265 citations · 369 across the 19 of their papers we have counts for
5 papers · 1 filter
Data Synthesis for Testing Black-Box Machine Learning Models
Diptikalyan Saha, Aniya Aggarwal, Sandeep Hans
The increasing usage of machine learning models raises the question of the reliability of these models. The current practice of testing with limited data is often insufficient. In…
Automated Testing of AI Models
Swagatam Haldar, Deepak Vijaykeerthy, Diptikalyan Saha
The last decade has seen tremendous progress in AI technology and applications. With such widespread adoption, ensuring the reliability of the AI models is crucial. In past, we too…
Towards API Testing Across Cloud and Edge
Samuel Ackerman, Sanjib Choudhury, Nirmit Desai +5
API economy is driving the digital transformation of business applications across the hybrid Cloud and edge environments. For such transformations to succeed, end-to-end testing of…
Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets
Nitin Gupta, Hima Patel, Shazia Afzal +10
The quality of training data has a huge impact on the efficiency, accuracy and complexity of machine learning tasks. Various tools and techniques are available that assess data qua…
Testing Framework for Black-box AI Models
Aniya Aggarwal, Samiulla Shaikh, Sandeep Hans +3
With widespread adoption of AI models for important decision making, ensuring reliability of such models remains an important challenge. In this paper, we present an end-to-end gen…