Timofey Bryksin

JetBrains Research

In many MOOCs, whenever a student completes a programming task, they can see previous solutions of other students to find potentially different ways of solving the problem and to learn new coding constructs. However, a lot of MOOCs simply show the most recent solutions, disregarding their diversity or quality, and thus hindering the students' oppor...

Computational notebooks became indispensable tools for research-related development, offering unprecedented interactivity and flexibility in the development process. However, these benefits come at the cost of reproducibility and an increased potential for bugs. With the rise of code-fluent Large Language Models empowered with agentic techniques, s...

Commit message generation (CMG) is a crucial task in software engineering that is challenging to evaluate correctly. When a CMG system is integrated into the IDEs and other products at JetBrains, we perform online evaluation based on user acceptance of the generated messages. However, performing online experiments with every change to a CMG system...

Nowadays, integration of AI-driven tools within Integrated Development Environments (IDEs) is reshaping the software development lifecycle. Existing research highlights that users expect these tools to be efficient, context-aware, accurate, user-friendly, customizable, and secure. However, a major gap remains in understanding developers' needs and...

Students often struggle with solving programming problems when learning to code, especially when they have to do it online, with one of the most common disadvantages of working online being the lack of personalized help. This help can be provided as next-step hint generation, i.e., showing a student what specific small step they need to do next to...

Software developers often repeat the same code changes within a project or across different projects. These repetitive changes are known as “code change patterns” (CPATs). Automating CPATs is crucial to expedite the software development process. While current Transformation by Example (TBE) techniques can automate CPATs, they are limited by the qua...

The rapid rise of Large Language Models (LLMs) has changed software development, with tools like Copilot, JetBrains AI Assistant, and others boosting developers' productivity. However, developers now spend more time reviewing code than writing it, highlighting the importance of Code Readability for code comprehension. Our previous research found th...

Nowadays, the fields of code and natural language processing are evolving rapidly. In particular, models become better at processing long context windows - supported context sizes have increased by orders of magnitude over the last few years. However, there is a shortage of benchmarks for code processing that go beyond a single file of context, whi...

The last several years saw the emergence of AI assistants for code -- multi-purpose AI-based helpers in software engineering. Their quick development makes it necessary to better understand how specifically developers are using them, why they are not using them in certain parts of their development workflow, and what needs to be improved. In this w...

Recent advancements in code-fluent Large Language Models (LLMs) enabled the research on repository-level code editing. In such tasks, the model navigates and modifies the entire codebase of a project according to request. Hence, such tasks require efficient context retrieval, i.e., navigating vast codebases to gather relevant context. Despite the r...

Excessively long methods, loaded with multiple responsibilities, are challenging to understand, debug, reuse, and maintain. The solution lies in the widely recognized Extract Method refactoring. While the application of this refactoring is supported in modern IDEs, recommending which code fragments to extract has been the topic of many research too...

In this technical report, we present three novel datasets of Kotlin code: KStack, KStack-clean, and KExercises. We also describe the results of fine-tuning CodeLlama and DeepSeek models on this data. Additionally, we present a version of the HumanEval benchmark rewritten by human experts into Kotlin - both the solutions and the tests. Our results d...

In recent years, several industrial solutions for the problem of multi-token code completion have appeared, each making a great advance in the area but mostly focusing on cloud-based runtime and avoiding working on the end user's device. In this work, we describe our approach for building a multi-token code completion feature for the JetBrains' Int...

In many MOOCs, whenever a student completes a programming task, they can see previous solutions of other students to find potentially different ways of solving the problem and learn new coding constructs. However, a lot of MOOCs simply show the most recent solutions, disregarding their diversity or quality. To solve this novel problem, we adapted t...

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 tendency to approach problem-solving with a preconceived mindset, often overlooking better solutions that may be available. This effect can significantly impact creative...

Commit messages are crucial to software development, allowing developers to track changes and collaborate effectively. Despite their utility, most commit messages lack important information since writing high-quality commit messages is tedious and time-consuming. The active research on commit message generation (CMG) has not yet led to wide adoptio...

