2,847 papers · page 7 of 143
Test cases are essential for software development and maintenance. In practice, developers derive multiple test cases from an implicit pattern based on their understanding of requirements and inference of diverse test scenarios, each validating a specific behavior of the focal me…
Large language models (LLMs) have achieved remarkable performance in software engineering (SE), and fine-tuning LLM for specific SE tasks has gradually become a new paradigm. However, storing fine-tuned checkpoints for multiple tasks incurs heavy storage and deployment complexity…
As Augmented Reality (AR) applications grow in popularity, understanding and addressing AR software bugs becomes crucial. AR applications, due to their interaction with the physical world, present unique challenges that differ from traditional software. In this study, we try to u…
Reentrancy vulnerabilities are a critical security risk in smart contracts, posing a significant threat to the entire blockchain ecosystem. These vulnerabilities arise when a malicious attacker exploits the design of a smart contract to re-enter a function within the execution of…
Software deployment is a critical software engineering practice, particularly for high performance computing (HPC) software.The deployment determines the software execution performance because the deployment maps a number of software components to multiple CPUs in a server. Inapp…
Machine learning (ML)–based static malware detectors are widely deployed for Portable Executable (PE) files due to their scalability and efficiency, yet they remain vulnerable to carefully crafted adversarial perturbations. Existing black-box evasion methods either rely on transf…
With the growing synergy between deep learning and quantum computing, Quantum Neural Networks (QNNs) have emerged as a promising paradigm by leveraging quantum parallelism and entanglement. However, testing QNNs remains underexplored due to their complex quantum dynamics and limi…
Large language models (LLMs) have been adopted for text-to-SQL tasks, utilizing their in-context learning (ICL) capability to translate natural language questions into SQL queries. However, such a technique faces correctness problems. In this paper, we conduct the first comprehen…
With Python’s rising popularity, ensuring the correctness of its ever-growing ecosystem of software libraries is more critical than ever. Recently, fuzzing has become a de facto technique for vetting software libraries, enabled via the use of harnesses: small wrapper programs tha…
The demand for better prediction accuracy and higher execution performance in neural networks continues to grow. The emergence and success of Large Language Models (LLMs) have produced many cloud-based tools for software engineering tasks such as code suggestion. Although effecti…
Block-based programming environments such as Scratch are increasingly popular in programming education, in particular for young learners. While the use of blocks helps prevent syntax errors, semantic bugs remain common and difficult to debug. Existing tools for Scratch debugging …
Security vulnerabilities in software packages are a significant concern for developers and users alike. Patching these vulnerabilities in a timely manner is crucial to restoring the integrity and security of software systems. However, previous work has shown that vulnerability re…
REST APIs are widely used for accessing web services. To support their use and testing, developers often write API specifications in open formats like OpenAPI. However, writing these specifications manually is tedious and error-prone, leading to incomplete or outdated specificati…
A code revision is a proposed modification to a specific code snippet under review, created in response to a reviewer’s comment. Modern code review platforms, such as GitHub, allow participants to provide these revisions inline as concrete change suggestions that the others can a…
Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards (e.g., to mitigate toxic or biased responses in text generation, or to enforce coding best practices in code generation). While LLM alignment…
When a program fails, statistical fault localization (SFL) provides important debugging hints by identifying the locations whose execution most correlates with failures. However, such correlations can be weakened if a test contains both _passing_ and _failing_ assertions, creatin…
We present SmarTrim, a new symbolic execution technique for detecting vulnerabilities in smart contracts. Smart contracts require rigorous safety validation since flaws in them can cause significant financial loss. Numerous symbolic execution techniques, which generate vulnerable…
Prompt-induced cognitive biases are changes in a general-purpose AI (GPAI) system's decisions caused solely by biased wording in the input (e.g., framing, anchors), not task logic. In software engineering (SE) decision support (where problem statements and requirements are natura…
With the rapid development of decentralized applications, many malicious actors exploit smart contract vulnerabilities for launching attacks. Moreover, as smart contracts utilize more state variables to support complex functionalities, some vulnerabilities require specific states…
Python's dynamic typing mechanism, while promoting flexibility, is a significant source of runtime type errors that plague large-scale software, which inspires the automatic type inference techniques. Existing type inference tools have achieved advances in type inference within i…