TECPS '17: "Fault Injection in the Internet ..."
Fault Injection in the Internet of Things Applications
Mohammad Amin Alipour
(University of Houston, USA)
Internet of Things comprises a large proportion of cyber-physical systems where a group of interconnected sensors and actuators, usually with cloud backends, are used to perform a task. Vendors of Internet of Things devices provide programming frameworks to help users—usually with little knowledge of embedded or distributed systems—to develop their applications. Most of these frameworks provide an event-based abstraction of the underlying cyber-physical systems.
In this paper, we propose a preliminary set of faults for fault injection in event-based Internet of Things as a part of our ongoing investigation into the testing of Internet of Things applications. These faults intend to enhance the awareness of the programmers about the situations that might arise in the wild.
@InProceedings{TECPS17p9,
author = {Mohammad Amin Alipour},
title = {Fault Injection in the Internet of Things Applications},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {9--11},
doi = {},
year = {2017},
}
TECPS '17: "Testing Uncertainty of Cyber-Physical ..."
Testing Uncertainty of Cyber-Physical Systems in IoT Cloud Infrastructures: Combining Model-Driven Engineering and Elastic Execution
Hong-Linh Truong and Luca Berardinelli
(Vienna University of Technology, Austria)
Today's cyber-physical systems (CPS) span IoT and cloud-based datacenter infrastructures, which are highly heterogeneous with various types of uncertainty. Thus, testing uncertainties in these CPS is a challenging and multidisciplinary activity. We need several tools for modeling, deployment, control, and analytics to test and evaluate uncertainties for different configurations of the same CPS. In this paper, we explain why using state-of-the art model-driven engineering (MDE) and model-based testing (MBT) tools is not adequate for testing uncertainties of CPS in IoT Cloud infrastructures. We discus how to combine them with techniques for elastic execution to dynamically provision both CPS under test and testing utilities to perform tests in various IoT Cloud infrastructures.
@InProceedings{TECPS17p5,
author = {Hong-Linh Truong and Luca Berardinelli},
title = {Testing Uncertainty of Cyber-Physical Systems in IoT Cloud Infrastructures: Combining Model-Driven Engineering and Elastic Execution},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {5--8},
doi = {},
year = {2017},
}
TECPS '17: "Discovering Instructions for ..."
Discovering Instructions for Robust Binary-Level Coverage Criteria
Vaibhav Sharma, Taejoon Byun, Stephen McCamant, Sanjai Rayadurgam, and Mats P. E. Heimdahl
(University of Minnesota, USA)
Object-Branch Coverage (OBC) is often used to measure effectiveness of test suites, when source code is unavailable. The traditional OBC definition can be made more resilient to variations in compilers and the structure of generated code by creating more robust definitions. However finding which instructions should be included in each new definition is laborious, error-prone, and architecture-dependent. We automate the discovery of instructions to be included for an improved OBC definition on the X86 and ARM architectures. We discover all possible valid instructions by symbolically executing instruction decoders for X86 and ARM instructions. For each discovered instruction, we translate it to Vine IR, and check if the Vine IR translation satisfies the OBC definition. We verify the correctness of our tool by comparing its output with the X86 and ARM architecture manuals. Our automated instruction classification facilitates development of more robust OBC definitions with better bug-finding ability and lesser sensitivity to compiler variations.
@InProceedings{TECPS17p1,
author = {Vaibhav Sharma and Taejoon Byun and Stephen McCamant and Sanjai Rayadurgam and Mats P. E. Heimdahl},
title = {Discovering Instructions for Robust Binary-Level Coverage Criteria},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {1--4},
doi = {},
year = {2017},
}
TECPS '17: "Towards Automated Composition ..."
Towards Automated Composition of Heterogeneous Tests for Cyber-Physical Systems
Alex Groce, Paul Flikkema, and Josie Holmes
(Northern Arizona University, USA; Pennsylvania State University, USA)
A key trait of modern cyber-physical systems (CPS) is complexity due to the number of components and layers in these systems. Unlike in traditional software development, where the device layer is essentially completely abstracted away by an operating system, CPS components include low-power edge nodes, gateways, and servers that together provide sensing, actuation, communication, model and state inference, and autonomous or user-driven control. Moreover, the CPS design process involves implementation of these functions at different levels of abstraction, from high-level computational models to bare-mental implementations. Unfortunately, even when advanced testing or verification methods are applied only to low level system aspects, those efforts are separated from high-level tests of a CPS, which are often produced by a different team, and do not stress the low-level system. Effective automated test composition would make it possible to automatically produce integration/system tests for CPS, even with extremely heterogeneous aspects, where individual elements have effective tests but the interactions between the sub-systems are untested. Because of the size of the search space involved and the complexity of modeling and designing CPS, we also propose in the long term a move towards system architectures to support testing across both system layers and levels of abstraction.
@InProceedings{TECPS17p12,
author = {Alex Groce and Paul Flikkema and Josie Holmes},
title = {Towards Automated Composition of Heterogeneous Tests for Cyber-Physical Systems},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {12--15},
doi = {},
year = {2017},
}
TECPS '17: "Towards Automated Composition ..."
