Genetic programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization tec...
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Genetic programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs;imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications;vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a "population" of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a "fitness function" and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a "correct" program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.
A relational database is a digital collection of data constructed on data stored in relations. RDF (Resource Description Framework) is a standard exemplification for data substitution on the Web RDF Schema is a semant...
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ISBN:
(数字)9789811360527
ISBN:
(纸本)9789811360527
A relational database is a digital collection of data constructed on data stored in relations. RDF (Resource Description Framework) is a standard exemplification for data substitution on the Web RDF Schema is a semantic addition of RDF. It renders the technique for narrating groups of allied resources. The direct mapping of RDF interprets the description of data in a relational database. It uses input data, schema and result in RDF graph, termed as direct graph. In this paper, online automatic conversion tool of RDB to RDF and RDFS is discussed. RDB to RDF and its schema is used to get relationships between tables using foreign keys and generate direct graph using data of RDB as input source. RDFS is a general-purpose language for demonstrating RDF. In RDFS, Object Oriented programming concepts are used to find Classes, Sub-Classes, Properties and SubProperties etc. to define relationships between the resources automatically.
This paper proposes a probabilistic reachability repair solution that enables abstract machines to automatically evolve and satisfy desired requirements. The solution is a combination of the B-method, machine learning...
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ISBN:
(纸本)9781728146485
This paper proposes a probabilistic reachability repair solution that enables abstract machines to automatically evolve and satisfy desired requirements. The solution is a combination of the B-method, machine learning and program synthesis. The B-method is used to formally specify an abstract machine and analyse the reachability of the abstract machine. Machine learning models are used to approximate features hidden in the semantics of the abstract machine. When the abstract machine fails to reach a desired state, the machine learning models are used to discover missing transitions to the state. Inserting the discovered transitions into the original abstract machine will lead to a repaired abstract machine that is capable of achieving the state. To obtain the repaired abstract machine, a set of insertion repairs are synthesised from the discovered transitions and are simplified using context-free grammars. Experimental results reveal that the reachability repair solution is applicable to a wide range of abstract machines and can accurately discover transitions that satisfy the requirements of reachability. Moreover, the results demonstrate that random forests are efficient machine learning models on transition discovery tasks. Additionally, we argue that the automated reachability repair process can improve the efficiency of software development.
automatically building programs has been a research goal for over 40 years. Code search technology, particularly code search combined with directed program transformations and validation, has the potential to address ...
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Most recent theoretical literature on program obfuscation is based on notions like virtual black box (VBB) obfuscation and indistinguishability obfuscation (iO). These notions are very strong and are hard to satisfy. ...
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ISBN:
(数字)9781665403924
ISBN:
(纸本)9781665403931
Most recent theoretical literature on program obfuscation is based on notions like virtual black box (VBB) obfuscation and indistinguishability obfuscation (iO). These notions are very strong and are hard to satisfy. Further, they offer far more protection than is typically required in practical applications. On the other hand, the security notions introduced by software security researchers are suitable for practical designs but are not formal or precise enough to enable researchers to provide a quantitative security assurance. Hence, in this paper, we introduce a new formalism for practical program obfuscation that still allows rigorous security proofs. We believe our formalism will make it easier to analyse the security of obfuscation schemes. To show the flexibility and power of our formalism, we give a number of examples. Moreover, we explain the close relationship between our formalism and the task of providing obfuscation challenges.
automatic programming has been researched for a long time. A variety of methodologies have been proposed. However, they have limited applicability, or they can generate only a few lines of code. In this research, the ...
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ISBN:
(纸本)9781538664308
automatic programming has been researched for a long time. A variety of methodologies have been proposed. However, they have limited applicability, or they can generate only a few lines of code. In this research, the authors are trying to generate source code of Java methods based on their specifications. In this paper, we propose a reuse-based code generation technique with method signature and test cases. First, our technique searches existing Java methods whose signature are the same as the one input by a user. Then, our technique reworks each of them by using test cases input by the user. Methods passing all the test cases are given to the user. At this moment, the authors have implemented a naive prototype and conducted experiments with four open source software. In total, our technique succeeded to generate 18 Java methods. In this paper, we also introduce some actual examples of generated Java methods and some ideas to enhance our technique.
To solve a problem without any knowledge of its solution, a variety evolutionary computation approach based automatic programming methods have been developed. Artficial Bee Colony programming (ABCP) is one of the rece...
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To solve a problem without any knowledge of its solution, a variety evolutionary computation approach based automatic programming methods have been developed. Artficial Bee Colony programming (ABCP) is one of the recently proposed automatic programming methods. ABCP has been preferred and applied to various problems by researchers from different disciplines like other evolutionary computation approach based algorithms. In this study, a cloud-based web application (ABCPWeb) that allows to use the ABCP with no need to have any programming knowledge is proposed. ABCPWeb is tested on the benchmark problems that are previously solved by ABCP. The success of ABCPWeb is revealed by comparing the experimental results with the results of basic ABCP.
We consider the automatic synthesis of an entity extractor, in the form of a regular expression, from examples of the desired extractions in an unstructured text stream. This is a long-standing problem for which many ...
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We consider the automatic synthesis of an entity extractor, in the form of a regular expression, from examples of the desired extractions in an unstructured text stream. This is a long-standing problem for which many different approaches have been proposed, which all require the preliminary construction of a large dataset fully annotated by the user. In this paper, we propose an active learning approach aimed at minimizing the user annotation effort: the user annotates only one desired extraction and then merely answers extraction queries generated by the system. During the learning process, the system digs into the input text for selecting the most appropriate extraction query to be submitted to the user in order to improve the current extractor. We construct candidate solutions with genetic programming (GP) and select queries with a form of querying-by-committee, i.e., based on a measure of disagreement within the best candidate solutions. All the components of our system are carefully tailored to the peculiarities of active learning with GP and of entity extraction from unstructured text. We evaluate our proposal in depth, on a number of challenging datasets and based on a realistic estimate of the user effort involved in answering each single query. The results demonstrate high accuracy with significant savings in terms of computational effort, annotated characters, and execution time over a state-of-the-art baseline.
This paper introduces current research on automatic performance tuning, specifically in the Japanese community, from two aspects. First, we discuss autotuning (AT) research from the viewpoint of AT frameworks, includi...
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This paper introduces current research on automatic performance tuning, specifically in the Japanese community, from two aspects. First, we discuss autotuning (AT) research from the viewpoint of AT frameworks, including AT methodology, computer languages, and performance models. In addition, target algorithms and applications of AT research are discussed, along with their functions. Then, we focus on the fast Fourier transform (FFT) as a major topic in the applications of adaptable and effective AT technologies and present state-of-the-art algorithms for advanced multicore architectures. An AT methodology for the FFT algorithm is also discussed.
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