paper_name stringlengths 4 399 | paper_url stringlengths 21 343 | paper_authors listlengths 0 125 | paper_abstract stringlengths 0 43.4k | paper_code stringlengths 1 149 | conf stringlengths 6 18 |
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RepairAgent: An Autonomous, LLM-Based Agent for Program Repair | https://doi.org/10.1109/ICSE55347.2025.00157 | [
"Islem Bouzenia",
"Premkumar T. Devanbu",
"Michael Pradel"
] | Automated program repair has emerged as a powerful technique to mitigate the impact of software bugs on system reliability and user experience. This paper introduces Repair Agent, the first work to address the program repair challenge through an autonomous agent based on a large language model (LLM). Unlike existing de... | https://github.com/sola-st/RepairAgent | ICSE2025 |
A Tale of Two DL Cities: When Library Tests Meet Compiler | https://doi.org/10.1109/ICSE55347.2025.00025 | [
"Qingchao Shen",
"Yongqiang Tian",
"Haoyang Ma",
"Junjie Chen",
"Lili Huang",
"Ruifeng Fu",
"Shing-Chi Cheung",
"Zan Wang"
] | Deep Learning (DL) compilers typically load a DL model and optimize it with intermediate representation. Existing DL compiler testing techniques mainly focus on model optimization stages, but rarely explore bug detection at the model loading stage. Effectively testing the model loading stage requires covering diverse u... | https://github.com/shenqingchao/opera | ICSE2025 |
Iterative Generation of Adversarial Example for Deep Code Models | https://doi.org/10.1109/ICSE55347.2025.00086 | [
"Li Huang",
"Weifeng Sun",
"Meng Yan"
] | Deep code models are vulnerable to adversarial attacks, making it possible for semantically identical inputs to trigger different responses. Current black-box attack methods typically prioritize the impact of identifiers on the model based on custom importance scores or program context and incrementally replace identif... | # | ICSE2025 |
On the Mistaken Assumption of Interchangeable Deep Reinforcement Learning Implementations | https://doi.org/10.1109/ICSE55347.2025.00222 | [
"Rajdeep Singh Hundal",
"Yan Xiao",
"Xiaochun Cao",
"Jin Song Dong",
"Manuel Rigger"
] | Deep Reinforcement Learning (DRL) is a paradigm of artificial intelligence where an agent uses a neural network to learn which actions to take in a given environment. DRL has recently gained traction from being able to solve complex environments like driving simulators, 3D robotic control, and multiplayer-online-battle... | # | ICSE2025 |
$\mu \text{PRL}$: A Mutation Testing Pipeline for Deep Reinforcement Learning Based on Real Faults | https://doi.org/10.1109/ICSE55347.2025.00036 | [
"Deepak-George Thomas",
"Matteo Biagiola",
"Nargiz Humbatova",
"Mohammad Wardat",
"Gunel Jahangirova",
"Hridesh Rajan",
"Paolo Tonella"
] | Reinforcement Learning (RL) is increasingly adopted to train agents that can deal with complex sequential tasks, such as driving an autonomous vehicle or controlling a humanoid robot. Correspondingly, novel approaches are needed to ensure that RL agents have been tested adequately before going to production. Among them... | # | ICSE2025 |
Testing and Understanding Deviation Behaviors in FHE-Hardened Machine Learning Models | https://doi.org/10.1109/ICSE55347.2025.00107 | [
"Yiteng Peng",
"Daoyuan Wu",
"Zhibo Liu",
"Dongwei Xiao",
"Zhenlan Ji",
"Juergen Rahmel",
"Shuai Wang"
] | Fully homomorphic encryption (FHE) is a promising cryptographic primitive that enables secure computation over encrypted data. A primary use of FHE is to support privacypreserving machine learning (ML) on public cloud infrastructures. Despite the rapid development of FHE-based ML (or HE-ML), the community lacks a syste... | # | ICSE2025 |
TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance | https://doi.org/10.1109/ICSE55347.2025.00128 | [
"Waris Gill",
"Ali Anwar",
"Muhammad Ali Gulzar"
] | In Federated Learning, clients train models on local data and send updates to a central server, which aggregates them into a global model using a fusion algorithm. This collaborative yet privacy-preserving training comes at a cost. FL developers face significant challenges in attributing global model predictions to spe... | https://github.com/seed-vt/tracefl | ICSE2025 |
A First Look at Conventional Commits Classification | https://doi.org/10.1109/ICSE55347.2025.00011 | [
"Qunhong Zeng",
"Yuxia Zhang",
"Zhiqing Qiu",
"Hui Liu"
] | Modern distributed software development relies on commits to control system versions. Commit classification plays a vital role in both industry and academia. The widely-used commit classification framework was proposed in 1976 by Swanson and includes three base classes: perfective, corrective, and adaptive. With the in... | # | ICSE2025 |
Chatgpt Inaccuracy Mitigation During Technical Report Understanding: Are we There Yet? | https://doi.org/10.1109/ICSE55347.2025.00145 | [
"Salma Begum Tamanna",
"Gias Uddin",
"Song Wang",
"Lan Xia",
"Longyu Zhang"
] | Hallucinations, the tendency to produce irrelevant/incorrect responses, are prevalent concerns in generative AIbased tools like ChatGPT. Although hallucinations in ChatGPT are studied for textual responses, it is unknown how ChatGPT hallucinates for technical texts that contain both textual and technical terms. We surv... | # | ICSE2025 |
SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing | https://doi.org/10.1109/ICSE55347.2025.00154 | [
"Wenchao Gu",
"Ensheng Shi",
"Yanlin Wang",
"Lun Du",
"Shi Han",
"Hongyu Zhang",
"Dongmei Zhang",
"Michael R. Lyu"
] | Code retrieval, which retrieves code snippets based on users' natural language descriptions, is widely used by devel-opers and plays a pivotal role in real-world software development. The advent of deep learning has shifted the retrieval paradigm from lexical-based matching towards leveraging deep learning models to en... | # | ICSE2025 |
Decoding the Issue Resolution Process in Practice via Issue Report Analysis: a Case Study of Firefox | https://doi.org/10.1109/ICSE55347.2025.00241 | [
"Antu Saha",
"Oscar Chaparro"
] | Effectively managing and resolving software issues is critical for maintaining and evolving software systems. Development teams often rely on issue trackers and issue reports to track and manage the work needed during issue resolution, ranging from issue reproduction and analysis to solution design, implementation, ver... | # | ICSE2025 |
Preserving Privacy in Software Composition Analysis: A Study of Technical Solutions and Enhancements | https://doi.org/10.1109/ICSE55347.2025.00055 | [
"Huaijin Wang",
"Zhibo Liu",
"Yanbo Dai",
"Shuai Wang",
"Qiyi Tang",
"Sen Nie",
"Shi Wu"
] | Software composition analysis (SCA) denotes the process of identifying open-source software components in an input software application. SCA has been extensively developed and adopted by academia and industry. However, we notice that the modern SCA techniques in industry scenarios still need to be improved due to priva... | # | ICSE2025 |
