Showing papers by "Daniel Rodriguez published in 2002"

A generic model and tool support for assessing and improving Web processes

Abstract: We discuss a generic quality framework, based on a generic model, for evaluating Web processes. The aim is to perform assessment and improvement of web processes by using techniques from empirical software engineering. A web development process can be broadly classified into two almost independent sub-processes: the authoring process (AUTH process) and the process of developing the infrastructure (INF process). The AUTH process concerns the creation and management of the contents of a set of nodes and the way they are linked to produce a web application, whereas the INF development process provides technological support and involves creation of databases, integration of the web application to legacy systems etc. In this paper, we instantiate our generic quality model to the AUTH process and present a measurement framework for this process. We also present a tool support to provide effective guidance to software personnel including developers, managers and quality assurance engineers.

Generation of Management Rules through System Dynamics and Evolutionary Computation

Abstract: Decision making has been traditionally based on a managers experience. This paper, however, discusses how a software project simulator based on System Dynamics and Evolutionary Computation can be combined to obtain management rules. The purpose is to provide accurate decision rules to help project managers to make decisions at any time in the software development life cycle. To do so, a database from which management rules are generated is obtained using a software project simulator based on system dynamics. We then find approximate optimal management rules using an evolutionary algorithm which implements a novel method for encoding the individuals, i.e., management rules to be searched by the algorithm. The resulting management rules of our method are also compared with the ones obtained by another algorithm called C4.5. Results show that our evolutionary approach produces better management decision rules regarding quality and understandability.

Maintenance of object oriented systems through re-engineering: a case study

Abstract: Unregulated evolution of software often leads to software ageing which not only makes the product difficult to maintain but also breaks the consistency between design and implementation. In such a case, it may become necessary to re-engineer the software so that it becomes maintainable again. In this paper we present the case study of the reengineering of the People Tracking subsystem of a surveillance system written in C++. We discuss the problems, the challenges and the approaches taken, and we show how the re-engineered product is now better maintainable. We also discuss the generation of the relevant artefacts - from requirement document through to design document.

An investigation of prediction models for project management

Abstract: It has been claimed that dynamic prediction models can be used to help project managers make more accurate estimates than static prediction models. However, such a claim needs to be validated so that project managers can use dynamic models with confidence. In this paper we discuss an experiment we conducted in an academic environment that compared a dynamic model using Bayesian belief networks (BBN) with a static model involving the COCOMO and Akiyama models. The results from this experiment in fact validate the above claim. However we suggest replication of this experiment in order to increase confidence to our results.

Generation of management rules through System Dynamics and Evolutionary Computation

Abstract: Decision making has been traditionally based on a managers experience. This paper, however, discusses how a software project simulator based on System Dynamics and Evolutionary Computation can be combined to obtain management rules. The purpose is to provide accurate decision rules to help project managers to make decisions at any time in the software development life cycle. To do so, a database from which management rules are generated is obtained using a software project simulator based on system dynamics. We then find approximate optimal management rules using an evolutionary algorithm which implements a novel method for encoding the individuals, i.e., management rules to be searched by the algorithm. The resulting management rules of our method are also compared with the ones obtained by another algorithm called C4.5. Results show that our evolutionary approach produces better management decision rules regarding quality and understandability.