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检索条件"主题词=source code model"

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Learning to Edit code: Towards Building General Purpose models for source code Editing

Learning to Edit Code: Towards Building General Purpose Mode...

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作者： Chakraborty, Saikat Columbia University

学位级别：Ph.D., Doctor of Philosophy

The way software developers edit code day-to-day tends to be repetitive, often using existing code elements. Many researchers have tried to automate the repetitive code editing process by mining specific change templates. However, such templates are often manually implemented for automated applications. Consequently, such template-based automated code editing is very tedious to implement. In addition, template-based code editing is often narrowly-scoped and low noise tolerant. Machine Learning, specially deep learning-based techniques, could help us solve these problems because of their generalization and noise tolerance capacities. The advancement of deep neural networks and the availability of vast open-source evolutionary data opens up the possibility of automatically learning those templates from the wild and applying those in the appropriate context. However, deep neural network-based modeling for code changes, and code, in general, introduces some specific problems that need specific attention from the research community. For instance, source code exhibit strictly defined syntax and semantics inherited from the properties of Programming Language (PL). In addition, source code vocabulary (possible number of tokens) can be arbitrarily large. This dissertation formulates the problem of automated code editing as a multi-modal translation problem, where, given a piece of code, the context, and some guidance, the objective is to generate edited code. In particular, we divide the problem into two sub-problems—source code understanding and generation. We empirically show that the deep neural networks (models in general) for these problems should be aware of the PL-properties (i.e., syntax, semantics). This dissertation investigates two primary directions of endowing the models with knowledge about PL-properties—(i) explicit encoding: where we design models catering to a specific property, and (ii) implicit encoding: where we train a very-large model to learn these pro

关键词： AI4SE code editing Programming language Processing source code model source code pretraining Transformer for source code

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Adaptive code Completion with Meta-learning 20

Adaptive Code Completion with Meta-learning

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12th Asia-Pacific Symposium on Internetware (Internetware) - A Software Paradigm for Internet Computing

作者： Fang, Liyu Huang, Zhiqiu Zhou, Yu Chen, Taolue Nanjing Univ Aaeronaut & Astronaut Dept Comp Sci Nanjing Peoples R China

ISBN: (纸本)9781450388191

Since human-written programs have useful local regularities, the ability to adapt to unseen, local context is an important challenge that successful models of source code must overcome. However, the current source code models mostly learn a common code pattern from large scale open-source codebases, which cannot make use of the localness nor satisfy developers' personal preferences. Consequently, fast learning and adapting to unseen code patterns from limited developers' code can provide new insights into source code completion. In this work, we train a base code model that is best able to learn semantic and structural information from context to improve predictions of unseen local tokens and propose an adaptive code model leveraging meta-learning techniques. We demonstrate highly improved performance in experiments on a large scale Java GitHub corpus compared with baselines.

关键词： code completion meta-learning adaptation source code model

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INVocD: Identifier Name Vocabulary Dataset

INVocD: Identifier Name Vocabulary Dataset

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10th IEEE Working Conference on Mining Software Repositories (MSR)

作者： Butler, Simon Wermelinger, Michel Yu, Yijun Sharp, Helen Open Univ Ctr Res Comp Dept Comp Milton Keynes Bucks England

ISBN: (纸本)9781479903450;9781467329361

INVocD is a database of the identifier name declarations and vocabulary found in 60 FLOSS Java projects where the source code structure is recorded and the identifier name vocabulary is made directly available, offering advantages for identifier name research over conventional source code models. The database has been used to support a range of research projects from identifier name analysis to concept location, and provides many opportunities to researchers. INVocD may be downloaded from http://***/36992

关键词： identifier names source code model source code mining

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A source code based model to generate GUI - GUI generation based on source code with declarative language extensions

A source code based model to generate GUI - GUI generation b...

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3rd International Conference on Software and Data Technologies

作者： Monteiro, Marco Oliveira, Paula Goncalves, Ramiro Polytech Inst Leiria Sch Technol & Management Leiria Portugal Univ Tras Os Montes & Alto Douro Engn Dept Vila Real Portugal

ISBN: (纸本)9789898111517

Due to data-driven application nature and its increasing complexity, developing its user interface can be a repetitive and time-consuming activity. Consequently, developers tend to focus more on the user interface aspects and less on business related code. In this paper, we present an alternative approach to graphical user interface development for data-driven applications, where the key concept is the generation of concrete graphical user interface from a source code based model. The model includes the original source code metadata and non-intrusive declarative language extensions that describes the user interface structure. Some Object Relational Mapping tools already use a similar concept to handle interoperability between the data layer and the business layer. Our approach applies the same concept to handle business and presentation layer interoperability. Also, concrete user interface implementation will be delegated to specialized software packages, developed by external entities, that provide complete graphical user interfaces services to the application. When applying our approach, we expect faster graphical user interface development, allowing developers to refocus on the source code and concentrate their efforts on application core logic.

关键词： attribute-oriented programming source code model GUI generation data-driven application

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GUI GENERATION BASED ON LANGUAGE EXTENSIONS A model to Generate GUI, based on source code with Custom Attributes

GUI GENERATION BASED ON LANGUAGE EXTENSIONS A Model to Gener...

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10th International Conference on Enterprise Information Systems

作者： Monteiro, Marco Oliveira, Paula Goncalves, Ramiro Polytech Inst Leiria Sch Technol & Management Leiria Portugal Univ Tras Os Montes Alto Douro Engn Dept Vila Real Portugal

ISBN: (纸本)9789898111364

Due to data-driven application nature and its increasing complexity, developing its user interface can be a repetitive and time-consuming activity. Consequently, developers tend to focus more on the user interface aspects and less on business related code. In this paper, we're presenting an alternative approach to graphical user interface development for data-driven applications, that allows developers to refocus on the source code and concentrate their efforts on application core logic. The key concept behind our approach is the generation of concrete graphical user interface from a source code based model, which includes the original source code metadata and non-intrusive declarative language extensions that describes the user inter-face structure. Concrete user interface implementation will be delegated to specialized software packages, developed by external entities, that provides complete graphical user interfaces services to the application. When applying our approach, we're expecting faster graphical user interface development.

关键词： Attribute-Oriented Programming source code model GUI Generation Data-Driven Application

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