UML is Back. Or is it? Investigating the Past, Present, and Future of UML in Open Source Software | https://doi.org/10.1109/ICSE55347.2025.00155 | [
"Joseph Romeo",
"Marco Raglianti",
"Csaba Nagy",
"Michele Lanza"
] | Since its inception, UML, the Unified Modeling Language, has been touted as the way to go when it comes to designing and documenting software systems. While being an integral part of many university software engineering programs, UML has found little consideration among developers, especially in open source software. R... | # | ICSE2025 |
Understanding the Response to Open-Source Dependency Abandonment in the npm Ecosystem | https://doi.org/10.1109/ICSE55347.2025.00004 | [
"Courtney Miller",
"Mahmoud Jahanshahi",
"Audris Mockus",
"Bogdan Vasilescu",
"Christian Kästner"
] | Many developers relying on open-source digital infrastructure expect continuous maintenance, but even the most critical packages can become unmaintained. Despite this, there is little understanding of the prevalence of abandonment of widely-used packages, of subsequent exposure, and of reactions to abandonment in pract... | # | ICSE2025 |
Understanding Compiler Bugs in Real Development | https://doi.org/10.1109/ICSE55347.2025.00068 | [
"Hao Zhong"
] | Compilers are critical in development, but compiler bugs can cause hidden and serious bugs in their compiled code. To deepen the understanding of compiler bugs, in the prior empirical studies, researchers read the bug reports and patches of compilers, and analyze their causes, locations, and patterns. Although they der... | # | ICSE2025 |
Studying Programmers Without Programming: Investigating Expertise Using Resting State fMRI | https://doi.org/10.1109/ICSE55347.2025.00164 | [
"Zachary Karas",
"Benjamin Gold",
"Violet Zhou",
"Noah Reardon",
"Thad Polk",
"Catie Chang",
"Yu Huang"
] | Expert programmers are more effective at coding activities, but the reasons for this remain elusive. Accordingly, recent research has used neuroimaging such as fMRI to analyze how expert programmers might think as they perform coding activities. Those experiments have all involved specific program-ming tasks (i.e., com... | # | ICSE2025 |
Accessibility Issues in Ad-Driven Web Applications | https://doi.org/10.1109/ICSE55347.2025.00171 | [
"Abdul Haddi Amjad",
"Muhammad Danish",
"Bless Jah",
"Muhammad Ali Gulzar"
] | Website accessibility is essential for inclusiveness and regulatory compliance. Although third-party advertisements (ads) are a vital revenue source for free web services, they introduce significant accessibility challenges. Leasing a website's space to ad-serving technologies, like DoubleClick, results in developers l... | # | ICSE2025 |
Unveiling the Energy Vampires: A Methodology for Debugging Software Energy Consumption | https://doi.org/10.1109/ICSE55347.2025.00118 | [
"Enrique Barba Roque",
"Luis Cruz",
"Thomas Durieux"
] | Energy consumption in software systems is becoming increasingly important, especially in large-scale deployments. However, debugging energy-related issues remains challenging due to the lack of specialized tools. This paper presents an energy debugging methodology for identifying and isolating energy consumption hotspo... | https://github.com/enriquebarba97/EnergyDebug | ICSE2025 |
Automated, Unsupervised, and Auto-Parameterized Inference of Data Patterns and Anomaly Detection | https://doi.org/10.1109/ICSE55347.2025.00078 | [
"Qiaolin Qin",
"Heng Li",
"Ettore Merlo",
"Maxime Lamothe"
] | With the advent of data-centric and machine learning (ML) systems, data quality is playing an increasingly critical role for ensuring the overall quality of software systems. Data preparation, an essential step towards high data quality, is known to be a highly effort-intensive process. Although prior studies have deal... | https://github.com/mooselab/discover-data-quality-with-riolu | ICSE2025 |
On Prescription or Off Prescription? An Empirical Study of Community-Prescribed Security Configurations for Kubernetes | https://doi.org/10.1109/ICSE55347.2025.00170 | [
"Shazibul Islam Shamim",
"Hanyang Hu",
"Akond Rahman"
] | Despite being beneficial for rapid delivery of software, Kubernetes deployments can be susceptible to security attacks, which can cause serious consequences. A systematic characterization of how community-prescribed security configurations, i.e., security configurations that are recommended by security experts, can aid... | # | ICSE2025 |
Similar but Patched Code Considered Harmful: The Impact of Similar but Patched Code on Recurring Vulnerability Detection and How to Remove Them | https://doi.org/10.1109/ICSE55347.2025.00110 | [
"Zixuan Tan",
"Jiayuan Zhou",
"Xing Hu",
"Shengyi Pan",
"Kui Liu",
"Xin Xia"
] | Identifying recurring vulnerabilities is crucial for ensuring software security. Clone-based techniques, while widely used, often generate many false alarms due to the existence of similar but patched (SBP) code, which is similar to vulnerable code but is not vulnerable due to having been patched. Although the SBP code... | # | ICSE2025 |
Tiver: Identifying Adaptive Versions of C/C++ Third-Party Open-Source Components Using a Code Clustering Technique | https://doi.org/10.1109/ICSE55347.2025.00188 | [
"Youngjae Choi",
"Seunghoon Woo"
] | Reusing open-source software (OSS) provides significant benefits but also poses risks from propagated vulnerabilities. While tracking OSS component versions helps mitigate threats, existing approaches typically map a single version to the reused codebase. This coarse-grained approach overlooks the coexistence of multip... | # | ICSE2025 |
An Exploratory Study on the Engineering of Security Features | https://doi.org/10.1109/ICSE55347.2025.00184 | [
"Kevin Hermann",
"Sven Peldszus",
"Jan-Philipp Steghöfer",
"Thorsten Berger"
] | Software security is of utmost importance for most software systems. Developers must systematically select, plan, design, implement, and especially, maintain and evolve security features-functionalities to mitigate attacks or protect personal data such as cryptography or access control-to ensure the security of their s... | # | ICSE2025 |
DesignRepair: Dual-Stream Design Guideline-Aware Frontend Repair with Large Language Models | https://doi.org/10.1109/ICSE55347.2025.00109 | [
"Mingyue Yuan",
"Jieshan Chen",
"Zhenchang Xing",
"Aaron Quigley",
"Yuyu Luo",
"Tianqi Luo",
"Gelareh Mohammadi",
"Qinghua Lu",
"Liming Zhu"
] | The rise of Large Language Models (LLMs) has streamlined frontend interface creation through tools like Vercel's v0, yet surfaced challenges in design quality (e.g., accessibility, and usability). Current solutions, often limited by their focus, generalisability, or data dependency, fall short in addressing these compl... | https://github.com/UGAIForge/DesignRepair | ICSE2025 |
