any project and is therefore very necessary. While several formal estimation methodologies exist, they all exhibit weaknesses in one form or another. The most established methodologies are based on early software development methods and it is questionable as to whether they can still address more modern development methods such as reusable component-based programming. Some researchers believe not and have proposed new methodologies that attempt to achieve this. Thus what is needed is a methodology that takes into account modern component-based development practices and, as a result, provides acceptable accuracy for the software organisation. This dissertation attempts to uniquely satisfy both of these requirements

Pragmatic cost estimation for web applications

Cost estimation for web applications is an interesting and difficult challenge for researchers and industrial practitioners. It is a particularly valuable area of ongoing commercial research. Attaining on accurate cost estimation for web applications is an essential element in being able to provide competitive bids and remaining successful in the market. The development of prediction techniques over thirty years ago has contributed to several different strategies. Unfortunately there is no collective evidence to give substantial advice or guidance for industrial practitioners. Therefore to address this problem, this thesis shows the way by investigating the characteristics of the dataset by combining the literature review and industrial survey findings. The results of the systematic literature review, industrial survey and an initial investigation, have led to an understanding that dataset characteristics may influence the cost estimation prediction techniques. From this, an investigation was carried out on dataset characteristics. However, in the attempt to structure the characteristics of dataset it was found not to be practical or easy to get a defined structure of dataset characteristics to use as a basis for prediction model selection. Therefore the thesis develops a pragmatic cost estimation strategy based on collected advice and general sound practice in cost estimation. The strategy is composed of the following five steps: test whether the predictions are better than the means of the dataset; test the predictions using accuracy measures such as MMRE, Pred and MAE knowing their strengths and weaknesses; investigate the prediction models formed to see if they are sensible and reasonable model; perform significance testing on the predictions; and get the effect size to establish preference relations of prediction models. The results from this pragmatic cost estimation strategy give not only advice on several techniques to choose from, but also give reliable results. Practitioners can be more confident about the estimation that is given by following this pragmatic cost estimation strategy. It can be concluded that the practitioners should focus on the best strategy to apply in cost estimation rather than focusing on the best techniques. Therefore, this pragmatic cost estimation strategy could help researchers and practitioners to get reliable results. The improvement and replication of this strategy over time will produce much more useful and trusted results.Cost estimation for web applications is an interesting and difficult challenge for researchers and industrial practitioners. It is a particularly valuable area of ongoing commercial research. Attaining on accurate cost estimation for web applications is an essential element in being able to provide competitive bids and remaining successful in the market. The development of prediction techniques over thirty years ago has contributed to several different strategies. Unfortunately there is no collective evidence to give substantial advice or guidance for industrial practitioners. Therefore to address this problem, this thesis shows the way by investigating the characteristics of the dataset by combining the literature review and industrial survey findings. The results of the systematic literature review, industrial survey and an initial investigation, have led to an understanding that dataset characteristics may influence the cost estimation prediction techniques. From this, an investigation was carried out on dataset characteristics. However, in the attempt to structure the characteristics of dataset it was found not to be practical or easy to get a defined structure of dataset characteristics to use as a basis for prediction model selection. Therefore the thesis develops a pragmatic cost estimation strategy based on collected advice and general sound practice in cost estimation. The strategy is composed of the following five steps: test whether the predictions are better than the means of the dataset; test the predictions using accuracy measures such as MMRE, Pred and MAE knowing their strengths and weaknesses; investigate the prediction models formed to see if they are sensible and reasonable model; perform significance testing on the predictions; and get the effect size to establish preference relations of prediction models. The results from this pragmatic cost estimation strategy give not only advice on several techniques to choose from, but also give reliable results. Practitioners can be more confident about the estimation that is given by following this pragmatic cost estimation strategy. It can be concluded that the practitioners should focus on the best strategy to apply in cost estimation rather than focusing on the best techniques. Therefore, this pragmatic cost estimation strategy could help researchers and practitioners to get reliable results. The improvement and replication of this strategy over time will produce much more useful and trusted results

Software metrics for monitoring software engineering projects

As part of the undergraduate course offered by Edith Cowan University, the Department of Computer Science has (as part of a year\u27s study) a software engineering group project. The structure of this project was divided into two units, Software Engineering l and Software Engineering 2. ln Software Engineering 1, students were given the group project where they had to complete and submit the Functional Requirement and Detail System Design documentation. In Software Engineering 2, students commenced with the implementation of the software, testing and documentation. The software was then submitted for assessment and presented to the client. To aid the students with the development of the software, the department had adopted EXECOM\u27s APT methodology as its standard guideline. Furthermore, the students were divided into groups of 4 to 5, each group working on the same problem. A staff adviser was assigned to each project group. The purpose of this research exercise was to fulfil two objectives. The first objective was to ascertain whether there is a need to improve the final year software engineering project for future students by enhancing any aspect that may be regarded as deficient. The second objective was to ascertain the factors that have the most impact on the quality of the delivered software. The quality of the delivered software was measured using a variety of software metrics. Measurement of software has mostly been ignored until recently or used without true understanding of its purpose. A subsidiary objective was to gain an understanding of the worth of software measurement in the student environment One of the conclusions derived from the study suggests that teams who spent more time on software design and testing, tended to produce better quality software with less defects. The study also showed that adherence to the APT methodology led to the project being on schedule and general team satisfaction with the project management. One of the recommendations made to the project co-ordinator was that staff advisers should have sufficient knowledge of the software engineering process