Related papers: An Empirical Study on How the Developers Discussed…
This project focuses on enhancing open-source large language models through instruction-tuning and providing comprehensive evaluations of their performance. We explore how various training data factors, such as quantity, quality, and…
Context: Successfully addressing stakeholder concerns that are related to software system development and operation is crucial to achieving development goals. The importance of using a systematic approach to addressing these concerns…
Quantum computing (QC) is increasingly transitioning toward practical and industrial adoption, highlighting the need to understand how developers engage with quantum technologies. In this study, we analyze 1,404 Stack Overflow posts related…
User satisfaction has always been important in the success of software, regardless of whether it is closed and proprietary or open source software (OSS). OSS users are geographically distributed and include technical as well as novice…
Data cubes are used for analyzing large data sets usually contained in data warehouses. The most popular data cube tools use graphical user interfaces (GUI) to do the data analysis. Traditionally this was fine since data analysts were not…
Background: Ad hoc parsers are pieces of code that use common string functions like split, trim, or slice to effectively perform parsing. Whether it is handling command-line arguments, reading configuration files, parsing custom file…
R and Python are among the most popular languages used in many critical data analytics tasks. However, we still do not fully understand the capabilities of these two languages w.r.t. bugs encountered in data analytics tasks. What type of…
Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python's dynamic nature and extensive usage make it an attractive candidate…
Software libraries are the elementary building blocks of open source software ecosystems, extending the capabilities of programming languages beyond their standard libraries. Although ecosystem health is often quantified using data on…
The library scikit-fda is a Python package for Functional Data Analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated…
Background: Open source software (OSS) libraries are critical components of modern software systems, yet their metadata-particularly links to source code repositories and donation platforms-is often incomplete, outdated, or inconsistent.…
LAMDA-SSL is open-sourced on GitHub and its detailed usage documentation is available at https://ygzwqzd.github.io/LAMDA-SSL/. This documentation introduces LAMDA-SSL in detail from various aspects and can be divided into four parts. The…
To improve software development methods and tools for research software, we first need to understand the current state of the practice. Therefore, we have developed a methodology for assessing the state of the software development practices…
Software development is information-dense knowledge work that requires collaboration with other developers and awareness of artifacts such as work items, pull requests, and files. With the speed of development increasing, information…
With the growing global emphasis on regulating the protection of personal information and increasing user expectation of the same, developing with privacy in mind is becoming ever more important. In this paper, we study the concerns,…
Background: Software security is crucial to ensure that the users are protected from undesirable consequences such as malware attacks which can result in loss of data and, subsequently, financial loss. Technical Debt (TD) is a metaphor…
The use of free and open source software (OSS) is gaining momentum due to the ever increasing availability and use of the Internet. Organizations are also now adopting open source software, despite some reservations, in particular regarding…
Data analysis is at the core of scientific studies, a prominent task that researchers and practitioners typically undertake by programming their own set of automated scripts. While there is no shortage of tools and languages available for…
A concern can be characterized as a developer's intent behind a piece of code, often not explicitly captured in it. We discuss a technique of recording concerns using source code annotations (concern annotations). Using two studies and two…
The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to…