An inter-comparison of Arctic synoptic scale storms between four global reanalysis datasets

The Arctic is becoming more accessible as sea ice extent continues to decline, resulting in higher human exposure to Arctic storms. This study compares Arctic storm characteristics between the ECMWF-Interim Reanalysis, 55-year Japanese Reanalysis, NASA-Modern Era Retrospective Analysis for Research and Applications Version 2 and National Centre for Environmental Prediction-Climate Forecast System Reanalysis datasets between 1980 and 2017, in winter (DJF) and summer (JJA). It is shown that Arctic storm characteristics are sensitive to the variable used for storm tracking. Arctic storm frequency is found to be similar in summer and winter when using sea level pressure minima to track Arctic storms, whereas, the storm frequency is found to be higher in winter than summer when using 850 hPa relative vorticity to track storms, based on using the same storm tracking algorithm. It is also found that there are no significant trends in Arctic storm characteristics between 1980 and 2017. Given the sparsity of observations in the Arctic, it might be expected that there are large differences in Arctic storm characteristics between the reanalysis datasets. Though, some similar Arctic storm characteristics are found between the reanalysis datasets, it is found that the differences in Arctic storm characteristics between the reanalysis datasets are generally higher in winter than in summer. Overall, the results show that there are differences in Arctic storm characteristics between reanalysis datasets, but even larger differences can arise between using 850 hPa relative vorticity or mean sea level pressure as the storm tracking variable, which adds to the uncertainty associated with current Arctic storm characteristics

MintHint: Automated Synthesis of Repair Hints

Being able to automatically repair programs is an extremely challenging task. In this paper, we present MintHint, a novel technique for program repair that is a departure from most of today's approaches. Instead of trying to fully automate program repair, which is often an unachievable goal, MintHint performs statistical correlation analysis to identify expressions that are likely to occur in the repaired code and generates, using pattern-matching based synthesis, repair hints from these expressions. Intuitively, these hints suggest how to rectify a faulty statement and help developers find a complete, actual repair. MintHint can address a variety of common faults, including incorrect, spurious, and missing expressions. We present a user study that shows that developers' productivity can improve manyfold with the use of repair hints generated by MintHint -- compared to having only traditional fault localization information. We also apply MintHint to several faults of a widely used Unix utility program to further assess the effectiveness of the approach. Our results show that MintHint performs well even in situations where (1) the repair space searched does not contain the exact repair, and (2) the operational specification obtained from the test cases for repair is incomplete or even imprecise

A methodology for the capture and analysis of hybrid data: a case study of program debugging

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Cognitive Aspects of Structured Process Modeling

After visualizing data of various observational experiments on the way in which modelers construct process models, a promising process modeling style (i.e., structured process modeling) was discovered that is expected to cause process model quality to increase. A modeler constructs process models in a structured way if she/he is working on few parts of the model simultaneously. This paper describes cognitive theories that can explain this causal relation. Cognitive Load Theory (CLT) suggests that the amount of errors increases when the limited capacity of our working memory is overloaded. Cognitive Fit Theory (CFT) states that performance is improved when task material representation matches with the task to be executed. Three hypotheses are formulated and the experimental set-up to evaluate these hypotheses is described

Sindarin: A Versatile Scripting API for the Pharo Debugger

International audienceDebugging is one of the most important and time consuming activities in software maintenance, yet mainstream debuggers are not well-adapted to several debugging scenarios. This has led to the research of new techniques covering specific families of complex bugs. Notably, recent research proposes to empower developers with scripting DSLs, plugin-based and moldable debuggers. However, these solutions are tailored to specific use-cases, or too costly for one-time-use scenarios. In this paper we argue that exposing a debugging scripting interface in mainstream debuggers helps in solving many challenging debugging scenarios. For this purpose, we present Sindarin, a scripting API that eases the expression and automation of different strategies developers pursue during their debugging sessions. Sindarin provides a GDB-like API, augmented with AST-bytecode-source code mappings and object-centric capabilities. To demonstrate the versatility of Sindarin, we reproduce several advanced breakpoints and non-trivial debugging mechanisms from the literature

Integration of DFDs into a UML - based model-driven engineering approach

The main aim of this article is to discuss how the functional and the object-oriented views can be inter-played to represent the various modeling perspectives of embedded systems.We discuss whether the object-oriented modeling paradigm, the predominant one to develop software at the present time, is also adequate for modeling embedded software and how it can be used with the functional paradigm.More specifically, we present how the main modeling tool of the traditional structured methods, data flow diagrams, can be integrated in an object-oriented development strategy based on the unified modeling language. The rationale behind the approach is that both views are important for modeling purposes in embedded systems environments, and thus a combined and integrated model is not only useful, but also fundamental for developing complex systems. The approach was integrated in amodel-driven engineering process, where tool support for the models used was provided. In addition, model transformations have been specified and implemented to automate the process.We exemplify the approach with an IPv6 router case study.FEDER -Fundação para a Ciência e a Tecnologia(HH-02-383