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 tendency to approach problem-solving with a preconceived mindset, often overlooking better solutions that may be available. This effect can significantly impact creative...

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 asked developers to complete the Barkley Deficits in Executive Functioning Scale, which indicates the presence and severity levels of ADHD symptoms. After that, participants...

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 dataset of student solutions. The algorithm consists of analyzing recurring unfixed issues in solutions of different students, matching them with the code of the template, and...

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 users. The programming field has long addressed this issue, and Integrated Development Environments (IDEs) have been created for efficient software development, helping progr...

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 showcase this method by transferring the threshold from regular Python scripts to Jupyter notebooks for using in two JetBrains IDEs, Datalore and DataSpell.

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 to write code that is not only correct but also of high quality. Unfortunately, this is difficult to control in the setting of a massive open online course. In this paper,...

Competitive programming remains a very popular activity that combines both software engineering and education. In order to prepare and to practice, contestants use extensive archives of problems from past contents available on various competitive programming platforms. One way to make this process more effective is to provide an automatic tag syste...

In software engineering, different approaches and machine learning models leverage different types of data: source code, textual information, historical data. An important part of any project is its dependencies. The list of dependencies is relatively small but carries a lot of semantics with it, which can be used to compare projects or make judgem...

In recent years, researchers have created and introduced a significant number of various code generation models. As human evaluation of every new model version is unfeasible, the community adopted automatic evaluation metrics such as BLEU to approximate the results of human judgement. These metrics originate from the machine translation domain and...

As researchers and practitioners apply Machine Learning to increasingly more software engineering problems, the approaches they use become more sophisticated. A lot of modern approaches utilize internal code structure in the form of an abstract syntax tree (AST) or its extensions: path-based representation, complex graph combining AST with addition...

Code clones are pairs of code snippets that implement similar functionality. Clone detection is a fundamental branch of automatic source code comprehension, having many applications in refactoring recommendation, plagiarism detection, and code summarization. A particularly interesting case of clone detection is the detection of semantic clones, i.e...

Machine Learning for Software Engineering (ML4SE) is an actively growing research area that focuses on methods that help programmers in their work. In order to apply the developed methods in practice, they need to achieve reasonable quality in order to help rather than distract developers. While the development of new approaches to code representat...

Integrated Development Environments (IDE) are designed to make users more productive, as well as to make their work more comfortable. To achieve this, a lot of diverse tools are embedded into IDEs, and the developers of IDEs can employ anonymous usage logs to collect the data about how they are being used to improve them. A particularly important c...

The automatic collection of stack traces in bug tracking systems is an integral part of many software projects and their maintenance. However, such reports often contain a lot of duplicates, and the problem of de-duplicating them into groups arises. In this paper, we propose a new approach to solve the deduplication task and report on its use on th...

A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves higher performance as opposed to using a corpus of code written in just one programming language. However, no analysis was made with respect to fine-tuning monolingual PLMs....

In recent years, Jupyter notebooks have grown in popularity in several domains of software engineering, such as data science, machine learning, and computer science education. Their popularity has to do with their rich features for presenting and visualizing data, however, recent studies show that notebooks also share a lot of drawbacks: high numbe...

In this paper, we present Lupa - a framework for large-scale analysis of the programming language usage. Lupa is a command line tool that uses the power of the IntelliJ Platform under the hood, which gives it access to powerful static analysis tools used in modern IDEs. The tool supports custom analyzers that process the rich concrete syntax tree o...

Reflection in Kotlin is a powerful mechanism to introspect program behavior during its execution at run-time. However, among the variety of practical tasks involving reflection, there are scenarios when the poor performance of run-time approaches becomes a significant disadvantage. This problem manifests itself in Kotless, a popular framework for d...

We have developed a plugin for IntelliJ IDEA called AntiCopyPaster that tracks the pasting of code inside the IDE and suggests appropriate Extract Method refactorings to combat the propagation of duplicates. To implement the plugin, we gathered a dataset of code fragments that should and should not be extracted, compiled a list of metrics of code t...

