4,951 papers · page 21 of 248
Code translation aims to convert source code from one programming language (PL) to another. Given the promising abilities of large language models (LLMs) in code synthesis, researchers are exploring their potential to automate code translation. The prerequisite for advancing the …
C is an unsafe language. Researchers have been developing tools to port C to safer languages such as Rust, Checked C, or Go. Existing tools, however, resort to preprocessing the source file first, then porting the resulting code, leaving barely recognizable code that loses macro …
Hyperproperties are used to define correctness requirements that involve relations between multiple program executions. This allows, for instance, to model security and concurrency requirements, which cannot be expressed by means of trace properties.
As a dynamic programming language, Python has become increasingly popular in recent years. Although the dynamic type system of Python facilitates the developers in writing Python programs, it also brings type errors at run-time which are prevalent yet not easy to fix. There exist…
Python is the top popular programming language used in the open-source community, largely owing to the extensive support from diverse third-party libraries within the PyPI ecosystem. Nevertheless, the utilization of third-party libraries can potentially lead to conflicts in depen…
Scientists write and maintain software artifacts to construct, validate, and apply scientific theories. Despite the centrality of software in their work, their practices differ significantly from those of professional software engineers. We sought to understand what makes scienti…
Deep learning source code models have been applied very successfully to the problem of automated program repair. One of the standing issues is the small input window of current models which often cannot fully fit the context code required for a bug fix (e.g., method or class decl…
Deep neural network (DNN) models have become increasingly crucial components of intelligent software systems. However, training a DNN model is typically expensive in terms of both time and computational resources. To address this issue, recent research has focused on reusing exis…
Deep learning vulnerability detection has shown promising results in recent years. However, an important challenge that still blocks it from being very useful in practice is that the model is not robust under perturbation and it cannot generalize well over the out-of-distribution…
Regression testing is an important part of the development process but suffers from the presence of flaky tests. Flaky tests nondeterministically pass or fail when run on the same code, misleading developers about the correctness of their changes. A common type of flaky tests are…
Automatic crash bucketing is a crucial phase in the software development process for efficiently triaging bug reports. It generally consists in grouping similar reports through clustering techniques. However, with real-time streaming bug collection, systems are needed to quickly …
Mobile apps have become popular for providing artificial intelligence (AI) services via on-device machine learning (ML) techniques. Unlike accomplishing these AI services on remote servers traditionally, these on-device techniques process sensitive information required by AI serv…
Generative artificial intelligence systems such as large language models (LLMs) exhibit powerful capabilities that many see as the kind of flexible and adaptive intelligence that previously only humans could exhibit. I address directions and implications of LLMs for software engi…
While software plagiarism detectors have been used for decades, the assumption that evading detection requires programming proficiency is challenged by the emergence of automated plagiarism generators. These generators enable effortless obfuscation attacks, exploiting vulnerabili…
Deep learning (DL) has been a common thread across several recent techniques for vulnerability detection. The rise of large, publicly available datasets of vulnerabilities has fueled the learning process underpinning these techniques. While these datasets help the DL-based vulner…
To ensure the validity of software engineering and IT security studies with professional programmers, it is essential to identify participants without programming skills. Existing screening questions are efficient, cheating robust, and effectively differentiate programmers from n…
Dynamic data race detection has emerged as a key technique for ensuring reliability of concurrent software in practice. However, dynamic approaches can often miss data races owing to non-determinism in the thread scheduler. Predictive race detection techniques cater to this short…
The relatively recent public release of generative artificial intelligence (AI) systems has ignited a significant leap in awareness of the capabilities of AI. In parallel, there has been a recognition of AI system limitations and the bias inherent in systems created by humans. Ex…
Rogue updates, an important type of software supply-chain attack in which attackers conceal malicious code inside updates to benign software, are a growing problem due to their stealth and effectiveness. We design and implement RogueOne, a system for detecting rogue updates to Ja…
Numerous third-party libraries introduced into client projects are not actually required, resulting in modern software being gradually bloated. Software developers may spend much unnecessary effort to manage the bloated dependencies: keeping the library versions up-to-date, makin…