17 citations · 59 across the 12 of their papers we have counts for
12 papers
An Experience Report on Regression-Free Repair of Deep Neural Network Model
Takao Nakagawa, Susumu Tokumoto, Shogo Tokui +1
Systems based on Deep Neural Networks (DNNs) are increasingly being used in industry. In the process of system operation, DNNs need to be updated in order to improve their performa…
Formal Modelling of Safety Architecture for Responsibility-Aware Autonomous Vehicle via Event-B Refinement
Tsutomu Kobayashi, Martin Bondu, Fuyuki Ishikawa
Ensuring the safety of autonomous vehicles (AVs) is the key requisite for their acceptance in society. This complexity is the core challenge in formally proving their safety condit…
Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery
Peter J. Bentley, Soo Ling Lim, Paolo Arcaini +1
The use of autonomous robots for delivery of goods to customers is an exciting new way to provide a reliable and sustainable service. However, in the real world, autonomous robots…
Goal-Aware RSS for Complex Scenarios via Program Logic
Ichiro Hasuo, Clovis Eberhart, James Haydon +12
We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS r…
Practical Insights of Repairing Model Problems on Image Classification
Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa
Additional training of a deep learning model can cause negative effects on the results, turning an initially positive sample into a negative one (degradation). Such degradation is…
NeuRecover: Regression-Controlled Repair of Deep Neural Networks with Training History
Shogo Tokui, Susumu Tokumoto, Akihito Yoshii +4
Systematic techniques to improve quality of deep neural networks (DNNs) are critical given the increasing demand for practical applications including safety-critical ones. The key…
Robustifying Controller Specifications of Cyber-Physical Systems Against Perceptual Uncertainty
Tsutomu Kobayashi, Rick Salay, Ichiro Hasuo +3
Formal reasoning on the safety of controller systems interacting with plants is complex because developers need to specify behavior while taking into account perceptual uncertainty…
Architecture-Guided Test Resource Allocation Via Logic
Clovis Eberhart, Akihisa Yamada, Stefan Klikovits +4
We introduce a new logic named Quantitative Confidence Logic (QCL) that quantifies the level of confidence one has in the conclusion of a proof. By translating a fault tree represe…
A Mutation-based Approach for Assessing Weight Coverage of a Path Planner
Thomas Laurent, Paolo Arcaini, Fuyuki Ishikawa +1
Autonomous cars are subjected to several different kind of inputs (other cars, road structure, etc.) and, therefore, testing the car under all possible conditions is impossible. To…
Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systems
Hiroshi Kuwajima, Fuyuki Ishikawa
More and more software practitioners are tackling towards industrial applications of artificial intelligence (AI) systems, especially those based on machine learning (ML). However,…
A Scalable Distributed Architecture for Network- and QoS-aware Service Composition
Adrian Klein, Fuyuki Ishikawa, Shinichi Honiden
Service-Oriented Computing (SOC) enables the composition of loosely coupled service agents provided with varying Quality of Service (QoS) levels, effectively forming a multiagent s…
Proceedings: Workshop on the experience of and advances in developing dependable systems in Event-B (DS-Event-B 2012)
Fuyuki Ishikawa, Alexander Romanovsky
These proceedings include papers presented at the Workshop on "The experience of and advances in developing dependable systems in Event-B" held on November 13, 2012 as part of the…