Fidelity of Cloud Emulators: The Imitation Game of Testing Cloud-Based Software | https://doi.org/10.1109/ICSE55347.2025.00077 | [
"Anna Mazhar",
"Saad Sher Alam",
"William X. Zheng",
"Yinfang Chen",
"Suman Nath",
"Tianyin Xu"
] | Modern software projects have been increasingly using cloud services as important components. The cloud-based programming practice greatly simplifies software development by harvesting cloud benefits (e.g., high availability and elasticity). However, it imposes new challenges for software testing and analysis, due to o... | # | ICSE2025 |
Formally Verified Cloud-Scale Authorization | https://doi.org/10.1109/ICSE55347.2025.00166 | [
"Aleks Chakarov",
"Jaco Geldenhuys",
"Matthew Heck",
"Michael Hicks",
"Sam Huang",
"Georges-Axel Jaloyan",
"Anjali Joshi",
"K. Rustan M. Leino",
"Mikael Mayer",
"Sean McLaughlin",
"Akhilesh Mritunjai",
"Clément Pit-Claudel",
"Sorawee Porncharoenwase",
"Florian Rabe",
"Marianna Rapoport",... | All critical systems must evolve to meet the needs of a growing and diversifying user base. But supporting that evolution is challenging at increasing scale: Maintainers must find a way to ensure that each change does only what is intended, and will not inadvertently change behavior for existing users. This paper prese... | # | ICSE2025 |
The Same Only Different: On Information Modality for Configuration Performance Analysis | https://doi.org/10.1109/ICSE55347.2025.00212 | [
"Hongyuan Liang",
"Yue Huang",
"Tao Chen"
] | Configuration in software systems helps to ensure efficient operation and meet diverse user needs. Yet, some, if not all, configuration options have profound implications for the system's performance. Configuration performance analysis, wherein the key is to understand (or infer) the configuration options' relations an... | https://github.com/ideas-labo/cp-mod | ICSE2025 |
3DGen: AI-Assisted Generation of Provably Correct Binary Format Parsers | https://doi.org/10.1109/ICSE55347.2025.00173 | [
"Sarah Fakhoury",
"Markus Kuppe",
"Shuvendu K. Lahiri",
"Tahina Ramananandro",
"Nikhil Swamy"
] | Improper parsing of attacker-controlled input is a leading source of software security vulnerabilities, especially when programmers transcribe informal format descriptions in RFCs into efficient parsing logic in low-level, memory unsafe languages. Several researchers have proposed formal specification languages for dat... | # | ICSE2025 |
Aligning the Objective of LLM-Based Program Repair | https://doi.org/10.1109/ICSE55347.2025.00169 | [
"Junjielong Xu",
"Ying Fu",
"Shin Hwei Tan",
"Pinjia He"
] | Large language models (LLMs) have achieved decent results on automated program repair (APR). However, the next token prediction training objective of decoder-only LLMs (e.g., GPT-4) is misaligned with the masked span prediction objective of current infilling-style methods, which impedes LLMs from fully leveraging pre-t... | https://github.com/cuhk-shenzhen-se/d4c | ICSE2025 |
Revisiting Unnaturalness for Automated Program Repair in the Era of Large Language Models | https://doi.org/10.1109/ICSE55347.2025.00089 | [
"Aidan Z. H. Yang",
"Sophia Kolak",
"Vincent J. Hellendoorn",
"Ruben Martins",
"Claire Le Goues"
] | The problem of software quality has motivated the development of a variety of techniques for Automatic Program Repair (APR). Meanwhile, recent advances in AI and Large Language Models (LLMs) have produced orders of magnitude performance improvements over previous code generation techniques, affording promising opportun... | # | ICSE2025 |
The Fact Selection Problem in LLM-Based Program Repair | https://doi.org/10.1109/ICSE55347.2025.00162 | [
"Nikhil Parasaram",
"Huijie Yan",
"Boyu Yang",
"Zineb Flahy",
"Abriele Qudsi",
"Damian Ziaber",
"Earl T. Barr",
"Sergey Mechtaev"
] | Recent research has shown that incorporating bug-related facts, such as stack traces and GitHub issues, into prompts enhances the bug-fixing capabilities of large language models (LLMs). Considering the ever-increasing context window of these models, a critical question arises: what and how many facts should be include... | https://github.com/pyrepair/maniple | ICSE2025 |
Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models | https://doi.org/10.1109/ICSE55347.2025.00180 | [
"Zhijie Wang",
"Zijie Zhou",
"Da Song",
"Yuheng Huang",
"Shengmai Chen",
"Lei Ma",
"Tianyi Zhang"
] | Large Language Models (LLMs) have demonstrated unprecedented capabilities in code generation. However, there remains a limited understanding of code generation errors that LLMs can produce. To bridge the gap, we conducted an in-depth analysis of code generation errors across six representative LLMs on the HumanEval dat... | # | ICSE2025 |
Famos: Fault Diagnosis for Microservice Systems Through Effective Multi-Modal Data Fusion | https://doi.org/10.1109/ICSE55347.2025.00073 | [
"Chiming Duan",
"Yong Yang",
"Tong Jia",
"Guiyang Liu",
"Jinbu Liu",
"Huxing Zhang",
"Qi Zhou",
"Ying Li",
"Gang Huang"
] | Accurately diagnosing the fault that causes the failure is crucial for maintaining the reliability of a microservice system after a failure occurs. Mainstream fault diagnosis approaches are data-driven and mainly rely on three modalities of runtime data: traces, logs, and metrics. Diagnosing faults with multiple modali... | # | ICSE2025 |
Leveraging Large Language Models to Detect NPM Malicious Packages | https://doi.org/10.1109/ICSE55347.2025.00146 | [
"Nusrat Zahan",
"Philipp Burckhardt",
"Mikola Lysenko",
"Feross Aboukhadijeh",
"Laurie A. Williams"
] | Existing malicious code detection techniques demand the integration of multiple tools to detect different malware patterns, often suffering from high misclassification rates. Therefore, malicious code detection techniques could be enhanced by adopting advanced, more automated approaches to achieve high accuracy and a l... | # | ICSE2025 |
MAGIKA: AI-Powered Content-Type Detection | https://doi.org/10.1109/ICSE55347.2025.00158 | [
"Yanick Fratantonio",
"Luca Invernizzi",
"Loua Farah",
"Kurt Thomas",
"Marina Zhang",
"Ange Albertini",
"Francois Galilee",
"Giancarlo Metitieri",
"Julien Cretin",
"Alex Petit-Bianco",
"David Tao",
"Elie Bursztein"
] | The task of content-type detection—which entails identifying the data encoded in an arbitrary byte sequence—is critical for operating systems, development, reverse engineering environments, and a variety of security applications. In this paper, we introduce Magika, a novel AI-powered content-type detection tool. Under ... | https://github.com/google/magika | ICSE2025 |
Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based on Code Naturalness | https://doi.org/10.1109/ICSE55347.2025.00247 | [
"Weisong Sun",
"Yuchen Chen",
