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International Symposium on Information Technology, ITSim

作者： Rohaida Romli Shahida Sulaiman Kamal Zuhairi Zamli College of Arts and Sciences (Applied Sciences) Universiti Utara Malaysia UUM Sintok Kedah Malaysia School of Computer Sciences Universiti Sains Islam Malaysia Penang Malaysia School of Electrical and Electronic Engineering Universiti Sains Islam Malaysia Nibong Tebal Penang Malaysia

automatic programming assessment has recently become an important method in assisting lecturers and instructors of programming courses to automatically mark and grade students' programming exercises as well as to provide useful feedbacks on students' programming solutions. As part of the method, test data generation process plays as an integral part to perform a dynamic testing on students' programs. To date, various automated methods for test data generation particularly in software testing field are available. Unfortunately, they are seldom used in the context of automatic programming assessment research area. Nevertheless, there have been limited studies taking a stab to integrate both of them due to more useful features and to include a better quality program testing coverage. Thus, this paper provides a review on approaches that have been implemented in various studies with regard to automatic programming assessment, test data generation and integration of both of them. This review is aimed at gathering different techniques that have been employed to forward an interested reader the starting points for finding further information regarding its trends. In addition, the result of the review reveals the main gap that exists within the context of the considered areas which contributes to our main research topic of interest.

关键词： Testing Manuals programming profession automatic programming Book reviews Plagiarism

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Cartesian Genetic programming 15

Cartesian Genetic Programming

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Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

作者： Julian Miller Andrew Turner The University of York York United Kingdom

ISBN: (纸本)9781450334884

Cartesian Genetic programming (CGP) is a well-known form of Genetic programming developed by Julian Miller in 1999-2000. In its classic form, it uses a very simple integer address-based genetic representation of a program in the form of a directed graph. Graphs are very useful program representations and can be applied to many domains (e.g. electronic circuits, neural networks). It can handle cyclic or acyclic graphs. In a number of studies, CGP has been shown to be comparatively efficient to other GP techniques. It is also very simple to program. The classical form of CGP has undergone a number of developments which have made it more useful, efficient and flexible in various ways. These include self-modifying CGP (SMCGP), cyclic connections (recurrent-CGP), encoding artificial neural networks and automatically defined functions (modular CGP).SMCGP uses functions that cause the evolved programs to change themselves as a function of time. This makes it possible to find general solutions to classes of problems and mathematical algorithms (e.g. arbitrary parity, n-bit binary addition, sequences that provably compute pi and e to arbitrary precision, and so on).Recurrent-CGP allows evolution to create programs which contain cyclic, as well as acyclic, connections. This enables application to tasks which require internal states or memory. It also allows CGP to create recursive *** encoded artificial neural networks represent a powerful training method for neural networks. This is because CGP is able to simultaneously evolve the networks connections weights, topology and neuron transfer functions. It is also compatible with Recurrent-CGP enabling the evolution of recurrent neural *** tutorial will cover the basic technique, advanced developments and applications to a variety of problem domains. It will present a live demo of how the open source cgplibrary can be used.

关键词： genetic programming evolutionary computation automatic programming

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Improved Lab VIEW Code Generation

Improved Lab VIEW Code Generation

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IEEE Workshop on Advances in Information, Electronic and Electrical Engineering

作者： E. Vavilina G. Gaigals Researcher Ventspils University College

ISBN: (纸本)9781509012022

Before implementation into hardware signal processing algorithms are tested in simulation mode. Lab VIEW provides highly convenient environment for simulation development and also tools for generation of simulation environment that can include simulation itself and collection of simulation data. Despite the fact these tools use Lab VIEW for code generation, it is not easy to understand the principles of code generation and effectively develop simulation generators. This paper presents toolbox for improved LabVIEW code generation. The developed toolbox is based on standard LabVIEW code generation functions maximally simplifying the application and minimizing the necessary amount of tools for code generation. This paper consists of theoretical part about LabVIEW code generation methods, practical part about principles of LabVIEW code generation using scripting and a graphical presentation of improved LabVIEW code generation advantages. The presented graphical results show that the improved LabVIEW code generation is simpler (thus better) and more understandable for practical realization and the code generator is clearer and more comprehensible than the original one.

