Search Results for author:
Found 7 papers, 3 papers with code
CSA-Trans: Code Structure Aware Transformer for AST
When applying the Transformer architecture to source code, designing a good self-attention mechanism is critical as it affects how node relationship is extracted from the Abstract Syntax Trees (ASTs) of the source code.
Autonomous Large Language Model Agents Enabling Intent-Driven Mobile GUI Testing
On average, DroidAgent achieved 61% activity coverage, compared to 51% for current state-of-the-art GUI testing techniques.
Genetic Improvement @ ICSE 2020
Following Prof. Mark Harman of Facebook's keynote and formal presentations (which are recorded in the proceedings) there was a wide ranging discussion at the eighth international Genetic Improvement workshop, GI-2020 @ ICSE (held as part of the 42nd ACM/IEEE International Conference on Software Engineering on Friday 3rd July 2020).
Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving
The development process in use consists of multiple iterations of data collection, labelling, training, and evaluation.
SINVAD: Search-based Image Space Navigation for DNN Image Classifier Test Input Generation
The testing of Deep Neural Networks (DNNs) has become increasingly important as DNNs are widely adopted by safety critical systems.
Arachne: Search Based Repair of Deep Neural Networks
The rapid and widespread adoption of Deep Neural Networks (DNNs) has called for ways to test their behaviour, and many testing approaches have successfully revealed misbehaviour of DNNs.
Guiding Deep Learning System Testing using Surprise Adequacy
Recently, a number of coverage criteria based on neuron activation values have been proposed.
