Challenges in Adopting Artificial Intelligence Based User Input Verification Framework in Reporting Software Systems
Artificial intelligence is driving new industrial solutions for challenging problems once considered impossible. Many large-scale companies use AI to identify opportunities to improve business processes and products. Despite the promise and perils of AI, many traditional software systems (e.g., taxation or reporting) are implemented without AI in mind. Adopting AI-based capabilities in such software can be challenging due to a lack of resources and uncertainties in requirements. This paper documents our experience working with our industry partner on adopting AI capabilities in enterprise software. The enterprise software receives and processes thousands of user inputs with different configuration settings daily, which makes manual user input verification infeasible. To assist our industry partner, we design and integrate an AI-based input verification framework into the software. However, during the design and integration of the framework, we encounter many challenges that range from the requirement engineering process to the development, adoption, and verification process. We discuss the challenges we encountered and their corresponding solutions while working with our industrial partner to integrate the AI-based input verification framework into their non-AI software. Our experience report may provide valuable insight to practitioners and researchers on better integrating AI-based capabilities with existing software systems.
Wed 17 MayDisplayed time zone: Hobart change
13:45 - 15:15 | AI systems engineeringSEIP - Software Engineering in Practice / Technical Track / NIER - New Ideas and Emerging Results / Journal-First Papers at Meeting Room 104 Chair(s): Xin Peng Fudan University | ||
13:45 15mTalk | FedDebug: Systematic Debugging for Federated Learning Applications Technical Track | ||
14:00 15mTalk | Practical and Efficient Model Extraction of Sentiment Analysis APIs Technical Track Weibin Wu Sun Yat-sen University, Jianping Zhang The Chinese University of Hong Kong, Victor Junqiu Wei The Hong Kong Polytechnic University, Xixian Chen Tencent, Zibin Zheng School of Software Engineering, Sun Yat-sen University, Irwin King The Chinese University of Hong Kong, Michael Lyu The Chinese University of Hong Kong | ||
14:15 15mTalk | CrossCodeBench: Benchmarking Cross-Task Generalization of Source Code Models Technical Track Changan Niu Software Institute, Nanjing University, Chuanyi Li Nanjing University, Vincent Ng Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX 75083-0688, Bin Luo Nanjing University Pre-print | ||
14:30 15mTalk | Challenges in Adopting Artificial Intelligence Based User Input Verification Framework in Reporting Software Systems SEIP - Software Engineering in Practice Dong Jae Kim Concordia University, Tse-Hsun (Peter) Chen Concordia University, Steve Sporea , Andrei Toma ERA Environmental Management Solutions, Laura Weinkam , Sarah Sajedi ERA Environmental Management Solutions, Steve Sporea | ||
14:45 7mTalk | Towards Understanding Quality Challenges of the Federated Learning for Neural Networks: A First Look from the Lens of Robustness Journal-First Papers Amin Eslami Abyane University of Calgary, Derui Zhu Technical University of Munich, Roberto Souza University of Calgary, Lei Ma University of Alberta, Hadi Hemmati York University | ||
14:52 7mTalk | An Empirical Study of the Impact of Hyperparameter Tuning and Model Optimization on the Performance Properties of Deep Neural Networks Journal-First Papers Lizhi Liao Concordia University, Heng Li Polytechnique Montréal, Weiyi Shang University of Waterloo, Lei Ma University of Alberta | ||
15:00 7mTalk | Black-box Safety Analysis and Retraining of DNNs based on Feature Extraction and Clustering Journal-First Papers Mohammed Attaoui University of Luxembourg, Hazem FAHMY University of Luxembourg, Fabrizio Pastore University of Luxembourg, Lionel Briand University of Luxembourg; University of Ottawa Link to publication Pre-print | ||
15:07 7mTalk | Iterative Assessment and Improvement of DNN Operational Accuracy NIER - New Ideas and Emerging Results Antonio Guerriero Università di Napoli Federico II, Roberto Pietrantuono Università di Napoli Federico II, Stefano Russo Università di Napoli Federico II Pre-print |