关键词： automatic programming parallel programming object oriented modeling signal processing algorithms virtual prototyping

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Behavior Composition Meets Supervisory Control

Behavior Composition Meets Supervisory Control

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IEEE International Conference on Systems, Man and Cybernetics

作者： Masoud Barati Richard St-Denis Département d’ informatique Université de Sherbrooke Sherbrooke (Québec) Canada

With the evolution of software engineering since the advent of structured programming until now, software engineers are faced with tremendous challenges mostly due to the development of large software programs that behave as open systems. Multi-agent systems, which consist of multiple cooperating intelligent agents within an environment, form a particular class of such systems. This sort of software program, which carries out operations by repeatedly interacting with dynamic environments, has become more and more complex with the emergence of ubiquitous communication and computing technologies that constantly grow and evolve. Agent-oriented computing constitutes an appealing solution for coping with this level of complexity because systems can be built by combining agents. The automated composition of software artifacts to generate new ones may rest on recent progress in artificial intelligence and automatic control that has its roots in the tradition of program synthesis. The goal is to provide software engineers with effective methods in which the planning and control of software actions are integral parts of composition operators, together with synthesis procedures that automatically generate an execution strategy that governs the discrete dynamics of the composed artifact in order to satisfy given requirements. This approach ensures a higher degree of safety because it relies on formal methods. This paper shows how the behavior composition problem issued from the artificial intelligence community can be solved within the framework of the supervisory control theory with the aim to benefit from all of its rich facets.

关键词： Supervisory control Planning Software Bismuth Control theory Controllability automatic programming

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Evolving Computing and automatic programming

Evolving Computing and Automatic Programming

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2010 The 3rd International Conference on Computational Intelligence and Industrial Application (PACIIA2010)

作者： Qingchun Wang Department of Computer Science Wuhan Institute of Technology Wuhan,Hubei,430073,China Aishu Wang Department of Computer Science Wuhan Institute of Technology Wuhan,Hubei,430073,China

automatic programming is not only one of the central goals of computer science,but also the goal computer science workers are striving for. Some science workers have been exploring and researching in this field for a long time. Significant advances have been made on evolving computer theory,especially on Genetic programming (for short G.P.) theory and method. Those bring hopes to automatic programming.

关键词： automatic programming program structure evolving method

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Design Defect Diagnosis in a Buggy Model of SPARC T1 Processor Using Random Test Program Generator

Design Defect Diagnosis in a Buggy Model of SPARC T1 Process...

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International Conference on Advances in Computing and Communications (ICACC)

作者： K. Brijmohan Nutan Hegde Lekha Pankaj Government Engineering College Bhavnagar Bhavnagar Gujarat IN KMCTCEW Calicut India AWHEC Calicut India

Verification has indisputably become the primary challenge today with recent industry studies estimating that half of all chips manufactured require one or more re-spins. Ideally the performance of the design should be verified for all possible circumstances under which it might be operated in the real world. Unfortunately, it requires a long time to generate and run test sequences. Under the time to market pressure, it is very time consuming to write all test programs manually. This brings about the necessity of developing a random test program generator (RTPG). Proposed RTPG is for verifying the SPARC processor architecture. The approach is in classifying general type of bugs that can get into the EXU unit of SPARC T1 processor design and introducing design defects in the RTL. Several defective models are developed covering the entire functional blocks in the EXU and several coverage models for the test cases run on the defective design were also developed. The direct and random test case generation is applied on the buggy model and various coverage reports are analyzed. This work tends to look back at the fact that verification is a process that is never truly complete. We understand that designs are error-prone and so, the objective of verification is to detect the errors. Yet, no one can really prove that the design is error-free.

关键词： Computer bugs Hardware Testing Sun Field programmable gate arrays automatic programming Analytical models

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Embracing the Algol Effort in Czechoslovakia

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IEEE ANNALS OF THE HISTORY OF COMPUTING 2014年第4期36卷 26-37页

作者： Durnova, Helena Masaryk Univ Fac Educ Brno Czech Republic

Czechoslovakian computing in the 1950s was known more for its fault-tolerant computers than for developments in automatic programming. However, the Algol effort did not go unnoticed, and after publication of the full Algol 60 report, the "Algol craze" spread quickly in Czechoslovakia. This article traces the history of programming methods and techniques in Czechoslovakia up to the first Czechoslovakian Algol compiler in the early 1960s.

