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Symbolic execution based on language transformation

COMPUTER LANGUAGES SYSTEMS & STRUCTURES 2015年第PartA期44卷 48-71页

作者： Arusoaie, Andrei Lucanu, Dorel Rusu, Vlad Alexandru Ioan Cuza Univ Fac Comp Sci Iasi Romania Inria Lille Nord Europe Villeneuve Dascq France

We propose a language-independent symbolic execution framework for languages endowed with a formal operational semantics based on term rewriting. Starting from a given definition of a language, a new language definition is generated, with the same syntax as the original one, but whose semantical rules are transformed in order to rewrite over logical formulas denoting possibly infinite sets of program states. then, the symbolic execution of concrete programs is, by definition, the execution of the same programs with the symbolic semantics. We prove that the symbolic execution thus defined has the properties naturally expected from it (with respect to concrete program execution). A prototype implementation of our approach was developed in the K framework. We demonstrate the tool's genericity by instantiating it on several languages, and illustrate it on the reachability analysis and model checking of several programs. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Symbolic execution Formal semantics programming languages Program analysis

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Improved Algorithms for Debugging Problems on Erroneous Reversible Circuits 7th

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7th international conference on Reversible Computation (RC)

作者： Inoue, Yuma Minato, Shin-ichi Hokkaido Univ Grad Sch Informat Sci & Technol Sapporo Hokkaido Japan JST ERATO MINATO Discrete Struct Manipulat Syst P Sapporo Hokkaido Japan

ISBN: (纸本)9783319208602;9783319208596

Reversible circuits and their synthesis methods have been actively studied in order to realize reversible computation. However, there are few known ways to debug erroneous reversible circuits. In this paper, we propose new algorithms for debugging problems. For single gate error, we improve the theoretical efficiency of previous methods, which use worst case exponential time algorithms such as SAT or decision diagrams. We also propose an algorithm debugging multiple gate error circuits by using pi DDs, decision diagrams for permutation sets. We evaluate our algorithms theoretically and experimentally, and confirm significant improvement.

关键词： Reversible computation Circuit design Permutations Algorithms Decision diagrams Dynamic programming

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Towards Machine Learning of Predictive Models from Ecological Data 1

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24th international conference on Inductive Logic programming (ILP)

作者： Tamaddoni-Nezhad, Alireza Bohan, David Raybould, Alan Muggleton, Stephen Univ London Imperial Coll Sci Technol & Med Dept Comp London SW7 2AZ England Pole Ecoldur UMR Agroecol 1347 F-21065 Dijon France Syngenta Crop Protect AG CH-4058 Basel Switzerland

ISBN: (数字)9783319237084

ISBN: (纸本)9783319237084;9783319237077

In a previous paper we described a machine learning approach which was used to automatically generate food-webs from national-scale agricultural data. the learned food-webs in the previous study consist of hundreds of ground facts representing trophic links between individual species. these species food-webs can be used to explain the structure and dynamics of particular eco-systems, however, they cannot be directly used as general predictive models. In this paper we describe the first steps towards this generalisation and present initial results on (i) learning general functional food-webs (i.e. trophic links between functional groups of species) and (ii) meta-interpretive learning (MIL) of general predictive rules (e.g. about the effect of agricultural management). Experimental results suggest that functional food-webs have at least the same levels of predictive accuracies as species food-webs despite being much more compact. In this paper we also present initial experiments where predicate invention and recursive rule learning in MIL are used to learn food-webs as well as predictive rules directly from data.

关键词： Artificial intelligence

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Study on Energy Management Strategies for Series-parallel Plug-in Hybrid Electric Buses 7th

Study on Energy Management Strategies for Series-parallel Pl...

