2 citations · 2 across the 3 of their papers we have counts for
5 papers
Agentic Persona Generation with Critique-Refinement: An Industrial Evaluation
Mohammad Hossein Amini, David Dewar, Shiva Nejati +1
Personas are widely used in software engineering to support requirements elicitation, design, and validation, but their manual creation is costly, time-consuming, and hard to scale…
Effort-Optimized, Accuracy-Driven Labelling and Validation of Test Inputs for DL Systems: A Mixed-Integer Linear Programming Approach
Mohammad Hossein Amini, Mehrdad Sabetzadeh, Shiva Nejati
Software systems increasingly include AI components based on deep learning (DL). Reliable testing of such systems requires near-perfect test-input validity and label accuracy, with…
Test Input Validation for Vision-based DL Systems: An Active Learning Approach
Delaram Ghobari, Mohammad Hossein Amini, Dai Quoc Tran +3
Testing deep learning (DL) systems requires extensive and diverse, yet valid, test inputs. While synthetic test input generation methods, such as metamorphic testing, are widely us…
Bridging the Gap between Real-world and Synthetic Images for Testing Autonomous Driving Systems
Mohammad Hossein Amini, Shiva Nejati
Deep Neural Networks (DNNs) for Autonomous Driving Systems (ADS) are typically trained on real-world images and tested using synthetic simulator images. This approach results in tr…
Evaluating the Impact of Flaky Simulators on Testing Autonomous Driving Systems
Mohammad Hossein Amini, Shervin Naseri, Shiva Nejati
Simulators are widely used to test Autonomous Driving Systems (ADS), but their potential flakiness can lead to inconsistent test results. We investigate test flakiness in simulatio…