Patterns in complex systems modeling

The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.

Termination of real-time programs: Definitely, definitely not, or maybe

Real-time control programs are often used in contexts where (conceptually) they run forever. Repetitions within such programs (or their specifications) may either (i) be guaranteed to terminate, (ii) be guaranteed to never terminate (loop forever), or (iii) may possibly terminate. In dealing with real-time programs and their specifications, we need to be able to represent these possibilities, and define suitable refinement orderings. A refinement ordering based on Dijkstra's weakest precondition only copes with the first alternative. Weakest liberal preconditions allow one to constrain behaviour provided the program terminates, which copes with the third alternative to some extent. However, neither of these handles the case when a program does not terminate. To handle this case a refinement ordering based on relational semantics can be used. In this paper we explore these issues and the definition of loops for real-time programs as well as corresponding refinement laws.

Compositional class refinement in object-Z

Object-Z allows coupling constraints between classes which, on the one hand, facilitate specification at a high level of abstraction, but, on the other hand, make class refinement non-compositional. The consequence of this is that refinement is not practical for large Systems. This paper overcomes this limitation by introducing a methodology for compositional class refinement in Object-Z. The key step is an equivalence transformation of an arbitrary Object-Z specification to one in which introduced constraints prohibit non-compositional refinements. The methodology also allows the constraints which couple classes to be refined yielding an unrestricted approach to compositional class refinement.

Continuous action system refinement

Action systems are a framework for reasoning about discrete reactive systems. Back, Petre and Porres have extended these action systems to continuous action systems, which can be. used to model hybrid systems. In this paper we define a refinement relation, and develop practical data refinement rules for continuous action systems. The meaning of continuous action systems is expressed in terms of a mapping from continuous action systems to action systems. First, we present a new mapping from continuous act ion systems to action systems, such that Back's definition of trace refinement is correct with respect to it. Second, we present a stream semantics that is compatible with the trace semantics, but is preferable to it because it is more general. Although action system trace refinement rules are applicable to continuous action systems with a stream semantics, they are not complete. Finally, we introduce a new data refinement rule that is valid with respect to the stream semantics and can be used to prove refinements that are not possible in the trace semantics, and we analyse the completeness of our new rule in conjunction with the existing trace refinement rules.

Reasoning algebraically about probabilistic loops

Back and von Wright have developed algebraic laws for reasoning about loops in the refinement calculus. We extend their work to reasoning about probabilistic loops in the probabilistic refinement calculus. We apply our algebraic reasoning to derive transformation rules for probabilistic action systems. In particular we focus on developing data refinement rules for probabilistic action systems. Our extension is interesting since some well known transformation rules that are applicable to standard programs are not applicable to probabilistic ones: we identify some of these important differences and we develop alternative rules where possible. In particular, our probabilistic action system data refinement rules are new.

A state-of-practice questionnaire on verification and validation for concurrent programs

Research in verification and validation (V&V) for concurrent programs can be guided by practitioner information. A survey was therefore run to gain state-of-practice information in this context. The survey presented in this paper collected state-of-practice information on V&V technology in concurrency from 35 respondents. The results of the survey can help refine existing V&V technology by providing a better understanding of the context of V&V technology usage. Responses to questions regarding the motivation for selecting V&V technologies can help refine a systematic approach to V&V technology selection.