Data-based code synthesis in IntelliJ IDEA

Тимофей Александрович Брыксин, Владислав Дмитриевич Танков

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

Automatic code synthesis has been attracting more attention lately. Some recent papers in this traditionally academic field even present results that could be applicable for industrial programmers. This paper provides an overview of Bayesian Sketch Learning (BSL) approach, describes basic concepts and workflow of a BSL synthesizer. Based on this we discuss an architecture of a configurable BSL synthesizer that could work as a part of an integrated development environment. We describe the implementation of such synthesizer for JVM platform and its integration with IntelliJ IDEA as a plugin. Two approaches to implement user interaction in a plugin like this are presented: method annotations and a domain-specific language. The paper concludes with an evaluation and a discussion on limitations of selected approach for industrial programmers.

Язык оригиналаанглийский
Название основной публикацииThird Conference on Software Engineering and Information Management (SEIM-2018)
Место публикацииSaint Petersburg
Страницы37-43
Число страниц7
Том2135
СостояниеОпубликовано - 2018

Серия публикаций

НазваниеCEUR Workshop Proceedings
ISSN (печатное издание)1613-0073

Предметные области Scopus

  • Компьютерные науки (все)

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