"Mengzhe Yuan",
"Chunrong Fang",
"Zhenpeng Chen",
"Chong Wang",
"Yang Liu",
"Baowen Xu",
"Zhenyu Chen"
] | Neural code models (NCMs) have demonstrated extraordinary capabilities in code intelligence tasks. Meanwhile, the security of NCMs and NCMs-based systems has garnered increasing attention. In particular, NCMs are often trained on large-scale data from potentially untrustworthy sources, providing attackers with the oppo... | # | ICSE2025 |
Treefix: Enabling Execution with a Tree of Prefixes | https://doi.org/10.1109/ICSE55347.2025.00215 | [
"Beatriz Souza",
"Michael Pradel"
] | The ability to execute code is a prerequisite for various dynamic program analyses. Learning-guided execution has been proposed as an approach to enable the execution of arbitrary code snippets by letting a neural model predict likely values for any missing variables. Although state-of-the-art learning-guided execution... | # | ICSE2025 |
Automated Accessibility Analysis of Dynamic Content Changes on Mobile Apps | https://doi.org/10.1109/ICSE55347.2025.00039 | [
"Forough Mehralian",
"Ziyao He",
"Sam Malek"
] | With mobile apps playing an increasingly vital role in our daily lives, the importance of ensuring their accessibility for users with disabilities is also growing. Despite this, app developers often overlook the accessibility challenges encountered by users of assistive technologies, such as screen readers. Screen read... | # | ICSE2025 |
Janus: Detecting Rendering Bugs in Web Browsers via Visual Delta Consistency | https://doi.org/10.1109/ICSE55347.2025.00013 | [
"Chijin Zhou",
"Quan Zhang",
"Bingzhou Qian",
"Yu Jiang"
] | Rendering lies at the heart of our modern web experience. However, the correctness of browser rendering is not always guaranteed, often leading to rendering bugs. Traditional differential testing, while successful in various domains, falls short when applied to rendering bug detection because an HTML file is likely yie... | # | ICSE2025 |
Chatgpt-Based Test Generation for Refactoring Engines Enhanced by Feature Analysis on Examples | https://doi.org/10.1109/ICSE55347.2025.00210 | [
"Chunhao Dong",
"Yanjie Jiang",
"Yuxia Zhang",
"Yang Zhang",
"Hui Liu"
] | Software refactoring is widely employed to improve software quality. However, conducting refactorings manually is tedious, time-consuming, and error-prone. Consequently, automated and semi-automated tool support is highly desirable for software refactoring in the industry, and most of the main-stream IDEs provide power... | # | ICSE2025 |
Navigating the Testing of Evolving Deep Learning Systems: An Exploratory Interview Study | https://doi.org/10.1109/ICSE55347.2025.00106 | [
"Hanmo You",
"Zan Wang",
"Bin Lin",
"Junjie Chen"
] | Deep Learning (DL) systems have been widely adopted across various industrial domains such as autonomous driving and intelligent healthcare. As with traditional software, DL systems also need to constantly evolve to meet ever-changing user requirements. However, ensuring the quality of these continuously evolving syste... | # | ICSE2025 |
EP-Detector: Automatic Detection of Error-Prone Operation Anomalies in Android Applications | https://doi.org/10.1109/ICSE55347.2025.00029 | [
"Chenkai Guo",
"Qianlu Wang",
"Naipeng Dong",
"Lingling Fan",
"Tianhong Wang",
"Weijie Zhang",
"Enbao Chen",
"Zheli Liu",
"Lu Yu"
] | Android applications are pervasively adopted and heavily relied on in our daily life, leading to the growing demand for enhanced user experiences, such as ease for operation and robustness. Nevertheless, developers continue to prioritize traditional functionality and performance, overlooking the pivotal role of user ex... | https://github.com/WordDealer/EP-Detector | ICSE2025 |
Mobile Application Coverage: The 30% Curse and Ways Forward | https://doi.org/10.1109/ICSE55347.2025.00142 | [
"Faridah Akinotcho",
"Lili Wei",
"Julia Rubin"
] | Testing, security analysis, and other dynamic quality assurance approaches rely on mechanisms that invoke the software under test, aiming to achieve high code coverage. A large number of invocation mechanisms proposed in the literature, in particular for Android mobile applications, employ GUI-driven application explor... | # | ICSE2025 |
The Design Smells Breaking the Boundary between Android Variants and AOSP | https://doi.org/10.1109/ICSE55347.2025.00062 | [
"Wuxia Jin",
"Jiaowei Shang",
"Jianguo Zheng",
"Mengjie Sun",
"Zhenyu Huang",
"Ming Fan",
"Ting Liu"
] | Phone vendors customize their Android variants to enhance system functionalities based on the Android Open Source Project (AOSP). While independent development, Android variants have to periodically evolve with the upstream AOSP and merge code changes from AOSP. Vendors have invested great effort to maintain their vari... | # | ICSE2025 |
Scenario-Driven and Context-Aware Automated Accessibility Testing for Android Apps | https://doi.org/10.1109/ICSE55347.2025.00093 | [
"Yuxin Zhang",
"Sen Chen",
"Xiaofei Xie",
"Zibo Liu",
"Lingling Fan"
] | Mobile accessibility is increasingly important nowadays as it enables people with disabilities to use mobile applications to perform daily tasks. Ensuring mobile accessibility not only benefits those with disabilities but also enhances the user experience for all users, making applications more intuitive and user-frien... | # | ICSE2025 |
TacDroid: Detection of Illicit Apps Through Hybrid Analysis of UI-Based Transition Graphs | https://doi.org/10.1109/ICSE55347.2025.00111 | [
"Yanchen Lu",
"Hongyu Lin",
"Zehua He",
"Haitao Xu",
"Zhao Li",
"Shuai Hao",
"Liu Wang",
"Haoyu Wang",
"Kui Ren"
] | Illicit apps have emerged as a thriving underground industry, driven by their substantial profitability. These apps either offer users restricted services (e.g., porn and gambling) or engage in fraudulent activities like scams. Despite the widespread presence of illicit apps, scant attention has been directed towards t... | # | ICSE2025 |
PacDroid: A Pointer-Analysis-Centric Framework for Security Vulnerabilities in Android Apps | https://doi.org/10.1109/ICSE55347.2025.00208 | [
"Menglong Chen",
"Tian Tan",
"Minxue Pan",
"Yue Li"
] | General frameworks such as FlowDroid, IccTA, P/Taint, Amandroid, and DroidSafe have significantly advanced the development of static analysis tools for Android security by providing fundamental facilities for them. However, while these frameworks have been instrumental in fostering progress, they often operate with inh... | # | ICSE2025 |
ROSA: Finding Backdoors with Fuzzing | https://doi.org/10.1109/ICSE55347.2025.00183 | [
"Dimitri Kokkonis",
"Michaël Marcozzi",
"Emilien Decoux",
"Stefano Zacchiroli"
] | A code-level backdoor is a hidden access, programmed and concealed within the code of a program. For instance, hard-coded credentials planted in the code of a file server application would enable maliciously logging into all deployed instances of this application. Confirmed software supplychain attacks have led to the ... | https://github.com/binsec/rosa | ICSE2025 |
