4,951 papers · page 23 of 248
Unmanned aerial vehicles (UAVs) are becoming increasingly ubiquitous in our daily lives. However, like many other complex systems, UAVs are susceptible to software bugs that can lead to abnormal system behaviors and undesirable consequences. It is crucial to study such software b…
A mixed-precision program is a floating-point program that utilizes different precisions for different operations, providing the opportunity of balancing the trade-off between accuracy and performance. Precision tuning aims to find a mixed-precision version of a program that impr…
Deep learning (DL) has emerged as a viable means for identifying software bugs and vulnerabilities. The success of DL relies on having a suitable representation of the problem domain. However, existing DL-based solutions for learning program representations have limitations - the…
Deep neural networks (DNNs) have shown powerful performance in various applications and are increasingly being used in decisionmaking systems. However, concerns about fairness in DNNs always persist. Some efficient white-box fairness testing methods about individual fairness have…
Deep Learning (DL) libraries have significantly impacted various domains in computer science over the last decade. However, developers often face challenges when using the DL APIs, as the development paradigm of DL applications differs greatly from traditional software developmen…
Binary code similarity analysis (BCSA) is a fundamental building block for various software security, reverse engineering, and re-engineering applications. Existing research has applied deep neural networks (DNNs) to measure the similarity between binary code, following the major…
Autonomous vehicles (AVs) must be able to operate in a wide range of scenarios including those in the long tail distribution that include rare but safety-critical events. The collection of sensor input and expected output datasets from such scenarios is crucial for the developmen…
Given the growing importance of smart contracts in various applications, ensuring their security and reliability is critical. Fuzzing, an effective vulnerability detection technique, has recently been widely applied to smart contracts. Despite numerous studies, a systematic inves…
Despite the benefits of using third-party libraries (TPLs), the misuse of TPL functions raises quality and security concerns. Using traditional static analysis to detect bugs caused by TPL function is non-trivial. One promising solution would be to automatically generate and pers…
Software composition analysis (SCA) tools have been widely adopted to identify vulnerable libraries used in software applications. Such SCA tools depend on a vulnerability database to know affected libraries of each vulnerability. However, it is labor-intensive and error prone fo…
Fuzzing has achieved tremendous success in discovering bugs and vulnerabilities in various software systems. Systems under test (SUTs) that take in programming or formal language as inputs, e.g., compilers, runtime engines, constraint solvers, and software libraries with accessib…
Virtual personal assistants (VPA) services encompass a large number of third-party applications (or apps) to enrich their functionalities. These apps have been well examined to scrutinize their data collection behaviors against their declared privacy policies. Nonetheless, it is …
Logging, which aims to determine the position of logging statements, the verbosity levels, and the log messages, is a crucial process for software reliability enhancement. In recent years, numerous automatic logging tools have been designed to assist developers in one of the logg…
Functional code clone detection is important for software maintenance. In recent years, deep learning techniques are introduced to improve the performance of functional code clone detectors. By representing each code snippet as a vector containing its program semantics, syntactic…
Log parsing, which involves log template extraction from semi-structured logs to produce structured logs, is the first and the most critical step in automated log analysis. However, current log parsers suffer from limited effectiveness for two reasons. First, traditional data-dri…
Video-based bug reports are increasingly being used to document bugs for programs centered around a graphical user interface (GUI). However, developing automated techniques to manage video-based reports is challenging as it requires identifying and understanding often nuanced vis…
Code idioms are commonly used patterns, techniques, or practices that aid in solving particular problems or specific tasks across multiple software projects. They can improve code quality, performance, and maintainability, and also promote program standardization and reuse across…
Reentrancy, a notorious vulnerability in smart contracts, has led to millions of dollars in financial loss. However, current smart contract vulnerability detection tools suffer from a high false positive rate in identifying contracts with reentrancy vulnerabilities. Moreover, onl…
Fault Localization (FL) aims to automatically localize buggy lines of code, a key first step in many manual and automatic debugging tasks. Previous FL techniques assume the provision of input tests, and often require extensive program analysis, program instrumentation, or data pr…
As a relatively new programming language, Rust is designed to provide both memory safety and runtime performance. To achieve this goal, Rust conducts rigorous static checks against its safety rules during compilation, effectively eliminating memory safety issues that plague C/C++…