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Software development increasingly depends on libraries and frameworks to increase productivity and reduce time-to-market. Despite this fact, we still lack techniques to assess developers expertise in widely popular libraries and frameworks.…

Context: Software developers are increasingly facing the challenges of writing code that is not only concurrent but also correct. Objective: To help these developers, it is necessary to understand concurrency topics they are interested in,…

Context: Modern software systems (e.g., Apache Spark) are usually written in multiple programming languages (PLs). There is little understanding on the phenomenon of multi-programming-language commits (MPLCs), which involve modified source…

Today's pursuit of a single Large Language Model (LMM) for all software engineering tasks is resource-intensive and overlooks the potential benefits of complementarity, where different models contribute unique strengths. However, the degree…

Log statements capture critical information for software maintenance activities such as testing, debugging, and failure analysis. Because of this importance, developers must carefully design log statements, which requires significant…

Much research that analyzes the evolution of a software ecosystem is confined to its own boundaries. Evidence shows, however, that software ecosystems co-evolve independently with other software ecosystems. In other words, understanding the…

Understanding large software systems is a challenging task, especially when code is distributed across multiple repositories and microservices. Developers often need to reason not only about the structure of the code, but also about its…

The open-source software (OSS) community has historically been dominated by English as the primary language for code, documentation, and developer interactions. However, with growing global participation and better support for non-Latin…

Developers frequently reuse Stack Overflow code snippets, yet the quality of these snippets remains unevenly understood, particularly across programming languages and geographic contexts. This study investigates code quality in Stack…

With the popularity of software ecosystems, the number of open source components (known as packages) has grown rapidly. Identifying high-quality and well-maintained packages from a large pool of packages to depend on is a basic and…

The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal value of generative AI tools in many communities. However, the…

Open-source software communities thrive on global collaboration and contributions from diverse participants. This study explores the Rust programming language ecosystem to understand its contributors' demographic composition and interaction…

Many software projects implement APIs and algorithms in multiple programming languages. Maintaining such projects is tiresome, as developers have to ensure that any change (e.g., a bug fix or a new feature) is being propagated, timely and…

Software developers are increasingly required to understand fundamental Data science (DS) concepts. Recently, the presence of machine learning (ML) and deep learning (DL) has dramatically increased in the development of user applications,…

For tasks like code synthesis from natural language, code retrieval, and code summarization, data-driven models have shown great promise. However, creating these models require parallel data between natural language (NL) and code with…

Language Models (LMs) have shown their application for tasks pertinent to code and several code~LMs have been proposed recently. The majority of the studies in this direction only focus on the improvements in performance of the LMs on…

Open-source software (OSS) is widely spread in industry, research, and government. OSS represents an effective development model because it harnesses the decentralized efforts of many developers in a way that scales. As OSS developers work…

Large Language Models (LLMs) have achieved state-of-the-art performance across software engineering tasks, from code generation to translation. However, we identify and systematically evaluate a critical failure mode: Programming Language…

Spoken Language Understanding (SLU), which aims to extract user semantics to execute downstream tasks, is a crucial component of task-oriented dialog systems. Existing SLU datasets generally lack sufficient diversity and complexity, and…

Studies over the past decade demonstrated that developers contributing to open source software systems tend to self-organize in "emerging" communities. This latent community structure has a significant impact on software quality. While…