Towards Automated Composition of Heterogeneous Tests for Cyber-Physical Systems
Alex Groce, Paul Flikkema, and Josie Holmes
(Northern Arizona University, USA; Pennsylvania State University, USA)
A key trait of modern cyber-physical systems (CPS) is complexity due to the number of components and layers in these systems. Unlike in traditional software development, where the device layer is essentially completely abstracted away by an operating system, CPS components include low-power edge nodes, gateways, and servers that together provide sensing, actuation, communication, model and state inference, and autonomous or user-driven control. Moreover, the CPS design process involves implementation of these functions at different levels of abstraction, from high-level computational models to bare-mental implementations. Unfortunately, even when advanced testing or verification methods are applied only to low level system aspects, those efforts are separated from high-level tests of a CPS, which are often produced by a different team, and do not stress the low-level system. Effective automated test composition would make it possible to automatically produce integration/system tests for CPS, even with extremely heterogeneous aspects, where individual elements have effective tests but the interactions between the sub-systems are untested. Because of the size of the search space involved and the complexity of modeling and designing CPS, we also propose in the long term a move towards system architectures to support testing across both system layers and levels of abstraction.
@InProceedings{TECPS17p12,
author = {Alex Groce and Paul Flikkema and Josie Holmes},
title = {Towards Automated Composition of Heterogeneous Tests for Cyber-Physical Systems},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {12--15},
doi = {},
year = {2017},
}
TECPS '17: "Discovering Instructions for ..."
Discovering Instructions for Robust Binary-Level Coverage Criteria
Vaibhav Sharma, Taejoon Byun, Stephen McCamant, Sanjai Rayadurgam, and Mats P. E. Heimdahl
(University of Minnesota, USA)
Object-Branch Coverage (OBC) is often used to measure effectiveness of test suites, when source code is unavailable. The traditional OBC definition can be made more resilient to variations in compilers and the structure of generated code by creating more robust definitions. However finding which instructions should be included in each new definition is laborious, error-prone, and architecture-dependent. We automate the discovery of instructions to be included for an improved OBC definition on the X86 and ARM architectures. We discover all possible valid instructions by symbolically executing instruction decoders for X86 and ARM instructions. For each discovered instruction, we translate it to Vine IR, and check if the Vine IR translation satisfies the OBC definition. We verify the correctness of our tool by comparing its output with the X86 and ARM architecture manuals. Our automated instruction classification facilitates development of more robust OBC definitions with better bug-finding ability and lesser sensitivity to compiler variations.
@InProceedings{TECPS17p1,
author = {Vaibhav Sharma and Taejoon Byun and Stephen McCamant and Sanjai Rayadurgam and Mats P. E. Heimdahl},
title = {Discovering Instructions for Robust Binary-Level Coverage Criteria},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {1--4},
doi = {},
year = {2017},
}
TECPS '17: "Towards Automated Composition ..."
Towards Automated Composition of Heterogeneous Tests for Cyber-Physical Systems
Alex Groce, Paul Flikkema, and Josie Holmes
(Northern Arizona University, USA; Pennsylvania State University, USA)
A key trait of modern cyber-physical systems (CPS) is complexity due to the number of components and layers in these systems. Unlike in traditional software development, where the device layer is essentially completely abstracted away by an operating system, CPS components include low-power edge nodes, gateways, and servers that together provide sensing, actuation, communication, model and state inference, and autonomous or user-driven control. Moreover, the CPS design process involves implementation of these functions at different levels of abstraction, from high-level computational models to bare-mental implementations. Unfortunately, even when advanced testing or verification methods are applied only to low level system aspects, those efforts are separated from high-level tests of a CPS, which are often produced by a different team, and do not stress the low-level system. Effective automated test composition would make it possible to automatically produce integration/system tests for CPS, even with extremely heterogeneous aspects, where individual elements have effective tests but the interactions between the sub-systems are untested. Because of the size of the search space involved and the complexity of modeling and designing CPS, we also propose in the long term a move towards system architectures to support testing across both system layers and levels of abstraction.
@InProceedings{TECPS17p12,
author = {Alex Groce and Paul Flikkema and Josie Holmes},
title = {Towards Automated Composition of Heterogeneous Tests for Cyber-Physical Systems},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {12--15},
doi = {},
year = {2017},
}
TECPS '17: "Discovering Instructions for ..."
Discovering Instructions for Robust Binary-Level Coverage Criteria
Vaibhav Sharma, Taejoon Byun, Stephen McCamant, Sanjai Rayadurgam, and Mats P. E. Heimdahl
(University of Minnesota, USA)
Object-Branch Coverage (OBC) is often used to measure effectiveness of test suites, when source code is unavailable. The traditional OBC definition can be made more resilient to variations in compilers and the structure of generated code by creating more robust definitions. However finding which instructions should be included in each new definition is laborious, error-prone, and architecture-dependent. We automate the discovery of instructions to be included for an improved OBC definition on the X86 and ARM architectures. We discover all possible valid instructions by symbolically executing instruction decoders for X86 and ARM instructions. For each discovered instruction, we translate it to Vine IR, and check if the Vine IR translation satisfies the OBC definition. We verify the correctness of our tool by comparing its output with the X86 and ARM architecture manuals. Our automated instruction classification facilitates development of more robust OBC definitions with better bug-finding ability and lesser sensitivity to compiler variations.
