Multiscale Bone Remodelling with Spatial P Systems

Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide "multilayer" models, only Complex Automata, derived from Cellular Automata, naturally embed spatial information and realize multiscaling with well-established inter-scale integration schemas. Spatial P systems, a variant of P systems in which a more geometric concept of space has been added, have several characteristics in common with Cellular Automata. We propose such a formalism as a basis to rephrase the Complex Automata multiscaling approach and, in this perspective, provide a 2-scale Spatial P system describing bone remodelling. The proposed model not only results to be highly faithful and expressive in a multiscale scenario, but also highlights the need of a deep and formal expressiveness study involving Complex Automata, Spatial P systems and other promising multiscale approaches, such as our shape-based one already resulted to be highly faithful.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

Opaque Service Virtualisation: A Practical Tool for Emulating Endpoint Systems

Large enterprise software systems make many complex interactions with other services in their environment. Developing and testing for production-like conditions is therefore a very challenging task. Current approaches include emulation of dependent services using either explicit modelling or record-and-replay approaches. Models require deep knowledge of the target services while record-and-replay is limited in accuracy. Both face developmental and scaling issues. We present a new technique that improves the accuracy of record-and-replay approaches, without requiring prior knowledge of the service protocols. The approach uses Multiple Sequence Alignment to derive message prototypes from recorded system interactions and a scheme to match incoming request messages against prototypes to generate response messages. We use a modified Needleman-Wunsch algorithm for distance calculation during message matching. Our approach has shown greater than 99% accuracy for four evaluated enterprise system messaging protocols. The approach has been successfully integrated into the CA Service Virtualization commercial product to complement its existing techniques.Comment: In Proceedings of the 38th International Conference on Software Engineering Companion (pp. 202-211). arXiv admin note: text overlap with arXiv:1510.0142

QCLab: a framework for query compilation on modern hardware platforms

As modern in-memory database systems achieve higher and higher processing speeds, the performance of memory becomes an increasingly limiting factor. Although there has been significant progress, the bottleneck only has shifted. While earlier systems were optimized for memory latencies, current systems are rather affected by the limited memory bandwidth. Query compilation is a proven technique to address bandwidth limitations. It translates queries via Just-In-Time compilation to native programs for the target hardware. The compiled queries execute with very high efficiency and only with a bare minimum of communication via memory. Despite these important improvements, the benefit of query compilation in certain scenarios is limited. On the one hand query compilers typically use standard compiler technology with relatively long compilation times. Therefore the overall execution time can be prolonged by the additional compilation time. On the other hand, not all emerging database technology is compatible with the approach. Query compilation uses a tuple-at-a-time processing style that departs from the column-at-a-time or vector-at- a-time approaches that in-memory systems typically use. Especially data-parallel processing techniques, e.g. SIMD or coprocessing-techniques, are challenging to use in combination with the approach. This work presents QCLab, a framework for query compilation on modern hardware platforms. The framework contains several new query compilation techniques that allow us to address the mentioned shortcomings and ultimately to extend the benefit of query compilation to new workloads and platforms. The techniques cover three aspects: compilation, communication, and processing. Together they serve as basis for building highly efficient query compilers. The techniques make efficient use of communication channels and of the large processing capacities of modern systems. They were designed for practical use and enable efficient processing, even when workload characteristics are challenging

LExecutor: Learning-Guided Execution

Executing code is essential for various program analysis tasks, e.g., to detect bugs that manifest through exceptions or to obtain execution traces for further dynamic analysis. However, executing an arbitrary piece of code is often difficult in practice, e.g., because of missing variable definitions, missing user inputs, and missing third-party dependencies. This paper presents LExecutor, a learning-guided approach for executing arbitrary code snippets in an underconstrained way. The key idea is to let a neural model predict missing values that otherwise would cause the program to get stuck, and to inject these values into the execution. For example, LExecutor injects likely values for otherwise undefined variables and likely return values of calls to otherwise missing functions. We evaluate the approach on Python code from popular open-source projects and on code snippets extracted from Stack Overflow. The neural model predicts realistic values with an accuracy between 79.5% and 98.2%, allowing LExecutor to closely mimic real executions. As a result, the approach successfully executes significantly more code than any available technique, such as simply executing the code as-is. For example, executing the open-source code snippets as-is covers only 4.1% of all lines, because the code crashes early on, whereas LExecutor achieves a coverage of 51.6%.Comment: Accepted in research track of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 202

Keeping Up with New Legal Titles

This review examines Usual Cruelty: The Complicity of Lawyers in the Criminal Injustice System, a new book by Alec Karakatsanis