Catálogo de publicaciones - libros

The complex nature of the software development paradigm and the rapid acceptance of emerging abstraction mechanisms, such as agent-oriented and service-oriented computing, highlight the increasing need for re-evaluation of existing software development approaches that focus on agile software de-velopment methodologies (primarily originating in object-oriented technology); since existing object-oriented, structure-oriented and component-oriented approaches embodied in an agile approach cannot be applied immediately to agent and service-oriented computing. Therefore, we present here, an agile toolkit (Java-based) to facilitate the construction of multi-abstraction or m-abstraction situation-specific agile processes for software development projects. This paper only presents the newly emergent abstraction concepts of agent and service, and does not discuss the well-established object-oriented mechanism used in current agile approaches.

Supply chain management is comprehensive software. Due to its scope and unpredictable, complex and unstable requirements, it is not possible to develop it with predictable development process models. Agile methodologies are targeted towards such kind of problems that involves change and uncertainty, and are adaptive rather than predictive. The aim of this paper is to analyze the management and development methodologies used in development of supply chain management software. This paper shows how to overcome risks and handicaps in each development phase of a complex inventive project. It also provides a set of guidelines regarding how the agile methods may be adopted, combined and used in these kinds of projects.

Implementing a measurement program is not an easy task. It requires effort, resources, budget, experts in the field, etc. The challenges to successfully implement a measurement program in small settings are considerable and greater than in large companies. Small and medium-sized enterprises (SMEs) have an additional handicap: the existing methods and frameworks that support measurement programs such as Goal Question Metric (GQM), Goal-Driven Software Measurement, GQ(I)M, PSM and ISO/IEC 15939 do not fully satisfy the needs of such companies. We propose MIS-PyME, a methodological framework which supports small and medium enterprises (SMEs) in establishing software measurement programs, especially as regards the definition of software indicators. MIS-PyME is based on GQ(I)M and aims at supporting SMEs measurement activities related to software process improvement tasks. This framework has been applied in STL, where the main benefit derived from the use of MIS-PyME has been an effortless, more accurate program definition integrated into software process improvement practices.

In software life cycle models traditionally the main attention is being paid to the software development, including requirement gathering (specification), design, implementation and testing. Less research is devoted to the system maintenance and operation despite the fact that these aspects take up the main part of the duration of a successful system. In the paper smart technologies are being analysed – architectural designs and software components which using meta information on system and its usage conditions are able to solve efficiently the problems of maintenance and usage: data quality and performance monitoring, software flexibility and testability, context dependant user interface. The advantages of smart technology usage are pointed out helping to improve software maintenance and operation processes.

Since 1984 the International Function Point Users Group (IFPUG) has produced and maintained a set of standards and technical documents about a functional size measurement methods, known as IFPUG, based on Albrecht Fuction Points. On the other hand, in 1998, the Common Software Measurement International Consortium (COSMIC) proposed an improved measurement method known as Full Function Points (FFP). Both the IFPUG and the COSMIC methods both measure functional size of software, but produce different results. In this paper, we propose a model to convert functional size measures obtained with the IFPUG method to the corresponding COSMIC measures. We also present the validation of the model using 33 software projects measured with both methods. This approach may be beneficial to companies using both methods or migrating to COSMIC such that past data in IFPUG can be considered for future estimates using COSMIC and as a validation procedure.

The effect of the quality of program source code on the cost of development and maintenance as well as on final system performance has resulted in a demand for technology that can measure and evaluate the quality with high precision. Many metrics have been proposed for measuring quality, but none have been able to provide a comprehensive evaluation, nor have they been used widely. We propose a practical framework which achieves effective measurement and evaluation of source code quality, solves many of the problems of earlier frameworks, and applies to programs in the C programming language. The framework consists of a comprehensive quality metrics suite, a technique for normalization of measured values, an aggregation tool which allows evaluation in arbitrary module units from the component level up to whole systems, a visualization tool for the evaluation of results, a tool for deriving rating levels, and a set of derived standard rating levels. By applying this framework to a collection of embedded programs experimentally, we verified that the framework can be used effectively to give quantitative evaluations of reliability, maintainability, reusability and portability of source code.

Software testing is a time-consuming and expensive process. Software fault prediction models are used to identify fault-prone classes automatically before system testing. These models can reduce the testing duration, project risks, resource and infrastructure costs. In this study, we propose a novel fault prediction model to improve the testing process. Chidamber-Kemerer Object-Oriented metrics and method-level metrics such as Halstead and McCabe are used as independent metrics in our Artificial Immune Recognition System based model. According to this study, class-level metrics based model which applies AIRS algorithm can be used successfully for fault prediction and its performance is higher than J48 based approach. A fault prediction tool which uses this model can be easily integrated into the testing process.

Software release planning takes place on strategic and operational levels. Strategic release planning aims at assigning features to subsequent releases such that technical, resource, risk and budget constraints are met. Operational release planning focuses on the realization of a single software release. Its purpose is to assign resources to feature development tasks such that total release duration is minimized under given process and project constraints. Re-planning becomes necessary on operational level due to addition or deletion of features during release development, or due to changes in the workforce. The allocation of resources to feature development tasks may depend on the accurate estimation of planning parameters such as feature size, developer productivity or development task dependencies. Risk analysis can help assess the vulnerability of a chosen release plan due to these dependencies. This paper presents a simulation-based approach to planning, re-planning and risk analysis of software releases on operational level. The core element of the approach is the process simulation model REPSIM-2 (Release Plan Simulator, Version 2). We describe the functionality of REPSIM-2 and illustrate its usefulness for planning, re-planning and risk analysis through application scenarios.

The cost of a Software Product Line (SPL) development project sometimes exceeds the initially planned cost, because of requirements volatility and poor quality. In this paper, we propose a cost overrun simulation model for time-boxed SPL development. The model is an enhancement of a previous model, specifically now including: consideration of requirements volatility, consideration of unplanned work for defect correction during product projects, and nominal project cost overrun estimation. The model has been validated through stochastic simulations with fictional SPL project data, by comparing generated unplanned work effort to actual change effort, and by sensitivity analysis. The result shows that the proposed model has reasonable validity to estimate nominal project cost overruns and its variability. Analysis indicates that poor management of requirements and quality will almost double estimation error, for the studied simulation settings.

The selection of the most acceptable architecture of e-services system is very important issue. One and the same e-service can be designed using different alternative architectures. Each system has different execution indices that are very important for the e-services clients and providers. This article shows solutions for compromise or the most acceptable selection of the architecture of e-services system using more than one criterion at the same time. The solution is based on the theory of graphs and usage of multi-criteria methods and their basics is following: E-service algorithm is described with an algorithm graph. Using segmentation of algorithm graph web service graphs are obtained that are assessed with characteristic numerical values of system architecture. Several characteristics of system architecture are: Reusability, Costs of Production and Time of Execution. The task of multi-criteria optimization of web service graphs is defined when as result the compromise or the Pareto set of web service graphs is evaluated. The most acceptable solution of system architecture is selected from Pareto set by using additional information. The usage of offered method is demonstrated with help of practical example.