Analyzing the Feasibility of Adopting Google's Nonce-Based CSP Solutions on Websites | https://doi.org/10.1109/ICSE55347.2025.00193 | [
"Mengxia Ren",
"Anhao Xiang",
"Chuan Yue"
] | Content Security Policy (CSP) is a leading security mechanism for mitigating content injection attacks such as CrossSite Scripting (XSS). Nevertheless, despite efforts from academia and industry, CSP policies (in short, CSPs) are not widely deployed on websites, and deployed CSPs often have security issues or errors. S... | # | ICSE2025 |
Early Detection of Performance Regressions by Bridging Local Performance Data and Architectural Models | https://doi.org/10.1109/ICSE55347.2025.00026 | [
"Lizhi Liao",
"Simon Eismann",
"Heng Li",
"Cor-Paul Bezemer",
"Diego Elias Costa",
"André van Hoorn",
"Weiyi Shang"
] | During software development, developers often make numerous modifications to the software to address existing issues or implement new features. However, certain changes may inadvertently have a detrimental impact on the overall system performance. To ensure that the performance of new software re-leases does not degrad... | # | ICSE2025 |
Practical Object-Level Sanitizer with Aggregated Memory Access and Custom Allocator | https://doi.org/10.1109/ICSE55347.2025.00213 | [
"Xiaolei Wang",
"Ruilin Li",
"Bin Zhang",
"Chao Feng",
"Chaojing Tang"
] | To mitigate potential memory safety vulnerabilities, recently there have been significant advances in sanitizers for pre-production bug detection. However, the limited inability to balance performance and detection accuracy still holds. The main reason is due to excessive reliance on shadow memory and a large number of... | # | ICSE2025 |
GVI: Guided Vulnerability Imagination for Boosting Deep Vulnerability Detectors | https://doi.org/10.1109/ICSE55347.2025.00214 | [
"Heng Yong",
"Zhong Li",
"Minxue Pan",
"Tian Zhang",
"Jianhua Zhao",
"Xuandong Li"
] | The use of deep learning to achieve automated software vulnerability detection has been a longstanding interest within the software security community. These deep vulnerability detectors are mostly trained in a supervised manner, which heavily relies on large-scale, high-quality vulnerability datasets. However, the vul... | # | ICSE2025 |
Decoding Secret Memorization in Code LLMs Through Token-Level Characterization | https://doi.org/10.1109/ICSE55347.2025.00229 | [
"Yuqing Nie",
"Chong Wang",
"Kailong Wang",
"Guoai Xu",
"Guosheng Xu",
"Haoyu Wang"
] | Code Large Language Models (LLMs) have demonstrated remarkable capabilities in generating, understanding, and manipulating programming code. However, their training process inadvertently leads to the memorization of sensitive information, posing severe privacy risks. Existing studies on memorization in LLMs primarily r... | # | ICSE2025 |
Are We Learning the Right Features? A Framework for Evaluating DL-Based Software Vulnerability Detection Solutions | https://doi.org/10.1109/ICSE55347.2025.00194 | [
"Satyaki Das",
"Syeda Tasnim Fabiha",
"Saad Shafiq",
"Nenad Medvidovic"
] | Recent research has revealed that the reported results of an emerging body of deep learning-based techniques for detecting software vulnerabilities are not reproducible, either across different datasets or on unseen samples. This paper aims to provide the foundation for properly evaluating the research in this domain. ... | # | ICSE2025 |
Boosting Static Resource Leak Detection via LLM-based Resource-Oriented Intention Inference | https://doi.org/10.1109/ICSE55347.2025.00131 | [
"Chong Wang",
"Jianan Liu",
"Xin Peng",
"Yang Liu",
"Yiling Lou"
] | Resource leaks, caused by resources not being released after acquisition, often lead to performance issues and system crashes. Existing static detection techniques rely on mechanical matching of predefined resource acquisition/release APIs and null-checking conditions to find unreleased resources, suffering from both (... | # | ICSE2025 |
Weakly-Supervised Log-Based Anomaly Detection with Inexact Labels via Multi-Instance Learning | https://doi.org/10.1109/ICSE55347.2025.00189 | [
"Minghua He",
"Tong Jia",
"Chiming Duan",
"Huaqian Cai",
"Ying Li",
"Gang Huang"
] | Log-based anomaly detection is essential for maintaining software availability. However, existing log-based anomaly detection approaches heavily rely on fine-grained exact labels of log entries which are very hard to obtain in real-world systems. This brings a key problem that anomaly detection models require supervisi... | # | ICSE2025 |
When Quantum Meets Classical: Characterizing Hybrid Quantum-Classical Issues Discussed in Developer Forums | https://doi.org/10.1109/ICSE55347.2025.00137 | [
"Jake Zappin",
"Trevor Stalnaker",
"Oscar Chaparro",
"Denys Poshyvanyk"
] | Recent advances in quantum computing have sparked excitement that this new computing paradigm could solve previously intractable problems. However, due to the faulty nature of current quantum hardware and quantum-intrinsic noise, the full potential of quantum computing is still years away. Hybrid quantum-classical comp... | # | ICSE2025 |
Improved Detection and Diagnosis of Faults in Deep Neural Networks Using Hierarchical and Explainable Classification | https://doi.org/10.1109/ICSE55347.2025.00224 | [
"Sigma Jahan",
"Mehil B. Shah",
"Parvez Mahbub",
"Mohammad Masudur Rahman"
] | Deep Neural Networks (DNN) have found numerous applications in various domains, including fraud detection, medical diagnosis, facial recognition, and autonomous driving. However, D NN - based systems often suffer from reliability issues due to their inherent complexity and the stochastic nature of their underlying mode... | # | ICSE2025 |
Lightweight Concolic Testing via Path-Condition Synthesis for Deep Learning Libraries | https://doi.org/10.1109/ICSE55347.2025.00202 | [
"Sehoon Kim",
"Yonghyeon Kim",
"Dahyeon Park",
"Yuseok Jeon",
"Jooyong Yi",
"Mijung Kim"
] | Many techniques have been recently developed for testing deep learning (DL) libraries. Although these techniques have effectively improved API and code coverage and detected unknown bugs, they rely on blackbox fuzzing for input generation. Concolic testing (also known as dynamic symbolic execution) can be more effectiv... | # | ICSE2025 |
Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning | https://doi.org/10.1109/ICSE55347.2025.00220 | [
"Ruchira Manke",
"Mohammad Wardat",
"Foutse Khomh",
"Hridesh Rajan"
] | While deep learning (DL) has permeated, and become an integral component of many critical software systems, today software engineering research hasn't explored how to separately test data and models that are integral for DL approaches to work effectively. The main challenge in independently testing these components ari... | # | ICSE2025 |
