26,098 papers · page 62 of 1,305
Despite great progress in fuzzing browser APIs, systematic approaches for testing web storage techniques remain absent. IndexedDB, the most popular NoSql database in modern browsers, brings unique challenges for fuzzing its API due to its asynchronous event-driven feature and str…
Modern video games pose significant challenges for traditional automated testing algorithms, yet intensive testing is crucial to ensure game quality. To address these challenges, researchers designed gaming agents using Reinforcement Learning, Imitation Learning, or Large Languag…
The development of Large Language Models (LLMs) enables LLM-based GUI testing to interact with graphical user interfaces by understanding GUI screenshots and generating actions, which are widely applied in industry and academia. However, current approaches test each app in isolat…
Identifying which software versions are affected by a vulnerability is critical for patching, risk mitigation. Despite a growing body of tools, their real-world effectiveness remains unclear due to narrow evaluation scopes—often limited to early SZZ variants, outdated techniques,…
The NFT ecosystem represents an interconnected, decentralized environment that encompasses the creation, distribution, and trading of Non-Fungible Tokens (NFTs), where key actors, such as marketplaces, sellers, and buyers, utilize smart contracts to facilitate secure, transparent…
Wi-Fi Network Interface Cards (NICs) are vital for enabling wireless connectivity across a wide range of devices. Ensuring their security is critical, as vulnerabilities can expose entire networks to threats. Fuzzing is a promising technique for detecting such flaws. However, exi…
The Linux distribution kernel differs significantly from the mainline kernel, incorporating additional features and vendor-specific extensions. Among these additions, many runtime parameter interfaces are unique to distribution kernels, which expands the attack surface and increa…
Security patch porting aims to adapt patches developed for one software version so they can be used in another version. This approach is crucial for maintaining the security of software systems over time. However, existing works often rely on predefined rules to understand patche…
Token-inconsistency bugs (TIBs) involve the misuse of syntactically valid yet incorrect code tokens, such as misused variables and erroneous function invocations, which can often lead to software bugs. Unlike simple syntactic bugs, TIBs occur at the semantic level and are subtle …
Ensuring safety and providing rigorous behavioral guarantees are critical for robotic systems operating in high-stakes environments such as autonomous driving. Field testing is common, but costly and risky. Simulation-based testing offers a safer and lower-cost alternative for au…
Automated testing is essential for evaluating and improving the reliability of Large Language Models (LLMs), yet the lack of automated oracles for verifying output correctness remains a key challenge. We present LLMorph, an automated testing tool specifically designed for LLMs pe…
We present Cryptbara, a precise approach for detecting Python cryptographic API misuses. Cryptographic APIs are widely used to ensure data security, but their improper use can inadvertently compromise the security of entire systems. Existing approaches often fail to capture how c…
Unit testing is essential for ensuring software reliability and correctness. Classic Search-Based Software Testing (SBST) methods and concolic execution-based approaches for generating unit tests often fail to achieve high coverage due to difficulties in handling complex program …
Token-Level code completion is one of the most critical features in modern Integrated Development Environments (IDEs). It assists developers by suggesting relevant identifiers and APIs during coding. While completions are typically derived from static analysis, their usefulness d…
Large Language Models (LLMs) are increasingly adopted to optimize source code, offering the promise of faster, more efficient programs without manual tuning. This capability is particularly appealing in the context of sustainable computing, where enhanced performance is often ass…
Although the study of software transparency has deep roots in software engineering, a shared definition and practical application in real-world development contexts remain elusive. Through an in-depth analysis of the academic and industrial landscape, this article provides an ove…
Large Language Models (LLMs) have revolutionized the way natural language tasks are handled, with big potential applications in the context of education. LLMs can save educators time and effort, for instance, in content creation and exam generation. Although promising, LLMs’ inte…
Fuzz testing is a widely used method for finding security issues in software. However, certain code paths can only be explored under specific program states. Flag variables, which represent internal states, are crucial in influencing program behavior through flag-guarded branches…
Continuous Integration (CI) is a widely adopted practice in software development to automatically verify code changes across diverse environments. However, executing the full test suite on every pull request update can lead to redundant runs, slower feedback loops, and inefficien…
The security of software builds has attracted increased attention in recent years in response to incidents like solarwinds and xz. Now, several companies including Oracle and Google rebuild open source projects in a secure environment and publish the resulting binaries through de…