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7th international conference on Applied Energy (ICAE)

作者： Peng, Jiankun He, Hongwen Xiong, Rui Beijing Inst Technol Natl Engn Lab Elect Vehicles Beijing 100081 Peoples R China

the power flow between the power sources and the performance of plug-in-hybrid electric vehicles (PHEV) significantly in fuel economy are mainly determined by energy management strategy. To research the energy management of the PHEV, the control strategy of a plug-in series-parallel hybrid electric bus (PHEB) is studied in this paper. Firstly, the simulation model of the PHEB is built with CRUISE software. Secondly, to explore the fuel-saving potential of the PHEB, the global optimal control strategy which adopts dynamic programming (DP) algorithm is studied and built with MATLAB software, although the minimum fuel consumption of certain driving cycle can be a benchmark for evaluating the energy management strategy of PHEB, the global optimal control strategy based on DP is rarely directly applied in real vehicle due to its long online computation time. At last, to ensure control timely, a rule-based control strategy is calibrated according to the computation results of global optimal control strategy. the simulation results show that, the fuel consumption per 100km decreased by 9.11% and the electric power consumption per 100km decreased by 6.27%. (C) 2015 the Authors. Published by Elsevier Ltd.

关键词： Energy management Dynamic programming (DP) rule-based Plug-in hybrid electric bus (PHEB)

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Methodology for optimal sizing of hybrid power system using particle swarm optimization and dynamic programming 7th

Methodology for optimal sizing of hybrid power system using ...

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7th international conference on Applied Energy (ICAE)

作者： Xiong, Rui He, Hongwen Sun, Fengchun Beijing Inst Technol Natl Engn Lab Elect Vehicles Beijing 100081 Peoples R China Beijing Inst Technol Collaborat Innovat Ctr Elect Vehicles Beijing Beijing 100081 Peoples R China

A methodology for optimal sizing of hybrid battery-ultracapacitor power system (HPS) is presented. the purpose of the proposed methodology is to locate the optimal voltage level for HPS used in a plug-in hybrid electric vehicle (PHEV). A combined optimization framework for a HPS is proposed and the optimization problem is solved in a bi-level manner. the framework contains two nested optimization loops. the outer loop evaluates the selected parameters through particle swarm optimization (PSO) algorithm, while the inner loop generates the optimal control strategy and calculates the costs through dynamic programming (DP) algorithm. the Chinese Typical City Bus Drive Cycle (CTCBDC) has been used to verify and evaluate the performance of the proposed methodology. the optimization result shows that higher voltage degree usually means better performance and the battery tends to provide a constant power for the HPS. It is noted that the constant power closes to the high efficiency district of the battery and DC/DC convertor. After that the optimal result is further analyzed under various optimization goals and battery charge/discharge current constrains. (C) 2015 the Authors. Published by Elsevier Ltd.

关键词： particle swarm optimization dynamic programming combined optimization HPS plug-in hybrid electric vehicle

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Program with Ixquic: How to Learn Object-Oriented programming with a Game

Program with Ixquic: How to Learn Object-Oriented Programmin...

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conference on Games and Virtual Worlds for Serious Applications, VS-GAMES

作者： Tania Patino Carmen Ramos Department of Visualization and Virtual Reality Ciudad Universitaria Coyoacán

In this paper we want to describe advances reached in the game design and implementation related to Serious Game: Program with Ixquic. We present a work in progress about this videogame. Program with Ixquic, has two main purposes: developing programming skills for every user that interacts with this videogame, where virtual scenes created in 2D dimensions presents Object-Oriented programming concepts through the development of examples and exercises in Java programming Language.

关键词： Games Training Virtual reality Object oriented programming programming profession Visualization

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Cartesian Genetic programming in a changing environment

Cartesian Genetic Programming in a changing environment

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international Joint conference on Computational Intelligence (IJCCI)

作者： Karel Slany Department of Computer Systems Brno University of Technology Brno Czech Republic

ISBN: (纸本)9781509019687

Evolutionary algorithm are prevalently being used in static environments. In a dynamically changing environment an evolutionary algorithm must be also able to cope with the changes of the environment. this paper describes an algorithm based on Cartesian Genetic programming (CGP) that is used to design and optimise a solution in a simulated symbolic regression problem in a changing environment. A modified version of the Age-Layered Population Structure (ALPS) algorithm is being used in cooperation with CGP. It is shown that the usage of ALPS can improve the performance on of CGP when solving problems in a changing environment.

