A CRITICAL REVIEW OF THE ENVIRONMENTAL UNCERTAINTY LITERATURE SINCE 1987

Environmental uncertainty has been a central construct of organizational theorists and strategic management researchers for many decades. The number of empirical studies using the uncertainty construct also continues to be significant. However, the confusion surrounding the conceptualization and measurement of the uncertainty construct remains a subject of scholarly debate. Through our comprehensive review of 77 empirical studies over the last 20 years and related theoretical and methodological work, we intend to (1) review the conceptualization trends and persisting issues that are apparent in uncertainty research, (2) review empirical issues particularly important to uncertainty work and illustrate how researches have or have not overcome some of these challenges, and (3) suggest directions for future research using the uncertainty construct.

Big Data Refinement

"Big data" has become a major area of research and associated funding, as well as a focus of utopian thinking. In the still growing research community, one of the favourite optimistic analogies for data processing is that of the oil refinery, extracting the essence out of the raw data. Pessimists look for their imagery to the other end of the petrol cycle, and talk about the "data exhausts" of our society. Obviously, the refinement community knows how to do "refining". This paper explores the extent to which notions of refinement and data in the formal methods community relate to the core concepts in "big data". In particular, can the data refinement paradigm can be used to explain aspects of big data processing

Model exploration and analysis for quantitative safety refinement in probabilistic B

The role played by counterexamples in standard system analysis is well known; but less common is a notion of counterexample in probabilistic systems refinement. In this paper we extend previous work using counterexamples to inductive invariant properties of probabilistic systems, demonstrating how they can be used to extend the technique of bounded model checking-style analysis for the refinement of quantitative safety specifications in the probabilistic B language. In particular, we show how the method can be adapted to cope with refinements incorporating probabilistic loops. Finally, we demonstrate the technique on pB models summarising a one-step refinement of a randomised algorithm for finding the minimum cut of undirected graphs, and that for the dependability analysis of a controller design.Comment: In Proceedings Refine 2011, arXiv:1106.348