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AITest 2019: Newark, CA, USA
- IEEE International Conference On Artificial Intelligence Testing, AITest 2019, Newark, CA, USA, April 4-9, 2019. IEEE 2019, ISBN 978-1-7281-0492-8
- Noureddine Aribi, Nadjib Lazaar, Yahia Lebbah, Samir Loudni, Mehdi Maamar:
A Multiple Fault Localization Approach Based on Multicriteria Analytical Hierarchy Process. 1-8 - Ayan Banerjee, Imane Lamrani, Prajwal Paudyal, Sandeep K. S. Gupta:
Generation of Movement Explanations for Testing Gesture Based Co-Operative Learning Applications. 9-16 - Sulaiman Alhaidari, Mohamed A. Zohdy:
Network Anomaly Detection Using Two-Dimensional Hidden Markov Model Based Viterbi Algorithm. 17-18 - Sahar Tahvili, Leo Hatvani, Michael Felderer, Wasif Afzal, Markus Bohlin:
Automated Functional Dependency Detection Between Test Cases Using Doc2Vec and Clustering. 19-26 - Jens Henriksson, Christian Berger, Markus Borg, Lars Tornberg, Cristofer Englund, Sankar Raman Sathyamoorthy, Stig Ursing:
Towards Structured Evaluation of Deep Neural Network Supervisors. 27-34 - Shunhui Ji, Qin Chen, Pengcheng Zhang:
Neural Network Based Test Case Generation for Data-Flow Oriented Testing. 35-36 - Josip Bozic, Oliver A. Tazl, Franz Wotawa:
Chatbot Testing Using AI Planning. 37-44 - Iosif Itkin, Anna Gromova, Anton Sitnikov, Dmitry Legchikov, Evgenii Tsymbalov, Rostislav Yavorskiy, Andrey Novikov, Kirill Rudakov:
User-Assisted Log Analysis for Quality Control of Distributed Fintech Applications. 45-51 - Kesav Viswanadha, Shivkumar Shivaji, Ram Shanmugam, Seounghan Song, Seoyoung Choi, Naresh Kumar:
ATARI: Autonomous Testing and Real-Time Intelligence - A Framework for Autonomously Testing Modern Applications. 52-54 - Jonathan Guichard, Elayne Ruane, Ross Smith, Dan Bean, Anthony Ventresque:
Assessing the Robustness of Conversational Agents using Paraphrases. 55-62 - Taejoon Byun, Vaibhav Sharma, Abhishek Vijayakumar, Sanjai Rayadurgam, Darren D. Cofer:
Input Prioritization for Testing Neural Networks. 63-70 - Pengcheng Zhang, Qiyin Dai, Shunhui Ji:
Condition-Guided Adversarial Generative Testing for Deep Learning Systems. 71-72 - Carlo Ieva, Arnaud Gotlieb, Souhila Kaci, Nadjib Lazaar:
Deploying Smart Program Understanding on a Large Code Base. 73-80 - Tariq M. King, Jason Arbon, Dionny Santiago, David Adamo, Wendy Chin, Ram Shanmugam:
AI for Testing Today and Tomorrow: Industry Perspectives. 81-88 - Yanshan Chen, Ziyuan Wang, Dong Wang, Yongming Yao, Zhenyu Chen:
Behavior Pattern-Driven Test Case Selection for Deep Neural Networks. 89-90 - Xin Yin, Vincenzo Musco, Iulian Neamtiu, Usman Roshan:
Statistically Rigorous Testing of Clustering Implementations. 91-98 - Marc Roper:
Using Machine Learning to Classify Test Outcomes. 99-100 - Dusica Marijan, Arnaud Gotlieb, Mohit Kumar Ahuja:
Challenges of Testing Machine Learning Based Systems. 101-102 - Cristian Augusto, Jesús Morán, Claudio de la Riva, Javier Tuya:
Test-Driven Anonymization for Artificial Intelligence. 103-110 - Koosha Sadeghi, Ayan Banerjee, Sandeep K. S. Gupta:
An Analytical Framework for Security-Tuning of Artificial Intelligence Applications Under Attack. 111-118 - Dong Wang, Ziyuan Wang, Chunrong Fang, Yanshan Chen, Zhenyu Chen:
DeepPath: Path-Driven Testing Criteria for Deep Neural Networks. 119-120 - Mathieu Collet, Arnaud Gotlieb, Nadjib Lazaar, Morten Mossige:
Stress Testing of Single-Arm Robots Through Constraint-Based Generation of Continuous Trajectories. 121-128 - Clemens Mühlbacher, Gerald Steinbauer, Michael Reip, Stephan Gspandl:
Constraint-Based Testing of An Industrial Multi-Robot Navigation System. 129-137 - Claude Michel, Michel Rueher:
Dedicated Search Strategies For Finding Critical Counterexamples In Programs With Floating Point Computations. 138-139 - Morteza Pourreza Shahri, Madhusudan Srinivasan, Gillian Reynolds, Diane Bimczok, Indika Kahanda, Upulee Kanewala:
Metamorphic Testing for Quality Assurance of Protein Function Prediction Tools. 140-148 - Hong Zhu, Dongmei Liu, Ian Bayley, Rachel Harrison, Fabio Cuzzolin:
Datamorphic Testing: A Method for Testing Intelligent Applications. 149-156 - Prashanta Saha, Upulee Kanewala:
Fault Detection Effectiveness of Metamorphic Relations Developed for Testing Supervised Classifiers. 157-164
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