Programming Not Only by Example

In recent years, there has been tremendous progress in automated synthesis techniques that are able to automatically generate code based on some intent expressed by the programmer. A major challenge for the adoption of synthesis remains in having the programmer communicate their intent. When the expressed intent is coarse-grained (for example, restriction on the expected type of an expression), the synthesizer often produces a long list of results for the programmer to choose from, shifting the heavy-lifting to the user. An alternative approach, successfully used in end-user synthesis is programming by example (PBE), where the user leverages examples to interactively and iteratively refine the intent. However, using only examples is not expressive enough for programmers, who can observe the generated program and refine the intent by directly relating to parts of the generated program. We present a novel approach to interacting with a synthesizer using a granular interaction model. Our approach employs a rich interaction model where (i) the synthesizer decorates a candidate program with debug information that assists in understanding the program and identifying good or bad parts, and (ii) the user is allowed to provide feedback not only on the expected output of a program, but also on the underlying program itself. That is, when the user identifies a program as (partially) correct or incorrect, they can also explicitly indicate the good or bad parts, to allow the synthesizer to accept or discard parts of the program instead of discarding the program as a whole. We show the value of our approach in a controlled user study. Our study shows that participants have strong preference to using granular feedback instead of examples, and are able to provide granular feedback much faster

Internal Avalanches in a Granular Medium

Avalanches of grain displacements can be generated by creating local voids within the interior of a granular material at rest in a bin. Modeling such a two-dimensional granular system by a collection of mono-disperse discs, the system on repeated perturbations, shows all signatures of Self-Organized Criticality. During the propagation of avalanches the competition among grains creates arches and in the critical state a distribution of arches of different sizes is obtained. Using a cellular automata model we demonstrate that the existence of arches determines the universal behaviour of the model system.Comment: 4 pages (Revtex), Four ps figures (included

Towards a new approach to quantum gravity phenomenology

The idea that quantum gravity manifestations would be associated with a violation of Lorentz invariance is very strongly bounded and faces serious theoretical challenges. This leads us to consider an alternative line of thought for such phenomenological search. We discuss the underlying viewpoint and briefly mention its possible connections with current theoretical ideas. We also outline the challenges that the experimental search of the effects would seem to entail.Comment: 13 pages, no figures. Discussion added, same conclusion

Knowledge Engineering in Search Engines

With large amounts of information being exchanged on the Internet, search engines have become the most popular tools for helping users to search and filter this information. However, keyword-based search engines sometimes obtain information, which does not meet user’ needs. Some of them are even irrelevant to what the user queries. When the users get query results, they have to read and organize them by themselves. It is not easy for users to handle information when a search engine returns several million results. This project uses a granular computing approach to find knowledge structures of a search engine. The project focuses on knowledge engineering components of a search engine. Based on the earlier work of Dr. Lin and his former student [1], it represents concepts in the Web by simplicial complexes. We found that to represent simplicial complexes adequately, we only need the maximal simplexes. Therefore, this project focuses on building maximal simplexes. Since it is too costly to analyze all Web pages or documents, the project uses the sampling method to get sampling documents. The project constructs simplexes of documents and uses the simplexes to find maximal simplexes. These maximal simplexes are regarded as primitive concepts that can represent Web pages or documents. The maximal simplexes can be used to build an index of a search engine in the future

Modeling of long-time thermal magnetization decay in interacting granular magnetic materials

We present a general method to evaluate the long-time magnetization decay in granular magnetic systems. The method is based on Arrhenius-Neel kinetics with the evaluation of the energy barriers in a multidimensional space. To establish a possible reversal mode, we suggest the use of Metropolis Monte Carlo and for the mode statistical sampling-the kinetic Monte Carlo criteria. The examples considered include long-time magnetization decay in CoCrPt low-magnetization longitudinal recording media and in a collection of Co particles with different concentrations