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When proving to a third party that a software system is of high quality or bug-free, a software vendor may have to reveal the source code such that the third party can use a public or their own static code analyzer to check the code. However, revealing ...

The operating system (OS) is the cornerstone for computer systems. It manages hardware and provides fundamental service for user-level applications. Thus, detecting bugs in OSes is important to improve the reliability of computer systems. Static typestate ...

Rust is renowned for its robust memory safety capabilities, yet its distinctive memory management model poses substantial challenges in both writing and understanding programs. Within Rust source code, comments are employed to clearly delineate ...

Command-line options (e.g., -l, -F, -R for ls) given to a command-line program can significantly alternate the behaviors of the program. Thus, fuzzing not only file input but also program options can improve test coverage and bug detection. In this paper, ...

Embedded devices use not only the microcontrollers, but also external devices to realize their functions. Due to lack of external device driver, developers may implement their own one, which can easily cause bugs. Once bugs are injected, debugging is ...

Static analysis frameworks (SAFs) such as Soot and WALA have been a fundamental support in today’s software analysis. They usually adopt various analysis techniques to transform programs into different representations which imply specific properties, ...

Graph Database Systems (GDBs) support efficiently storing and retrieving graph data, and have become a critical component in many important applications. Many widely-used GDBs utilize the Gremlin query language to create, modify, and retrieve data in ...

Static analysis techniques for buffer overflow detection still struggle with being scalable for millions of lines of code, while being precise enough to have an acceptable false positive rate. The checking of buffer overflow necessitates reasoning about ...

Transformer-based neural network models are increasingly employed to handle software engineering issues, such as bug localization and program repair. These models, equipped with a self-attention mechanism, excel at understanding source code context and ...

Increasing studies have shown bugs in multi-language software as a critical loophole in modern software quality assurance, especially those induced by language interactions (i.e., multilingual bugs). Yet existing tool support for bug detection/...

As quantum computing is rising in popularity, the amount of quantum programs and the number of developers writing them are increasing rapidly. Unfortunately, writing correct quantum programs is challenging due to various subtle rules developers need to ...

Code comments are the most important medium for documenting program logic and design. Nevertheless, as modern software undergoes frequent updates and modifications, maintaining the accuracy and relevance of comments becomes a labor-intensive endeavor. ...

While static analysis is instrumental in uncovering software bugs, its precision in analyzing large and intricate codebases remains challenging. The emerging prowess of Large Language Models (LLMs) offers a promising avenue to address these complexities. ...

The use of drones for collecting information and detecting bugs in orchards covered by nets is a challenging problem. The nets help in reducing pest damage, but they also constrain the drone’s flight path, making it longer and more complex. To address ...

Bug localization, which is used to help programmers identify the location of bugs in source code, is an essential task in software development. Researchers have already made efforts to harness the powerful deep learning (DL) techniques to ...

Researchers have already made efforts to harness the powerful deep learning techniques to automate bug localization and further fixing. However, training bug localization model requires a large quantity of data labeled with the bug's exact location, ...

Given a known buggy code snippet, searching for similar patterns in a target project to detect unknown bugs is a reasonable approach. In practice, a search unit, such as a function, may appear quite different from the buggy snippet but actually contains ...

Mastering the knowledge about the bug-prone functions (i.e., sensitive functions) is important to detect bugs. Some automated techniques have been proposed to identify the sensitive functions in large software systems, based on machine learning or ...

Identifying and resolving logic errors can be one of the most frustrating challenges for novices programmers. Unlike syntax errors, for which a compiler or interpreter can issue a message, logic errors can be subtle. In certain conditions, buggy code may ...

Ensuring the correctness of code coverage profilers is crucial, given the widespread adoption of code coverage for various software engineering tasks. Existing validation techniques, such as differential testing and metamorphic testing, have shown ...

Recent advances of Large Language Models (LLMs), e.g., ChatGPT, exhibited strong capabilities of comprehending and responding to questions across a variety of domains. Surprisingly, ChatGPT even possesses a strong understanding of program code. In this ...