Developing reproducible and comprehensible computational models

Quantitative predictions for complex scientific theories are often obtained by running simulations on computational models. In order for a theory to meet with wide-spread acceptance, it is important that the model be reproducible and comprehensible by independent researchers. However, the complexity of computational models can make the task of replication all but impossible. Previous authors have suggested that computer models should be developed using high-level specification languages or large amounts of documentation. We argue that neither suggestion is sufficient, as each deals with the prescriptive definition of the model, and does not aid in generalising the use of the model to new contexts. Instead, we argue that a computational model should be released as three components: (a) a well-documented implementation; (b) a set of tests illustrating each of the key processes within the model; and (c) a set of canonical results, for reproducing the model’s predictions in important experiments. The included tests and experiments would provide the concrete exemplars required for easier comprehension of the model, as well as a confirmation that independent implementations and later versions reproduce the theory’s canonical results

Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

Non-Linearities And Fractional Integration In The Us Unemployment Rate

This paper proposes a model of the US unemployment rate which accounts for both its asymmetry and its long memory. Our approach introduces fractional integration and nonlinearities simultaneously into the same framework, using a Lagrange Multiplier procedure with a standard null limit distribution. The empirical results suggest that the US unemployment rate can be specified in terms of a fractionally integrated process, which interacts with some non-linear functions of labour demand variables such as real oil prices and real interest rates. We also find evidence of a long-memory component. Our results are consistent with a hysteresis model with path dependency rather than a NAIRU model with an underlying unemployment equilibrium rate, thereby giving support to more activist stabilisation policies. However, any suitable model should also include business cycle asymmetries, with implications for both forecasting and policy-making

Evolution of Ada technology in the flight dynamics area: Implementation/testing phase analysis

An analysis is presented of the software engineering issues related to the use of Ada for the implementation and system testing phases of four Ada projects developed in the flight dynamics area. These projects reflect an evolving understanding of more effective use of Ada features. In addition, the testing methodology used on these projects has changed substantially from that used on previous FORTRAN projects