4,951 papers · page 30 of 248
Software bugs claim ≈ 50 % of development time and cost the global economy billions of dollars. Once a bug is reported, the assigned developer attempts to identify and understand the source code responsible for the bug and then corrects the code. Over the last five decades, there…
Although machine learning (ML)-enabled software systems seem to be a success story considering their rise in economic power, there are consistent reports from companies and practitioners struggling to bring ML models into production. Many papers have focused on specific, and pure…
Past studies have illustrated the prevalence of UI dark patterns, or user interfaces that can lead end-users toward (unknowingly) taking actions that they may not have intended. Such deceptive UI designs can be either intentional (to benefit an online service) or unintentional (t…
Software engineering research has always being concerned with the improvement of code completion approaches, which suggest the next tokens a developer will likely type while coding. The release of GitHub Copilot constitutes a big step forward, also because of its unprecedented ab…
Pressure for higher productivity and faster delivery is increasingly pervading software organizations. This can lead software engineers to act like chess players playing a gambit—making sacrifices of their technically sound estimates, thus submitting their teams to time pressure.…
Background: Sustainable software engineering (SSE) means creating software in a way that meets present needs without undermining our collective capacity to meet our future needs. It is typically conceptualized as several intersecting dimensions or “pillars”-environmental, social,…
In recent years, template-based and NMT-based automated program repair methods have been widely studied and achieved promising results. However, there are still disadvantages in both methods. The template-based methods cannot fix the bugs whose types are beyond the capabilities o…
Intel's SGX is a confidential computing technique. It allows key functionalities of C/C++/native applications to be confidentially executed in hardware enclaves. However, numerous cloud applications are written in Java. For supporting their confidential computing, state-of-the-ar…
The deep feedforward neural networks (DNNs) are increasingly deployed in socioeconomic critical decision support software systems. DNNs are exceptionally good at finding min-imal, sufficient statistical patterns within their training data. Consequently, DNNs may learn to encode d…
Testing and debugging the implementation of static analysis is a challenging task, often involving significant manual effort from domain experts in a tedious and unprincipled process. In this work, we propose an approach that greatly improves the automation of this process for st…
Automated program repair is already deployed in industry, but concerns remain about repair quality. Recent research has shown that one of the main reasons repair tools produce incorrect (but seemingly correct) patches is imperfect fault localization (FL). This paper demonstrates …
Existing automatic code comment generators mainly focus on producing a general description of functionality for a given code snippet without considering developer intentions. However, in real-world practice, comments are complicated, which often contain information reflecting var…
Modern software systems often exhibit numerous configuration options to tailor them to user requirements, including the system's performance behavior. Performance models derived via machine learning are an established approach for estimating and optimizing configuration-dependent…
Developers constantly learn new APIs, but often lack necessary information from documentation, resorting instead to popular question-and-answer platforms such as Stack Overflow. In this paper, we investigate how to use recent machine-Iearning-based knowledge extraction techniques…
Large language models trained on massive code corpora can generalize to new tasks without the need for task-specific fine-tuning. In few-shot learning, these models take as input a prompt, composed of natural language instructions, a few instances of task demonstration, and a que…
Build systems automate the integration of source code into executables. Maintaining build systems is known to be challenging. Lax build maintenance can lead to costly build breakages or unexpected software behaviour. Code review is a broadly adopted practice to improve software q…
Psychoactive substances, which influence the brain to alter perceptions and moods, have the potential to have positive and negative effects on critical software engineering tasks. They are widely used in software, but that use is not well understood. We present the results of the…
Writing tests is a time-consuming yet essential task during software development. We propose to leverage recent advances in deep learning for text and code generation to assist developers in writing tests. We formalize the novel task of test completion to automatically complete t…
A large number of bug reports are created during the evolution of a software system. Locating the source code files that need to be changed in order to fix these bugs is a challenging task. Information retrieval-based bug localization techniques do so by correlating bug reports w…
While a large number of pre-trained models of source code have been successfully developed and applied to a variety of software engineering (SE) tasks in recent years, our understanding of these pre-trained models is arguably fairly limited. With the goal of advancing our underst…