关键词： Algol 60 automatic programming Computer languages EPOS Algol Europe History history of computing Information processing Program processors programming programming in Czechoslovakia SAPO computer EPOS computer

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Applying Input-Output Tree to the Implementation of a Rapid Prototyping Tool for Java Web Applications

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2014年第1期30卷 125-139页

作者： Hsia, Chun-Feng Chu, Chih-Ping Natl Cheng Kung Univ Dept Comp Sci & Engn Tainan 701 Taiwan Chia Nan Univ Pharm & Sci Dept Appl Informat & Multimedia Tainan 717 Taiwan

A prototyping tool which facilitates the design of Java applets based on existing Java classes in the repository is developed and embedded into an eLearning platform. An input-output tree is proposed to graphically show the data flow from the input to output of a specific application. In the future, the possible direction of using such similar application as the proposed tool will assist the programmer to assemble the reusable software components from the repository, in which the source codes are generated automatically by means of automatic programming.

关键词： automatic programming CASE input-output tree rapid prototyping software reuse

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Building Efficient Query Engines in a High-Level Language

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PROCEEDINGS OF THE VLDB ENDOWMENT 2014年第10期7卷 853-864页

作者： Klonatos, Yannis Koch, Christoph Rompf, Tiark Chafi, Hassan Ecole Polytech Fed Lausanne Lausanne Switzerland Oracle Labs Redwood Shores CA USA

In this paper we advocate that it is time for a radical rethinking of database systems design. Developers should be able to leverage high-level programming languages without having to pay a price in efficiency. To realize our vision of abstraction without regret, we present LegoBase, a query engine written in the high-level programming language Scala. The key technique to regain efficiency is to apply generative programming: the Scala code that constitutes the query engine, despite its high-level appearance, is actually a program generator that emits specialized, low-level C code. We show how the combination of high-level and generative programming allows to easily implement a wide spectrum of optimizations that are difficult to achieve with existing low-level query compilers, and how it can continuously optimize the query engine. We evaluate our approach with the TPC-H benchmark and show that: (a) with all optimizations enabled, our architecture significantly outperforms a commercial in-memory database system as well as an existing query compiler, (b) these performance improvements require programming just a few hundred lines of high-level code instead of complicated low-level code that is required by existing query compilers and, finally, that (c) the compilation overhead is low compared to the overall execution time, thus making our approach usable in practice for efficiently compiling query engines.

关键词： C (programming language) automatic programming Benchmarking Codes (symbols) Database systems Efficiency Engines Program compilers Query processing Generative programming High level programming language In memory database systems Overall execution Performance improvements Query engines Tpc h benchmarks Wide spectrum

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Specializing Compiler Optimizations Through Programmable Composition For Dense Matrix Computations 47

Specializing Compiler Optimizations Through Programmable Com...

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47th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Yi, Qing Wang, Qian Cui, Huimin Univ Colorado Dept Comp Sci Colorado Springs CO 80907 USA Univ Colorado Colorado Springs CO 80907 USA Univ Chinese Acad Sci Hefei Peoples R China Chinese Acad Sci Inst Software Beijing Peoples R China Chinese Acad Sci SKL Comp Sci Beijing Peoples R China Chinese Acad Sci Inst Comp Tech SKL Comp Architecture Beijing Peoples R China

ISBN: (纸本)9781479969982

General purpose compilers aim to extract the best average performance for all possible user applications. Due to the lack of specializations for different types of computations, compiler attained performance often lags behind those of the manually optimized libraries. In this paper, we demonstrate a new approach, programmable composition, to enable the specialization of compiler optimizations without compromising their generality. Our approach uses a single pass of source-level analysis to recognize a common pattern among dense matrix computations. It then tags the recognized patterns to trigger a sequence of general-purpose compiler optimizations specially composed for them. We show that by allowing different optimizations to adequately communicate with each other through a set of coordination handles and dynamic tags inserted inside the optimized code, we can specialize the composition of general-purpose compiler optimizations to attain a level of performance comparable to those of manually written assembly code by experts, thereby allowing selected computations in applications to benefit from similar levels of optimizations as those manually applied by experts.

关键词： Computers and information processing Computer science programming automatic programming

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