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- research-articleOctober 2024
Exploring the Use of Abusive Generative AI Models on Civitai
MM '24: Proceedings of the 32nd ACM International Conference on MultimediaPages 6949–6958https://doi.org/10.1145/3664647.3681052The rise of generative AI is transforming the landscape of digital imagery, and exerting a significant influence on online creative communities. This has led to the emergence of AI-Generated Content (AIGC) social platforms, such as Civitai. These ...
- research-articleOctober 2024
Understanding the Impact of AI-Generated Content on Social Media: The Pixiv Case
MM '24: Proceedings of the 32nd ACM International Conference on MultimediaPages 6813–6822https://doi.org/10.1145/3664647.3680631In the last two years, Artificial Intelligence Generated Content (AIGC) has received significant attention, leading to an anecdotal rise in the amount of AIGC being shared via social media platforms. The impact of AIGC and its implications are of key ...
- research-articleOctober 2024
An Empirical Study on Current Practices and Challenges of Core AR/VR Developers
ASEW '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering WorkshopsPages 233–238https://doi.org/10.1145/3691621.3694956Augmented reality (AR) and virtual reality (VR) applications are increasingly integral to modern society. Core AR/VR developers, pivotal in crafting these advanced technologies, face significant challenges throughout the software development lifecycle. ...
- short-paperOctober 2024
A Preliminary Study of Multilingual Code Language Models for Code Generation Task Using Translated Benchmarks
ASEW '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering WorkshopsPages 94–99https://doi.org/10.1145/3691621.3694939Evaluating the performance of Code Language Models (CLMs) for software engineering tasks, especially in multilingual and low-resource programming language settings, poses significant challenges. These challenges are primarily due to the lack of high-...
- research-articleOctober 2024
On the Evaluation of Large Language Models in Unit Test Generation
- Lin Yang,
- Chen Yang,
- Shutao Gao,
- Weijing Wang,
- Bo Wang,
- Qihao Zhu,
- Xiao Chu,
- Jianyi Zhou,
- Guangtai Liang,
- Qianxiang Wang,
- Junjie Chen
ASE '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software EngineeringPages 1607–1619https://doi.org/10.1145/3691620.3695529Unit testing is an essential activity in software development for verifying the correctness of software components. However, manually writing unit tests is challenging and time-consuming. The emergence of Large Language Models (LLMs) offers a new ...
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- research-articleOctober 2024
What Makes a High-Quality Training Dataset for Large Language Models: A Practitioners' Perspective
ASE '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software EngineeringPages 656–668https://doi.org/10.1145/3691620.3695061Large Language Models (LLMs) have demonstrated remarkable performance in various application domains, largely due to their self-supervised pre-training on extensive high-quality text datasets. However, despite the importance of constructing such datasets,...
- research-articleOctober 2024
An Empirical Study on Learning-based Techniques for Explicit and Implicit Commit Messages Generation
ASE '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software EngineeringPages 544–556https://doi.org/10.1145/3691620.3695025High-quality and appropriate commit messages help developers to quickly understand and track code evolution, which is crucial for the collaborative development and maintenance of software. To relieve developers of the burden of writing commit messages, ...
- research-articleOctober 2024
A Systematic Evaluation of Large Code Models in API Suggestion: When, Which, and How
ASE '24: Proceedings of the 39th IEEE/ACM International Conference on Automated Software EngineeringPages 281–293https://doi.org/10.1145/3691620.3695004API suggestion is a critical task in modern software development, assisting programmers by predicting and recommending third-party APIs based on the current context. Recent advancements in large code models (LCMs) have shown promise in the API suggestion ...
- research-articleOctober 2024
An Empirical Study of API Misuses of Data-Centric Libraries
ESEM '24: Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and MeasurementPages 245–256https://doi.org/10.1145/3674805.3686685Developers rely on third-party library Application Programming Interfaces (APIs) when developing software. However, libraries typically come with assumptions and API usage constraints, whose violation results in API misuse. API misuses may result in ...
- short-paperOctober 2024
Ask or Recommend: An Empirical Study on Conversational Product Search
CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge ManagementPages 3927–3931https://doi.org/10.1145/3627673.3679875Conversational Product Search (CPS) provides an engaging way for users to find products through effective natural language conversations. However, understanding the effect of conversational characteristics on user search performance and when to ask ...
