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ORCIDAITest 2024: Shanghai, China
- IEEE International Conference on Artificial Intelligence Testing, AITest 2024, Shanghai, China, July 15-18, 2024. IEEE 2024, ISBN 979-8-3503-6505-4
- Monowar Bhuyan, Haihua Chen:
Message from the PC Chairs, IEEE AITest 2024. xi - Jerry Zeyu Gao, Hiroyuki Sato, Wen Wu:
General Chair Message; IEEE CISOSE 2024. viii-ix - Monowar Bhuyan, Lingzi Hong, Fanjing Meng, Junhua Ding:
Plenary Panel at IEEE CISOSE 2024; Ethical, Societal, and Policy Implications of AI. xxx - Fanjing Meng, Shuguang Qi, Chao Li:
Sustainable AI: Pursuing Computational Efficiency and Environmental Harmony. xxviii-xxix - Hong Zhu, Junhua Ding:
Message From the General Chairs; IEEE AITest 2024. x - Hong Zhu, Xiaoli Li, Junhua Ding, Emese Bari, Yang Liu:
Plenary Panel at IEEE CISOSE 2024; GenAI, Where are You Going? xxvi-xxvii - Hans-Werner Wiesbrock, Jürgen Großmann:
Outline of an Independent Systematic Blackbox Test for ML-based Systems. 1-10 - Nicolas Grube, Mozhdeh Massah, Michael Tebbe, Paul Wancura, Hans-Werner Wiesbrock, Jürgen Großmann, Sami Kharma
:
On a Systematic Test of ML-Based Systems: Experiments on Test Statistics. 11-20 - Jing Shu, Bing-Jiun Miu, Eugene Chang, Jerry Gao, Jun Liu:
Computer Vision Intelligence Test Modeling and Generation: A Case Study on Smart OCR. 21-28 - Zesheng Chen, Jack Li, Chao Chen:
MEH-FEST-NA: An Ensemble Defense System Against Adversarial Attacks in Speaker Verification Systems. 29-36 - Muyeed Ahmed, Iulian Neamtiu:
Quantifying the Vulnerability of Anomaly Detection Implementations to Nondeterminism-based Attacks. 37-46 - Herbert Mühlburger, Franz Wotawa:
FaultLines - Evaluating the Efficacy of Open-Source Large Language Models for Fault Detection in Cyber-Physical Systems. 47-54 - Debalina Ghosh Paul, Hong Zhu, Ian Bayley:
ScenEval: A Benchmark for Scenario-Based Evaluation of Code Generation. 55-63 - Sunny Shree, Yu Lei, Raghu N. Kacker, D. Richard Kuhn:
Proxima: A Proxy Model-Based Approach to Influence Analysis. 64-72 - Florian Klück, Daniel Sumann, Franz Wotawa:
Utilizing Genetic Algorithms for Generating Critical Scenarios for Testing Autonomous Driving Functions. 73-80 - Mahdi Farzandway, Fatemeh Ghassemi:
SpecNLP: A Pre-trained Model Enhanced with Spectrum Profile for Bug Localization. 81-86 - Debalina Ghosh Paul, Hong Zhu, Ian Bayley:
Benchmarks and Metrics for Evaluations of Code Generation: A Critical Review. 87-94 - Medlen Jiri, Bari Emese, Patrick Medlen:
Leveraging Large Language Models for Python Unit Test. 95-100 - Jiyuan Sun, Haibo Yu, Jianjun Zhao:
Black-box l1 and £2 Adversarial Attack Based on Genetic Algorithm. 101-108 - Tanha Miah, Hong Zhu:
User Centric Evaluation of Code Generation Tools (Invited Paper). 109-119 - Yuhan Zhou, Fengjiao Tu, Kewei Sha, Junhua Ding, Haihua Chen:
A Survey on Data Quality Dimensions and Tools for Machine Learning Invited Paper. 120-131 - Jerry Gao, Prerna Garsole, Radhika Agarwal, Shengqiang Liu:
AI Test Modeling and Analysis for Intelligent Chatbot Mobile App - A Case Study on Wysa. 132-141 - Junhua Ding, Huyen Nguyen, Haihua Chen:
Evaluation of Question-Answering Based Text Summarization using LLM Invited Paper. 142-149 - Meixian Zhang, Xue Shi, Jiaxin Huang:
Real-Time Anomaly Detection in Time Series Using Transformer-Like Architecture. 150-151 - Priyanka Dattatray Sawant:
Test Case Prioritization for Regression Testing Using Machine Learning. 152-153
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