@InProceedings{TECPS17p1,
author = {Vaibhav Sharma and Taejoon Byun and Stephen McCamant and Sanjai Rayadurgam and Mats P. E. Heimdahl},
title = {Discovering Instructions for Robust Binary-Level Coverage Criteria},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {1--4},
doi = {},
year = {2017},
}
TECPS '17: "Discovering Instructions for ..."
Discovering Instructions for Robust Binary-Level Coverage Criteria
Vaibhav Sharma, Taejoon Byun, Stephen McCamant, Sanjai Rayadurgam, and Mats P. E. Heimdahl
(University of Minnesota, USA)
Object-Branch Coverage (OBC) is often used to measure effectiveness of test suites, when source code is unavailable. The traditional OBC definition can be made more resilient to variations in compilers and the structure of generated code by creating more robust definitions. However finding which instructions should be included in each new definition is laborious, error-prone, and architecture-dependent. We automate the discovery of instructions to be included for an improved OBC definition on the X86 and ARM architectures. We discover all possible valid instructions by symbolically executing instruction decoders for X86 and ARM instructions. For each discovered instruction, we translate it to Vine IR, and check if the Vine IR translation satisfies the OBC definition. We verify the correctness of our tool by comparing its output with the X86 and ARM architecture manuals. Our automated instruction classification facilitates development of more robust OBC definitions with better bug-finding ability and lesser sensitivity to compiler variations.
@InProceedings{TECPS17p1,
author = {Vaibhav Sharma and Taejoon Byun and Stephen McCamant and Sanjai Rayadurgam and Mats P. E. Heimdahl},
title = {Discovering Instructions for Robust Binary-Level Coverage Criteria},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {1--4},
doi = {},
year = {2017},
}
TECPS '17: "Discovering Instructions for ..."
Discovering Instructions for Robust Binary-Level Coverage Criteria
Vaibhav Sharma, Taejoon Byun, Stephen McCamant, Sanjai Rayadurgam, and Mats P. E. Heimdahl
(University of Minnesota, USA)
Object-Branch Coverage (OBC) is often used to measure effectiveness of test suites, when source code is unavailable. The traditional OBC definition can be made more resilient to variations in compilers and the structure of generated code by creating more robust definitions. However finding which instructions should be included in each new definition is laborious, error-prone, and architecture-dependent. We automate the discovery of instructions to be included for an improved OBC definition on the X86 and ARM architectures. We discover all possible valid instructions by symbolically executing instruction decoders for X86 and ARM instructions. For each discovered instruction, we translate it to Vine IR, and check if the Vine IR translation satisfies the OBC definition. We verify the correctness of our tool by comparing its output with the X86 and ARM architecture manuals. Our automated instruction classification facilitates development of more robust OBC definitions with better bug-finding ability and lesser sensitivity to compiler variations.
@InProceedings{TECPS17p1,
author = {Vaibhav Sharma and Taejoon Byun and Stephen McCamant and Sanjai Rayadurgam and Mats P. E. Heimdahl},
title = {Discovering Instructions for Robust Binary-Level Coverage Criteria},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {1--4},
doi = {},
year = {2017},
}
TECPS '17: "Testing Uncertainty of Cyber-Physical ..."
Testing Uncertainty of Cyber-Physical Systems in IoT Cloud Infrastructures: Combining Model-Driven Engineering and Elastic Execution
Hong-Linh Truong and Luca Berardinelli
(Vienna University of Technology, Austria)
Today's cyber-physical systems (CPS) span IoT and cloud-based datacenter infrastructures, which are highly heterogeneous with various types of uncertainty. Thus, testing uncertainties in these CPS is a challenging and multidisciplinary activity. We need several tools for modeling, deployment, control, and analytics to test and evaluate uncertainties for different configurations of the same CPS. In this paper, we explain why using state-of-the art model-driven engineering (MDE) and model-based testing (MBT) tools is not adequate for testing uncertainties of CPS in IoT Cloud infrastructures. We discus how to combine them with techniques for elastic execution to dynamically provision both CPS under test and testing utilities to perform tests in various IoT Cloud infrastructures.
@InProceedings{TECPS17p5,
author = {Hong-Linh Truong and Luca Berardinelli},
title = {Testing Uncertainty of Cyber-Physical Systems in IoT Cloud Infrastructures: Combining Model-Driven Engineering and Elastic Execution},
booktitle = {Proc.\ TECPS},
publisher = {ACM},
pages = {5--8},
doi = {},
year = {2017},
}