- research-articleSeptember 2024
An Empirical Study on the Characteristics of Database Access Bugs in Java Applications
ACM Transactions on Software Engineering and Methodology (TOSEM), Volume 33, Issue 7Article No.: 181, Pages 1–25https://doi.org/10.1145/3672449Database-backed applications rely on the database access code to interact with the underlying database management systems (DBMSs). Although many prior studies aim at database access issues like SQL anti-patterns or SQL code smells, there is a lack of ...
Give me some REST: A Controlled Experiment to Study Effects and Perception of Model-Driven Engineering with a Domain-Specific Language
MODELS '24: Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and SystemsPages 214–225https://doi.org/10.1145/3640310.3674080Domain-Specific Languages (DSLs) are an efficient means to counter accidental complexity and are therefore a key technology for Model-Driven Engineering (MDE). Despite DSLs' potential, there is a lack of empirical research regarding the practical effects ...
- extended-abstractSeptember 2024
Vision Beyond Boundaries: An Initial Design Space of Domain-specific Large Vision Models in Human-robot Interaction
MobileHCI '24 Adjunct: Adjunct Proceedings of the 26th International Conference on Mobile Human-Computer InteractionArticle No.: 9, Pages 1–8https://doi.org/10.1145/3640471.3680244The emergence of large vision models (LVMs) is following in the footsteps of the recent prosperity of Large Language Models (LLMs) in following years. However, there’s a noticeable gap in structured research applying LVMs to human-robot interaction (HRI)...
- research-articleSeptember 2024
Characterizing and Detecting Program Representation Faults of Static Analysis Frameworks
ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and AnalysisPages 1772–1784https://doi.org/10.1145/3650212.3680398Static 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, ...
An Empirical Study on Kubernetes Operator Bugs
ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and AnalysisPages 1746–1758https://doi.org/10.1145/3650212.3680396Kubernetes is the leading cluster management platform, and within Kubernetes, an operator is an application-specific program that leverages the Kubernetes API to automate operation tasks for managing an application deployed on a Kubernetes cluster. Users ...
A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
- Zhihan Jiang,
- Jinyang Liu,
- Junjie Huang,
- Yichen Li,
- Yintong Huo,
- Jiazhen Gu,
- Zhuangbin Chen,
- Jieming Zhu,
- Michael R. Lyu
ISSTA 2024: Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and AnalysisPages 223–234https://doi.org/10.1145/3650212.3652123Log data have facilitated various tasks of software development and maintenance, such as testing, debugging and diagnosing. Due to the unstructured nature of logs, log parsing is typically required to transform log messages into structured data for ...
- research-articleAugust 2024JUST ACCEPTED
Empirical Study of Impact of Solidity Compiler Updates on Vulnerabilities in Ethereum Smart Contracts
Distributed Ledger Technologies: Research and Practice (DLT), Just Accepted https://doi.org/10.1145/3688812Vulnerabilities in Ethereum smart contracts often cause significant financial damage. Whereas the Solidity compiler has been updated to mitigate vulnerabilities, the effectiveness of these updates remains undisclosed to the best of our knowledge. In this ...
- research-articleAugust 2024JUST ACCEPTED
Benchmarking and Categorizing the Performance of Neural Program Repair Systems for Java
ACM Transactions on Software Engineering and Methodology (TOSEM), Just Accepted https://doi.org/10.1145/3688834Recent years have seen a rise in neural program repair systems in the software engineering community, which adopt advanced deep learning techniques to automatically fix bugs. Having a comprehensive understanding of existing systems can facilitate new ...
State Reconciliation Defects in Infrastructure as Code
Proceedings of the ACM on Software Engineering (PACMSE), Volume 1, Issue FSEArticle No.: 83, Pages 1865–1888https://doi.org/10.1145/3660790In infrastructure as code (IaC), state reconciliation is the process of querying and comparing the infrastructure state prior to changing the infrastructure. As state reconciliation is pivotal to manage IaC-based computing infrastructure at scale, ...
- research-articleJuly 2024
Understanding and Detecting Annotation-Induced Faults of Static Analyzers
Proceedings of the ACM on Software Engineering (PACMSE), Volume 1, Issue FSEArticle No.: 33, Pages 722–744https://doi.org/10.1145/3643759Static analyzers can reason about the properties and behaviors of programs and detect various issues without executing them. Hence, they should extract the necessary information to understand the analyzed program well. Annotation has been a widely used ...