Rug: Turbo Llm for Rust Unit Test Generation | https://doi.org/10.1109/ICSE55347.2025.00097 | [
"Xiang Cheng",
"Fan Sang",
"Yizhuo Zhai",
"Xiaokuan Zhang",
"Taesoo Kim"
] | Unit testing improves software quality by evaluating isolated sections of the program. This approach alleviates the need for comprehensive program-wide testing and confines the potential error scope within the software. However, unit test development is time-consuming, requiring developers to create appropriate test co... | # | ICSE2025 |
An Empirical Study of Proxy Contracts at the Ethereum Ecosystem Scale | https://doi.org/10.1109/ICSE55347.2025.00083 | [
"Mengya Zhang",
"Preksha Shukla",
"Wuqi Zhang",
"Zhuo Zhang",
"Pranav Agrawal",
"Zhiqiang Lin",
"Xiangyu Zhang",
"Xiaokuan Zhang"
] | The proxy design pattern separates data and code in smart contracts into proxy and logic contracts. Data resides in proxy contracts, while code is sourced from logic contracts. This pattern allows for flexible smart contract development, enabling upgradeability, extensibility, and code reuse. Despite its popularity and... | # | ICSE2025 |
Demystifying and Detecting Cryptographic Defects in Ethereum Smart Contracts | https://doi.org/10.1109/ICSE55347.2025.00010 | [
"Jiashuo Zhang",
"Yiming Shen",
"Jiachi Chen",
"Jianzhong Su",
"Yanlin Wang",
"Ting Chen",
"Jianbo Gao",
"Zhong Chen"
] | Ethereum has officially provided a set of system-level cryptographic APIs to enhance smart contracts with cryptographic capabilities. These APIs have been utilized in over 10% of Ethereum transactions, motivating developers to implement various on-chain cryptographic tasks, such as digital signatures. However, since de... | https://github.com/jiashuo-zhang/crysol | ICSE2025 |
Chord: Towards a Unified Detection of Blockchain Transaction Parallelism Bugs | https://doi.org/10.1109/ICSE55347.2025.00205 | [
"Yuanhang Zhou",
"Zhen Yan",
"Yuanliang Chen",
"Fuchen Ma",
"Ting Chen",
"Yu Jiang"
] | Blockchain systems have implemented various transaction parallelism mechanisms to improve the system throughput and reduce the latency. However, they inevitably introduce bugs. Such bugs can result in severe consequences such as asset loss, double spending, consensus failure, and DDoS. Unfortunately, they have been lit... | # | ICSE2025 |
Definition and Detection of Centralization Defects in Smart Contracts | https://doi.org/10.1109/ICSE55347.2025.00058 | [
"Zewei Lin",
"Jiachi Chen",
"Jiajing Wu",
"Weizhe Zhang",
"Zibin Zheng"
] | In recent years, security incidents stemming from centralization defects in smart contracts have led to substantial financial losses. A centralization defect refers to any error, flaw, or fault in a smart contract's design or development stage that introduces a single point of failure. Such defects allow a specific acc... | # | ICSE2025 |
Fork State-Aware Differential Fuzzing for Blockchain Consensus Implementations | https://doi.org/10.1109/ICSE55347.2025.00085 | [
"Wonhoi Kim",
"Hocheol Nam",
"Muoi Tran",
"Amin Jalilov",
"Zhenkai Liang",
"Sang Kil Cha",
"Min Suk Kang"
] | Blockchain networks allow multiple client implementations of the same consensus algorithm by different developers to coexist in the same system. Ensuring correct implementations among these heterogeneous clients is crucial, as even slight semantic discrepancies in their implementations can lead to safety failures. Whil... | # | ICSE2025 |
Code Cloning in Solidity Smart Contracts: Prevalence, Evolution, and Impact on Development | https://doi.org/10.1109/ICSE55347.2025.00123 | [
"Ran Mo",
"Haopeng Song",
"Wei Ding",
"Chaochao Wu"
] | In recent years, the development of Solidity smart contracts has been increasing rapidly in popularity. Code cloning is a common coding practice, and many prior studies have revealed that code clones could negatively impact software maintenance and quality. However, there is little work systematically analyzing the nat... | # | ICSE2025 |
Pattern-Based Generation and Adaptation of Quantum Workflows | https://doi.org/10.1109/ICSE55347.2025.00196 | [
"Martin Beisel",
"Johanna Barzen",
"Frank Leymann",
"Lavinia Stiliadou",
"Daniel Vietz",
"Benjamin Weder"
] | Building quantum applications requires deep knowledge of quantum computing and software engineering. Hence, an abstraction layer reducing the complexity for non-experts is needed. Patterns are an established concept for the abstract description of proven solutions to recurring problems. Therefore, the quantum computing... | # | ICSE2025 |
BSan: A Powerful Identifier-Based Hardware-Independent Memory Error Detector for COTS Binaries | https://doi.org/10.1109/ICSE55347.2025.00020 | [
"Wen Zhang",
"Botang Xiao",
"Qingchen Kong",
"Le Guan",
"Wenwen Wang"
] | This paper presents BSan, a practical softwareonly memory error detector for binary code. Different from state-of-the-art binary-level detectors, which rely on either the shadow-memory-based approach or the hardware-specific feature and thus suffer from several fundamental limitations, BSan adopts an identifier-based a... | # | ICSE2025 |
RustAssistant: Using LLMs to Fix Compilation Errors in Rust Code | https://doi.org/10.1109/ICSE55347.2025.00022 | [
"Pantazis Deligiannis",
"Akash Lal",
"Nikita Mehrotra",
"Rishi Poddar",
"Aseem Rastogi"
] | The Rust programming language, with its safety guarantees, has established itself as a viable choice for low-level systems programming language over the traditional, unsafe alternatives like C/C++. These guarantees come from a strong ownership-based type system, as well as primitive support for features like closures, ... | # | ICSE2025 |
Your Fix Is My Exploit: Enabling Comprehensive DL Library API Fuzzing with Large Language Models | https://doi.org/10.1109/ICSE55347.2025.00041 | [
"Kunpeng Zhang",
"Shuai Wang",
"Jitao Han",
"Xiaogang Zhu",
"Xian Li",
"Shaohua Wang",
"Sheng Wen"
] | Deep learning (DL) libraries are widely used to form the basis of various AI applications in computer vision, natural language processing, and software engineering domains. Despite their popularity, DL libraries are known to have vulnerabilities, such as buffer overflows, use-after-free, and integer overflows, that can... | # | ICSE2025 |
BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks | https://doi.org/10.1109/ICSE55347.2025.00069 | [
"Yisong Xiao",
"Aishan Liu",
"Xinwei Zhang",
"Tianyuan Zhang",
"Tianlin Li",
"Siyuan Liang",
"Xianglong Liu",
"Yang Liu",
"Dacheng Tao"
] | Pre-trained large deep learning models are now serving as the dominant component for downstream middleware users and have revolutionized the learning paradigm, replacing the traditional approach of training from scratch locally. To reduce development costs, developers often integrate third-party pre-trained deep neural... | # | ICSE2025 |
