activity
20202026
most citedOut of the BLEU: how should we assess quality of the Code Generation models?

115 citations · 386 across the 61 of their papers we have counts for

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Showing 2023Show all

11 papers · 1 filter

cs.SE2023★ 2 cited

Dynamic Retrieval-Augmented Generation

Anton Shapkin, Denis Litvinov, Yaroslav Zharov +3

Current state-of-the-art large language models are effective in generating high-quality text and encapsulating a broad spectrum of world knowledge. These models, however, often hal…

cs.SE2023★ 1 cited

From Commit Message Generation to History-Aware Commit Message Completion

Aleksandra Eliseeva, Yaroslav Sokolov, Egor Bogomolov +3

Commit messages are crucial to software development, allowing developers to track changes and collaborate effectively. Despite their utility, most commit messages lack important in…

cs.SE2023★ 1 cited

Overcoming the Mental Set Effect in Programming Problem Solving

Agnia Sergeyuk, Sergey Titov, Yaroslav Golubev +1

This paper adopts a cognitive psychology perspective to investigate the recurring mistakes in code resulting from the mental set (Einstellung) effect. The Einstellung effect is the…

cs.SE2023

Detecting Code Quality Issues in Pre-written Templates of Programming Tasks in Online Courses

Anastasiia Birillo, Elizaveta Artser, Yaroslav Golubev +4

In this work, we developed an algorithm for detecting code quality issues in the templates of online programming tasks, validated it, and conducted an empirical study on the datase…

cs.SE2023

What Writing Assistants Can Learn from Programming IDEs

Sergey Titov, Agnia Sergeyuk, Timofey Bryksin

With the development of artificial intelligence, writing assistants (WAs) are changing the way people interact with text, creating lengthy outputs that can be overwhelming for user…

cs.SE2023

Optimizing Duplicate Size Thresholds in IDEs

Konstantin Grotov, Sergey Titov, Alexandr Suhinin +2

In this paper, we present an approach for transferring an optimal lower size threshold for clone detection from one language to another by analyzing their clone distributions. We s…

cs.SE2023★ 1 cited

Judging Adam: Studying the Performance of Optimization Methods on ML4SE Tasks

Dmitry Pasechnyuk, Anton Prazdnichnykh, Mikhail Evtikhiev +1

Solving a problem with a deep learning model requires researchers to optimize the loss function with a certain optimization method. The research community has developed more than a…

cs.SE2023

Just-in-Time Code Duplicates Extraction

Eman Abdullah AlOmar, Anton Ivanov, Zarina Kurbatova +7

Refactoring is a critical task in software maintenance, and is usually performed to enforce better design and coding practices, while coping with design defects. The Extract Method…

cs.SE2023★ 5 cited

The Effect of Perceptual Load on Performance within IDE in People with ADHD Symptoms

Vseslav Kasatskii, Agnia Sergeyuk, Anastasiia Serova +2

In this paper, we describe the research on how perceptual load can affect programming performance in people with symptoms of Attention Deficit / Hyperactivity Disorder (ADHD). We a…

cs.SE2023

Analyzing the Quality of Submissions in Online Programming Courses

Maria Tigina, Anastasiia Birillo, Yaroslav Golubev +3

Programming education should aim to provide students with a broad range of skills that they will later use while developing software. An important aspect in this is their ability t…

cs.SE2023★ 3 cited

Predicting Tags For Programming Tasks by Combining Textual And Source Code Data

Artyom Lobanov, Egor Bogomolov, Yaroslav Golubev +2

Competitive programming remains a very popular activity that combines both software engineering and education. In order to prepare and to practice, contestants use extensive archiv…