关键词： programming

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Symbolic execution based on language transformation

Symbolic execution based on language transformation

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7th international conference on Software Language Engineering (SLE)

作者： Arusoaie, Andrei Lucanu, Dorel Rusu, Vlad Alexandru Ioan Cuza Univ Fac Comp Sci Iasi Romania Inria Lille Nord Europe Villeneuve Dascq France

关键词： Symbolic execution Formal semantics programming languages Program analysis

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7th international Symposium on Search-Based Software Engineering, SSBSE 2015

7th International Symposium on Search-Based Software Enginee...

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7th international Symposium on Search-Based Software Engineering, SSBSE 2015

ISBN: (纸本)9783319221823

the proceedings contain 38 papers. the special focus in this conference is on Search-Based Software Engineering. the topics include: Genetic improvement of software for multiple objectives;amortised optimisation of non-functional properties in production environments;metrics are not enough;searching for useful parallelism in functional programs;an improved beam-search for the test case generation for formal verification systems;combining multiple coverage criteria in search-based unit test generation;epistatic genetic algorithm for test case prioritization;a scala combinator toolkit for semi-automated composition of metaheuristics;hypervolume-based search for test case prioritization;optimizing aspect-oriented product line architectures with search-based algorithms;adaptive neighbourhood search for the component deployment problem;transformed search based software engineering;regression test case prioritisation for guava;continuous test generation on guava;generating readable unit tests for guava;testing django configurations using combinatorial interaction testing;synthesis of equivalent method calls in guava;object-oriented genetic improvement for improved energy consumption in google guava;automated transplantation of call graph and layout features into kate;growing django citation services using SBSE;multi-objective module clustering for kate;search based component selection for budget hardware;search-based bug report prioritization for kate editor bugs repository;inferring test models from kate’s bug reports using multi-objective search;introducing learning mechanism for class responsibility assignment problem;transformed vargha-delaney effect size;optimizing software product line architectures with OPLA-tool;exploring the landscape of non-functional program properties using spatial analysis and interactive software release planning with preferences base.

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A Framework for Real-Time Information Derivation from Big Sensor Data

A Framework for Real-Time Information Derivation from Big Se...

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IEEE international Symposium on Cyberspace Safety and Security

作者： Liehuo Chen Kyoung-Don Kang Dept. of Comput. Sci. State Univ. of New York at Binghamton Binghamton NY USA

ISBN: (纸本)9781479989386

In data-intensive real-time applications, e.g., transportation management and location-based services, the amount of sensor data is exploding. In these applications, it is desirable to extract value-added information, e.g., fast driving routes, from sensor data streams in real-time rather than overloading users with massive raw data. However, achieving the objective is challenging due to the data volume and complex data analysis tasks with stringent timing constraints. Most existing big data management systems, e.g., Hadoop, are not directly applicable to real-time sensor data analytics, since they are timing agnostic and focus on batch processing of previously stored data that are potentially outdated and subject to I/O overheads. To address the problem, we design a new real-time big data management framework, which supports a non-preemptive periodic task model for continuous in-memory sensor data analysis and a schedulability test based on the EDF (Earliest Deadline First) algorithm to derive information from current sensor data in real-time by extending the map-reduce model originated in functional programming. As a proof-of-concept case study, a prototype system is implemented. In the performance evaluation, it is empirically shown that all deadlines can be met for the tested sensor data analysis benchmarks.

关键词： Big Data batch processing (computers) data analysis functional programming parallel processing performance evaluation EDF algorithm I/O overheads batch processing complex data analysis tasks continuous in-memory sensor data analysis data volume data-intensive real-time applications earliest deadline first algorithm nonpreemptive periodic task model real-time big data management framework real-time information derivation real-time sensor big data analytics schedulability test stringent timing constraints timing agnostic value-added information extraction Analytical models Big data Data analysis Data models Mobile radio mobility management Real-time systems Timing Big Sensor Data Real-Time Information

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