When a computer is used to synthesize a program, there is usually too much information for it to handle. In this paper, we propose the use of stepwise refinement technique, based upon the concept of structured program...
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We describe an approach to automatic discovery of samplers in the form of human interpretable probabilistic programs. Specifically, we learn the procedure code of samplers for one-dimensional distributions. We formula...
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ISBN:
(纸本)9783319416496;9783319416489
We describe an approach to automatic discovery of samplers in the form of human interpretable probabilistic programs. Specifically, we learn the procedure code of samplers for one-dimensional distributions. We formulate a Bayesian approach to this problem by specifying an adaptor grammar prior over probabilistic program code, and use approximate Bayesian computation to learn a program whose execution generates samples that match observed data or analytical characteristics of a distribution of interest. In our experiments we leverage the probabilistic programming system Anglican to perform Markov chain Monte Carlo sampling over the space of programs. Our results are competive relative to state-of-the-art genetic programming methods and demonstrate that we can learn approximate and even exact samplers.
In recent years, there has been a number of studies on automatic program repair (APR) techniques to reduce the burden on developers in fixing defects. The quality of patches generated by APR techniques is verified by ...
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An approach to automatic analytical modeling of electrochemical impedance spectroscopy data by evolutionary programming based on cultural algorithms is proposed. A solution-search strategy based on a cultural mechanis...
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An approach to automatic analytical modeling of electrochemical impedance spectroscopy data by evolutionary programming based on cultural algorithms is proposed. A solution-search strategy based on a cultural mechanism is exploited for defining the equivalent-circuit model automatically: information on search advance is transmitted to all potential solutions, rather than only to a small inheriting subset, such as in a traditional genetic approach. Moreover, with respect to the state of the art, also specific information related to constraints on the application physics knowledge is transferred. Experimental results of the proposed approach implementation in impedance spectroscopy for general-purpose electrochemical circuit analysis and for corrosion monitoring and diagnosing are presented.
Large language models (LLMs) have significantly advanced autonomous software engineering, leading to a growing number of software engineering agents that assist developers in automatic program repair. Issue localizati...
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The data type correspondence problem arises when one tries to interconnect, within a single program, modules written in different languages and therefore within the framework of different type systems. An interconnect...
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The data type correspondence problem arises when one tries to interconnect, within a single program, modules written in different languages and therefore within the framework of different type systems. An interconnection model is proposed which hides details such as interlanguage data type mappings and low level communications, which are irrelevant or confusing to most programmers. Using this model, the authors develop an automated solution to the problem of finding, for a given type in a given programming language, the corresponding type in another programming language. They compare this approach with others which have been proposed in the literature, and discuss a prototype implementation in detail.< >
We present some preliminary results and the main conclusions of a study that we conducted at the University of Algarve, for one of the programming courses in the first year of the Computer Science degree at the Univer...
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ISBN:
(纸本)9781424465682;9781424465712
We present some preliminary results and the main conclusions of a study that we conducted at the University of Algarve, for one of the programming courses in the first year of the Computer Science degree at the University of Algarve. We analyzed the self-reflections made by the students about their study habits and about the skills they acquired in the course. This particular course uses a methodology of blended-learning supported by an automatic judge. The research data were obtained through questionnaires that were distributed and collected during the period of study between the end of classes and the exam. We took into account data from other instruments related to previous work carried out by students, in this course and in previous courses, as well as the performance of the students. We intended to ascertain to what extent the planning, motivation, previous study or knowledge about the type of examination influenced final results. The results suggest measures to be implemented in future editions of the course.
It is necessary to improve the productivity of telecommunication software in order to provide new services quickly. This paper proposes an automatic testing system based on process programming to support the developme...
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It is necessary to improve the productivity of telecommunication software in order to provide new services quickly. This paper proposes an automatic testing system based on process programming to support the development of telecommunication software. This is achieved by using a process-describing language to interpret the testing process that is formally described as a test scenario. By using automatic testing, the productivity can be improved, and the testing period can be reduced. Furthermore, describing the testing process formally promotes process reuse.< >
Nowadays more and more complex railway systems can operate efficiently only if we have tools for planning their maintenance. Train accidents are mainly caused by infrastructure problems, or more specifically by track ...
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Nowadays more and more complex railway systems can operate efficiently only if we have tools for planning their maintenance. Train accidents are mainly caused by infrastructure problems, or more specifically by track geometry *** this paper, we present a support decision system for forecasting the deterioration of track geometry. Two types of defects can be identified for each railway track segment. If a defect belongs to the first type, it must be repaired immediately;otherwise, the defect can be fixed after a specific time period. For resolving this problem, we first decompose the problem into two stages: prediction and classification. Both phases contain a learning phase and a testing phase. The solution technique for both stages are based on automatic programming field and its recently proposed heuristic, called variable neighborhood programming. Our new method is tested on real world problems. The results show that the proposed approach is a good and reliable tool for the preventive maintenance planning of the railway infrastructure.
Gene expression programming (GEP) is a powerful evolutionary algorithm derived from genetic algorithm and genetic programming for system modeling and knowledge discovery. However, when dealing with complex problems, G...
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Gene expression programming (GEP) is a powerful evolutionary algorithm derived from genetic algorithm and genetic programming for system modeling and knowledge discovery. However, when dealing with complex problems, GEP shows quite slow convergence speed, it also probably encounters premature convergence. This paper proposed a clonal selection- based gene expression programming (CS-GEP), which combines the advantages of clonal selection algorithm (CSA) and GEP, overcoming some drawbacks of GEP. CS-GEP is applied into function modeling experiments, the results show that CS-GEP has faster convergence speed and higher modeling precision than that of GEP.
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