Jupyter notebooks represent a unique format for programming - a combination of code and Markdown with rich formatting, separated into individual cells. We propose to perceive a Jupyter Notebook cell as a simplified and raw version of a programming function. Similar to functions, Jupyter cells should strive to contain singular, self-contained action...

In software engineering, it is not enough to simply write code that only works as intended, even if it is free from vulnerabilities and bugs. Every programming language has a style guide and a set of best practices defined by its community, which help practitioners to build solutions that have a clear structure and therefore are easy to read and ma...

The popularity of cloud technologies has led to the development of a new type of applications that specifically target cloud environments. Such applications require a lot of cloud infrastructure to run, which brought about the Infrastructure as Code approach, where the infrastructure is also coded using a separate language in parallel to the main a...

Similarly to production code, code smells also occur in test code, where they are called test smells. Test smells have a detrimental effect not only on test code but also on the production code that is being tested. To date, the majority of the research on test smells has been focusing on programming languages such as Java and Scala. However, there...

In software engineering, a great number of new approaches are being actively researched, and a lot of tools are being developed based on them. These tools require a framework for their creation and an opportunity to be used by potential developers. Modern IDEs provide both. In this paper, we describe the main capabilities of the IntelliJ Platform t...

Many code changes that developers make in their projects are repeated and constitute recurrent change patterns. It is of interest to collect such patterns from the version history of open-source repositories and suggest the most useful of them as quick fixes. In this paper, we present Revizor - a tool aimed to build custom plugins for PyCharm, a po...

Inspection of code changes is a time-consuming task that constitutes a big part of everyday work of software engineers. Existing IDEs provide little information about the semantics of code changes within the file editor view. Therefore developers have to track changes across multiple files, which is a hard task with large codebases. In this paper,...

The popularity of cloud technologies has led to the development of a new type of applications that specifically target cloud environments. Such applications require a lot of cloud infrastructure to run, which brought about the Infrastructure as Code approach, where the infrastructure is also coded using a separate language in parallel to the main a...

Similarly to production code, code smells also occur in test code, where they are called test smells. Test smells have a detrimental effect not only on test code but also on the production code that is being tested. To date, the majority of the research on test smells has been focusing on programming languages such as Java and Scala. However, there...

Software development is a complex process that includes many different tasks besides just writing code. One of the aspects of software engineering is selecting and managing licenses for the given project. In this paper, we present Sorrel - a plugin for managing licenses and detecting potential incompatibilities for IntelliJ IDEA, a popular Java IDE...

Despite the availability of refactoring as a feature in popular IDEs, recent studies revealed that developers are reluctant to use them, and still prefer the manual refactoring of their code. At JetBrains, our goal is to fully support refactoring features in IntelliJ-based IDEs and improve their adoption in practice. Therefore, we start by raising...

Online programming courses are becoming more and more popular, but they still have significant drawbacks when compared to the traditional education system, e.g., the lack of feedback. In this study, we apply machine learning methods to improve the feedback of automated verification systems for programming assignments. We propose an approach that pr...

Code cloning plays a very important role in open-source software engineering. The presence of clones within a project may indicate a need for refactoring, and clones between projects are even more interesting, since code migration takes place and violations are possible. But how is code being copied? How prevalent is the process and on what level d...

A lot of problems in the field of software engineering - bug fixing, commit message generation, etc. - require analyzing not only the code itself but specifically code changes. Applying machine learning models to these tasks requires us to create numerical representations of the changes, i.e. embeddings. Recent studies demonstrate that the best way...

Code changes constitute one of the most important features of software evolution. Studying them can provide insights into the nature of software development and also lead to practical solutions - recommendations and automations of popular changes for developers. In our work, we developed a tool called PythonChangeMiner that allows to discover code...

Recent trends in Web development demonstrate an increased interest in serverless applications, i.e. applications that utilize computational resources provided by cloud services on demand instead of requiring traditional server management. This approach enables better resource management while being scalable, reliable, and cost-effective. However, i...