Catálogo de publicaciones - libros

This paper presents a survey about use of quantitative management indicators in a Japanese software development organization. This survey is conducted in order to investigate possible criteria for selecting and customizing organizational standard indicators according to the context of each project. Based on results of the survey, we propose a process tailoring support system that is mainly focusing to quantitative management planning. The system EPDG+ (Electronic Process Data Guidebook Plus) helps project planners select / customize indicators to be employed in process control. Derived software project plans including measurement and analysis activities can be browsed in detail with this system.

Component based development (CBD), product line engineering (PLE), and model driven architecture (MDA) are representative approaches for software reuse. CBD and PLE focus on reusable assets of components and core assets, MDA focuses on transforming reusable models into implementation. Although these approaches are orthogonal, they can be integrated into a comprehensive and extremely effective framework for software development. In this paper, we first present our strategies of integrating CBD, PLE and MDA, and propose an integrated process that adopts reuse engineering and automation paradigm. By applying the proposed approach, it becomes feasible to semi-automatically develop a number of applications in a domain.

In today’s software development organizations, methods and tools are employed that frequently lack sufficient evidence regarding their suitability, limits, qualities, costs, and associated risks. For example, in Communications of the ACM (Communications of the ACM May 2004/Vol. 47, No. 5) Robert L. Glass, taking the standpoint of practitioners, asks for help from research: “Here’s a message from software practitioners to software researchers: We (practitioners) need your help. We need some better advice on how and when to use methodologies”. Therefore, he demands: – a taxonomy of available methodologies, based upon their strengths and weaknesses; – a taxonomy of the spectrum of problem domains, in terms of what practitioners need; – a mapping of the first taxonomy to the second (or the second to the first). The evidence-based Software Engineering Paradigm promises to solve parts of these issues by providing a framework for goal-oriented research leading to a common body of knowledge and, based on that, comprehensive problemoriented decision support regarding SE technology selection. One issue that is becoming more and more important in the context of the evidence-based SE Paradigm is the teaching of evidence-based Software Engineering. A major discussion with regard to this issue revolves around the question of how to “grow the seeds”; that is, how can we teach evidence-based SE in a way that encourages students to practice paradigm in their professional life. The goal of this workshop is to discuss issues related to fostering the evidence-based paradigm. The results from the workshop and especially from the working groups will be published in the “Workshop Series on Empirical Software Engineering”, Vol.3. The workshop itself is the fourth one in the workshop series on Empirical Software Engineering. The first one was held in conjunction with PROFES 2002 in Rovaniemi, the second one was held in conjunction with the Empirical Software Engineering International Week 2003 in Rome, and the third one was held in conjunction with PROFES 2005 in Oulu.

The embedded systems industry is growing and getting a more dominant role in the markets. Due to tight time-to-market requirements and complexity of the systems, companies hardly ever develop embedded products on their own. In order to acquire the required expertise, efficiency and desired lead-time, embedded systems need to be developed globally in collaboration with subcontractors, third party developers and in-house development. Against this background, the workshop on Embedded Software Development In Collaboration addresses the increasing demand of the industry for finding and discovering new and more efficient ways to support collaborative embedded systems development. The short paper sessions provide an excellent forum and opportunity for industrial experts, scholars, and Ph.D. students to discuss their interests on collaborative (embedded) systems development.

Quality is measurable – also in the case of software. Properly introduced metrics are the basis for efficient project- and quality management. This tutorial presents the basic concepts of measurement and gives guidelines on how to apply measurement in practice. Numerous examples included in the tutorial help quality managers, developers, and project leaders to understand the concepts presented and to select optimal metric sets for their specific organizational needs.

Informed and qualified decisions are key factors for project failure or success. The idea of decision support always arises when timely decisions must be made in unstructured or semi-structured problem domains, where multiple stakeholders are involved, and when the information available is uncertain. Release planning (RP) addresses decisions related to the selection and assignment of features to a sequence of consecutive product releases such that the most important technical, resource, budget, and risk constraints are met. Release planning is an important and integral part of any type of incremental product development. The objective of this tutorial is to describe and position the ‘art and science’ of software release planning. The “art of release planning” refers to relying on human intuition, communication, and capabilities to negotiate between conflicting objectives and constraints. The “science of release planning” refers to emphasizing formalization of the problem and applying computational algorithms to generate best solutions. Both art and science are important for achieving meaningful release planning results. We investigate the release planning process and propose a hybrid planning approach that integrates the strength of computational intelligence with the knowledge and experience of human experts.

Multiple Projects Development Environments have evolved recently. However, most available environments do not provide risk management process support to the project manager’s activities. This support could be provided through the analysis of the interactions between projects. One of the main weaknesses of the approaches up to now is that risk management process improvement based on the risks between ongoing projects and completed ones is being neglected. In this light, we propose the creation of a Risk Management Model for Multiple Project Environments to treat the risk interactions between projects.

Ten years after the presentation of the tutorial “The Experience Factory: How to Build and Run One” at ICSE 17 in 1995 [4], the idea of building such a Learning Software Organization (LSO) is in wide spread use. Meanwhile, the Experience Factory (EF) concept [2], i.e., the systematic goal-oriented utilization of experience , is also being successfully applied outside the domain of Software Engineering [11], [12]. However, defining and implementing a successful Experience Factory is still a challenge [9]. In this tutorial we take a look at existing concepts on how to identify and structure the content of the experience base (EB), discuss solutions for how to implement an EB, and present processes on how to setup, run, evaluate, and maintain an EF in an organization. The tutorial is based on the authors’ organizations’ experiences with implementing EFs in research, industry, and government environments.