Related papers: SACS: A Code Smell Dataset using Semi-automatic Ge…

Context. Code smells, which are recurring anomalies in design or style, have been extensively researched in professional code. However, their significance in block-based projects created by novices is still largely unknown. Block-based…

Code smells are indicators of potential design flaws in source code and do not appear alone but in combination with other smells, creating complex interactions. While existing literature classifies these smell interactions into collocated,…

In the era of Large Language Models (LLMs), the code summarization technique boosts a lot, along with the emergence of many new significant works. However, the potential of code summarization in the Computer Security Area still remains…

Logging plays a central role in ensuring reproducibility, observability, and reliability in machine learning (ML) systems. While logging is generally considered a good engineering practice, poorly designed logging can negatively affect…

The coding capabilities of large language models (LLMs) have opened up new opportunities for automatic statistical analysis in machine learning and data science. However, before their widespread adoption, it is crucial to assess the…

Object-oriented code smells are well-known concepts in software engineering that refer to bad design and development practices commonly observed in software systems. With the emergence of mobile apps, new classes of code smells have been…

Measuring and evaluating source code similarity is a fundamental software engineering activity that embraces a broad range of applications, including but not limited to code recommendation, duplicate code, plagiarism, malware, and smell…

We present a benchmark dataset for evaluating method-level code generation task. The benchmark contains a dataset of 175 samples for automated evaluation and a dataset of 161 samples for manual evaluation. We also present a new metric for…

Eradication of code smells is often pointed out as a way to improve readability, extensibility and design in existing software. However, code smell detection in large systems remains time consuming and error-prone, partly due to the…

\underline{Context:} Logging is a fundamental yet complex practice in software engineering, essential for monitoring, debugging, and auditing software systems. With the increasing integration of machine learning (ML) components into…

Use case modeling is very popular to represent the functionality of the system to be developed, and it consists of two parts: use case diagram and use case description. Use case descriptions are written in structured natural language (NL),…

The learning and usage of an API is supported by official documentation. Like source code, API documentation is itself a software product. Several research results show that bad design in API documentation can make the reuse of API features…

Semi-supervised learning (SSL) is a promising approach for training deep classification models using labeled and unlabeled datasets. However, existing SSL methods rely on a large unlabeled dataset, which may not always be available in many…

Simulation modelling systems are routinely used to test or understand real-world scenarios in a controlled setting. They have found numerous applications in scientific research, engineering, and industrial operations. Due to their complex…

Current code generation benchmarks focus primarily on functional correctness while overlooking two critical aspects of real-world programming: algorithmic efficiency and code quality. We introduce COMPASS (COdility's Multi-dimensional…

Code smells signal violations of design principles that degrade the internal quality of evolving software systems. Although many tools detect such anomalies using static metrics, they often ignore the development context in which smells…

Code review is considered a key process in the software industry for minimizing bugs and improving code quality. Inspection of review process effectiveness and continuous improvement can boost development productivity. Such inspection is a…

Code review is an important practice in software development, yet it is time-consuming and requires substantial effort. While open-source datasets have been used to train neural models for automating code review tasks, including review…

Test smells can pose difficulties during testing activities, such as poor maintainability, non-deterministic behavior, and incomplete verification. Existing research has extensively addressed test smells in automated software tests but…

Spreadsheets are the most popular end-user programming software, where formulae act like programs and also have smells. One well recognized common smell of spreadsheet formulae is nest-IF expressions, which have low readability and high…