Leveraging Propagated Infection to Crossfire Mutants | https://doi.org/10.1109/ICSE55347.2025.00150 | [
"Hang Du",
"Vijay Krishna Palepu",
"James A. Jones"
] | Mutation testing was proposed to identify weaknesses in test suites by repeatedly generating artificially faulty versions of the software (i.e., mutants) and determining if the test suite is sufficient to detect them (i.e., kill them). When the tests are insufficient, each surviving mutant provides an opportunity to im... | # | ICSE2025 |
IEEE/ACM International Workshop on Cloud Intelligence & AIOps, AIOps@ICSE 2025, Ottawa, ON, Canada, May 3, 2025 | https://doi.org/10.1109/AIOps66738.2025 | [] | # | ICSE2025 | |
Message from Cloud Intelligence / AIOps Workshop 2025 Chairs | https://doi.org/10.1109/AIOps66738.2025.00005 | [
"Jian Zhang",
"Qingwei Lin",
"Xin Peng"
] | The 6th International Workshop on Cloud Intelligence / AIOps is a forum for researchers, scientists, engineers, and practitioners to share and learn AI/ML powered DevOps solutions for cloud services. We envision that with the advance of AI/ML and related technologies like Large Language Models (LLMs), the cloud industr... | # | ICSE2025 |
Automated Service Design with Cerulean (Project Showcase) | https://doi.org/10.1109/AIOps66738.2025.00006 | [
"Vaastav Anand",
"Alok Gautam Kumbhare",
"Celine Irvene",
"Chetan Bansal",
"Gagan Somashekar",
"Jonathan Mace",
"Pedro Henrique B. Las-Casas",
"Ricardo Bianchini",
"Rodrigo Fonseca"
] | Modern cloud applications are commonly developed as microservice systems [2]. In these systems, the application is decomposed into loosely-coupled lightweight services connected over the network, each responsible for providing a single high-level business capability in the system. | # | ICSE2025 |
Automated Lifting for Cloud Infrastructure-as-Code Programs | https://doi.org/10.1109/AIOps66738.2025.00007 | [
"Jingjia Peng",
"Yiming Qiu",
"Patrick Tser Jern Kon",
"Pinhan Zhao",
"Yibo Huang",
"Zheng Guo",
"Xinyu Wang",
"Ang Chen"
] | Infrastructure-as-code (IaC) is reshaping how cloud resources are managed. IaC users write high-level programs to define their desired infrastructure, and the underlying IaC platforms automatically deploy the constituent resources into the cloud. While proven powerful at creating greenfield deployments (i.e., deploymen... | # | ICSE2025 |
Orchestrating Cross-Layer Anomaly Detection and Mitigation to Address Gray Failures in Large-Scale Cloud Infrastructure | https://doi.org/10.1109/AIOps66738.2025.00008 | [
"Ze Li",
"Chang Lou",
"Vignatha Yenugutala",
"Vivek Ramamurthy",
"Eion Blanchard",
"Minghua Ma",
"Murali Chintalapati"
] | Cloud infrastructure in production constantly experiences gray failures: a degraded state in which failures go undetected by system mechanisms, yet adversely affect end-users. Addressing the underlying anomalies on host nodes is crucial for such gray failures. However, current approaches suffer from two key limitations... | # | ICSE2025 |
Towards Using Llms for Distributed Trace Comparison (Abstract) | https://doi.org/10.1109/AIOps66738.2025.00009 | [
"Vaastav Anand",
"Pedro Henrique B. Las-Casas",
"Rodrigo Fonseca",
"Antoine Kaufmann"
] | Troubleshooting issues in modern cloud systems is a tedious task. To make this task easier for developers, researchers and practitioners have developed observability tools to capture relevant information about the system execution that can aid in triaging issues. | # | ICSE2025 |
Breaking the Cycle of Recurring Failures: Generative AI and Root Cause Analysis in Legacy Banking Systems | https://doi.org/10.1109/AIOps66738.2025.00010 | [
"Siyuan Jin",
"Zhendong Bei",
"Bichao Chen",
"Yong Xia"
] | The banking legacy systems and fragmented ownership often lead to superficial incident resolutions without addressing root causes, resulting in recurring failures. To solve this, we use Generative AI (GenAI) agents combined with the “Five Whys” technique. Our approach draws knowledge from problem descriptions, change r... | # | ICSE2025 |
Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents | https://doi.org/10.1109/AIOps66738.2025.00011 | [
"Yiming Xiang",
"Zhenning Yang",
"Jingjia Peng",
"Hermann Bauer",
"Patrick Tser Jern Kon",
"Yiming Qiu",
"Ang Chen"
] | Cloud environments are increasingly managed by Infrastructure-as-Code (IaC) platforms (e.g., Terraform), which allow developers to define their desired infrastructure as a configuration program that describes cloud resources and their dependencies. This shields developers from low-level operations for creating and main... | # | ICSE2025 |
IEEE/ACM International Workshop on Designing Software, Designing@ICSE 2025, Ottawa, ON, Canada, April 27-28, 2025 | https://doi.org/10.1109/Designing66910.2025 | [] | # | ICSE2025 | |
2nd International Workshop on Designing Software - Designing 2025 - | https://doi.org/10.1109/Designing66910.2025.00005 | [
"Yuanfang Cai",
"Michel R. V. Chaudron",
"Eunsuk Kang",
"André van der Hoek"
] | Software design has been a topic of interest in the research community since the emergence of software engineering. Indeed, in the past, a dedicated, thriving workshop existed (IWSSD [Library(2000)], last held in 2000), but gradually many topics from this workshop were absorbed into the traditional venues such as ICSE,... | # | ICSE2025 |
Documenting and Communicating Design Decisions | https://doi.org/10.1109/Designing66910.2025.00006 | [
"Steven Fraser",
"Dennis Mancl"
] | Design is both a human and a technical endeavor. Documenting and communicating design decisions remains challenging. Lightweight graphical models, text, and designfocused unit tests help. However, whether trying to understand the software output of an AI-aided design tool or reusing software components developed by oth... | # | ICSE2025 |
Assessing LLMs for Front-end Software Architecture Knowledge | https://doi.org/10.1109/Designing66910.2025.00007 | [
"Luiz Pedro Franciscatto Guerra",
"Neil A. Ernst"
] | Large Language Models (LLMs) have demonstrated significant promise in automating software development tasks, yet their capabilities with respect to software design tasks remains largely unclear. This study investigates the capabilities of an LLM in understanding, reproducing, and generating structures within the comple... | # | ICSE2025 |
Using Case Studies to Investigate Software Design Practices in Industry: Proposed Workshop Activity | https://doi.org/10.1109/Designing66910.2025.00008 | [
"David Budgen"
] | The activity will address the question: “how can we acquire deeper and good quality knowledge about design experiences to provide better guidance for both novice and expert designers?”. It is motivated by the following overarching short and long-term research strategies, although the activity is only directly concerned... | # | ICSE2025 |
