To support decision-making for security-risk mitigation and the appropriate selection of security countermeasures, we propose a system dynamics model of the security aspects of an enterprise system. We developed such an executable model, incorporating the concept of archetypes. We present here one archetype for computer security, namely symptomatic fixes (or shifting the burden). Using simulation, we show one instance of how this archetype can be used for recognizing and diagnosing typical situations, as well as for fixing problems. The global effects of changes and behavioral trends are examined, and other instances of symptomatic fixes in security are described as well

Empirical evaluation of dependability is a complement to modeling and analytical methods. Although empirical evaluation applies to real systems and is more realistic, more accurate, and provides a higher level of confidence, it is not extensively used, for multiple reasons: it is time and effort consuming; the results have limited portability; there are no benchmarks to define what measures to be collected, how to measure the data, how to report it, what are the models that indicate the ranges of "good" and "bad" values, and how to compare the values for different systems. Due to these challenges, very few results and empirical data are available for dependability evaluation, comparison, and benchmarking. Acknowledging these challenges, but also the need for empirical dependability evaluation, this workshop will bring together researchers and practitioners for sharing their solutions and results, as well as for documenting their needs, problems, and ideas with respect to this topic. The workshop will include presentations and a hands-on session where participants will work on finding solutions to pre-selected questions.

At NASA, more and more functionality is implemented in software. Change requests tend to arrive late, making software flexibility an important aspect. However, such changes present a high risk and are more likely to introduce defects and to violate flexibility properties of the software, causing its "degeneration." In this paper, we present some preliminary results from a recent study of Software Architecture Flexibility. The study was conducted as an experiment with students using the TSAFE experimental testbed. The main conclusion is that constructs for flexibility are not automatically understood, used, and followed by new developers. Better ways to describe the intention with certain constructs in combination with assigning responsibility for making sure that the implementation adheres to the intended architecture and its design rationale could provide a successful approach for avoiding degeneration of built-in flexibility.

In support of decision-making for planning the effort to be allocated to inspections in different software development phases, we propose combining empirical studies with process modeling and simulation. We present the simulator developed for answering questions and running "what-if" scenarios specific to NASA software development projects.

Decision-making is a complex and important task in software engineering. The current state-of-the-practice is rather non-systematic as it typically relies upon personal judgment and experience without using explicit models. Empirical studies can help but they are costly to conduct and, to some extent, context dependent. Typically it is not efficient or even possible to conduct empirical studies for a large number of context parameter variations. Process simulation offers decision support as well, but currently suffers from a lack of empirical knowledge on the determinants of underlying system dynamics. In this paper we present an assessment of empirical knowledge and simulation techniques for the area of quality assurance planning. There is a strong interdependency between process simulation and empirical models for decision-making in this area: (a) profound empirical knowledge enables process simulation to support decision-making, and (b) the analysis of simulation results can point out situations and factors for which conducting empirical studies would be most worthwhile. This paper discusses critically some of the most important challenges for decision-making in the area of quality assurance planning.

Abstract Welcome to this special issue of the Journal of Software Maintenance and Evolution on process diversity. We, the guest editors, are very pleased to be able to include three fine papers on this subject, and we hope that our readers will find them stimulating and informative. Copyright © 2003 John Wiley & Sons, Ltd.

Decision-making is a complex and important task in software engineering. The current state-of-the-practice is rather non-systematic as it typically relies upon personal experience without using explicit models. Empirical studies can help but are to some extent context dependent and costly to conduct. Typically it is not efficient or even possible to conduct empirical studies for a large number of context parameter variations. We propose to build on a set of systematic empirical studies to fill gaps in context variable space with simulation: (a) Simulation can use the empirical results from different contexts and apply them to a planning situation as appropriate. (b) The analysis of simulation results can point out situations and factors for which conducting empirical studies would be most worthwhile. This paper presents a general decision model, a simulation framework, and examples for different decisions to use V&V activities in software development (e.g., under which conditions is a V&V activity, such as a re-inspection, worthwhile) to demonstrate practical applications of the general model.

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The National Aeronautics and Space Administration (NASA) Space Shuttle program is a multi-billion dollar activity scheduled to span over 40 years. Maintaining such software with requirements for high reliability and mission safety taxes current development methods. The authors present how independent verification and validation (IV&V) activities are used to support these requirements. They also show how the IV&V activities for this program differ from those of more traditional software developments.

No abstract available.

This decision support system was built to assist project managers to design and tailor the software development process to their specific projects for achieving required software reliability values. The decision support system has two subsystems: a knowledge-based expert system for reliability engineering strategy selection and a process simulator for strategy assessment. We present here the knowledge-based component for strategy selection assistance. The paper describes the framework for identifying software reliability engineering practices and the decision factors for selecting a subset of practices appropriate for the project, taking into account various project constraints. After identifying heuristics for making the selection decisions, we have developed a knowledge base and implemented an expert system to help a less experienced project manager with engineering the process in a product quality driven manner. The expert system is a rule based fuzzy logic system, developed by using the off-the-shelf FuzzyCLIPS shell.