Integrating User Experience Design and Agile Software Development Processes | https://doi.org/10.1109/Designing66910.2025.00009 | [
"Fayaz Suleman",
"David Wilson"
] | More than a million global corporations and Information Technology (IT) companies design and develop software solutions for their products and services. To properly manage software development, different Agile Software Development methodologies have been widely adopted. To support good user experience, user-centered me... | # | ICSE2025 |
Building MVPs: An Experience Report of a Software Engineering Capstone Course | https://doi.org/10.1109/Designing66910.2025.00010 | [
"Melissa M. Sahl",
"Mohammad Samarah"
] | Software engineers and software engineering managers are often faced with a challenge to create new products under a tight timeline to meet client and market demand. Often the problem is ill-defined, and the stakeholders vary in their view of what the product should be with only one thing common among all and that is a... | # | ICSE2025 |
What is New When Talking About Sustainable Software Architectures? | https://doi.org/10.1109/Designing66910.2025.00011 | [
"Elisa Yumi Nakagawa",
"Rick Kazman"
] | The macroscopic level of software design is software architecture, and architecture choices impact system qualities, including sustainability. Several studies have explored ways to achieve sustainable architectures: those that can endure over the long-term. However, there needs to be a broader understanding of such arc... | # | ICSE2025 |
Curating Model Problems for Software Designing | https://doi.org/10.1109/Designing66910.2025.00012 | [
"Mary Shaw",
"Marian Petre"
] | Many disciplines use standard examples for education and to share and compare research results. The examples are rich enough to study from multiple points of view; they are often called model problems. Software design lacks such a community resource. We propose an activity for Designing 2025 in which participants impro... | # | ICSE2025 |
Adaptive Abstraction with AI for Managing Software Antipatterns Throughout the Software Lifecycle | https://doi.org/10.1109/Designing66910.2025.00013 | [
"Roberto O. Andrade",
"Jenny Torres",
"Pamela Flores",
"Erick Cabezas",
"Jorge Segovia"
] | Antipatterns, commonly described as solutions that initially appear promising but have negative consequences, present significant risks in software development, particularly with respect to security. This paper explores the classification of antipatterns in various domains, such as architecture, design, and implementat... | # | ICSE2025 |
A Structured Approach to Accessibility in Software Development Lifecycle | https://doi.org/10.1109/Designing66910.2025.00014 | [
"Md Hasan Saju",
"Sanaa A. Alwidian",
"Partha Mazumder",
"Akramul Azim"
] | Accessibility is a fundamental aspect of designing and developing systems that are inclusive and usable by individuals of all abilities. Despite its importance, accessibility often receives insufficient attention during the development process, primarily due to the pressures of tight deadlines and early-stage design co... | # | ICSE2025 |
Assessing Compliance of Software System Designs to Laws, Regulations, and their Underlying Values | https://doi.org/10.1109/Designing66910.2025.00015 | [
"Agnieszka Marczak-Czajka",
"Katherine R. Dearstyne",
"Jane Cleland-Huang"
] | Software systems, particularly those in safetycritical domains or those handling personal data and financial transactions, must navigate a complex landscape of legal regulations while also aligning with societal values. Prior research has largely focused on either regulatory compliance or human values, but rarely on th... | # | ICSE2025 |
Design Obligations for Software, with Examples from Data Abstraction and Adaptive Systems | https://doi.org/10.1109/Designing66910.2025.00016 | [
"Mary Shaw"
] | Producing a good software design involves not only writing a definition that satisfies the syntax of the chosen language or structural constraints of a design paradigm. It also involves upholding a variety of expectations about the behavior of the system-the semantic expectations. These expectations may apply not only ... | # | ICSE2025 |
1st IEEE/ACM International Workshop on Neuro-Symbolic Software Engineering, NSE@ICSE 2025, Ottawa, ON, Canada, May 3, 2025 | https://doi.org/10.1109/NSE66660.2025 | [] | # | ICSE2025 | |
Next Steps in LLM-Supported Java Verification | https://doi.org/10.1109/NSE66660.2025.00007 | [
"Samuel Teuber",
"Bernhard Beckert"
] | Recent work has shown that Large Language Models (LLMs) are not only a suitable tool for code generation but also capable of generating annotation-based code specifications. Scaling these methodologies may allow us to deduce provably correctness guarantees for large-scale software systems. In comparison to other LLM ta... | # | ICSE2025 |
Neurosymbolic Architectural Reasoning: Towards Formal Analysis through Neural Software Architecture Inference | https://doi.org/10.1109/NSE66660.2025.00008 | [
"Steffen Herbold",
"Christoph Knieke",
"Andreas Rausch",
"Christian Schindler"
] | Formal analysis to ensure adherence of software to defined architectural constraints is not yet broadly used within software development, due to the effort involved in defining formal architecture models. Within this paper, we outline neural architecture inference to solve the problem of having a formal architecture de... | # | ICSE2025 |
A Graph-Centric Neuro-Symbolic Architecture Applied to Personalized Sepsis Treatments | https://doi.org/10.1109/NSE66660.2025.00009 | [
"Lucas Sakizloglou",
"Taisiya Khakharova",
"Leen Lambers"
] | Recent research on intelligent healthcare employs Deep Reinforcement Learning (DRL) to personalize treatments according to patients’ physiological characteristics and thus render treatments more effective. However, the majority of approaches rely on the relational data model, that struggles with the representation of t... | # | ICSE2025 |
StreamLLM: Enhancing Constraint Programming with Large Language Model-Generated Streamliners | https://doi.org/10.1109/NSE66660.2025.00010 | [
"Florentina Voboril",
"Vaidyanathan Peruvemba Ramaswamy",
"Stefan Szeider"
] | This paper introduces StreamLLM, a method that uses Large Language Models (LLMs) to generate streamliners for constraint programming. Streamliners narrow the search space to improve the efficiency of solving complex problems but typically require extensive manual design or exhaustive testing. StreamLLM instead leverage... | # | ICSE2025 |
IEEE/ACM Requirements Engineering for AI-powered Software, RAISE@ICSE 2025, Ottawa, ON, Canada, May 3, 2025 | https://doi.org/10.1109/RAISE66696.2025 | [] | # | ICSE2025 |
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