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18-tik 1-10 emaitza erakusten
Towards a Taxonomy for Eliciting Design-Operation Continuum Requirements of Cyber-Physical Systems
(IEEE, 2020)
Software systems that are embedded in autonomous Cyber-Physical Systems (CPSs) usually have a large life-cycle, both during its development and in maintenance. This software evolves during its life-cycle in order to ...
Seeding Strategies for Multi-Objective Test Case Selection: An Application on Simulation-based Testing
(ACM, 2020)
The time it takes software systems to be tested is usually long. This is often caused by the time it takes the entire test suite to be executed. To optimize this, regression test selection approaches have allowed for ...
Generating metamorphic relations for cyber-physical systems with genetic programming: an industrial case study
(ACM, 2021)
One of the major challenges in the verification of complex industrial Cyber-Physical Systems is the difficulty of determining whether a particular system output or behaviour is correct or not, the socalled test oracle ...
QoS-aware Metamorphic Testing: An Elevation Case Study
(IEEE, 2020)
Elevators are among the oldest and most widespread transportation systems, yet their complexity increases rapidly to satisfy customization demands and to meet quality of service requirements. Verification and validation ...
Some Seeds are Strong : Seeding Strategies for Search-based Test Case Selection
(ACM, 2022)
The time it takes software systems to be tested is usually long. Search-based test selection has been a widely investigated technique to optimize the testing process. In this paper, we propose a set of seeding strategies ...
Multi-Objective Metamorphic Test Case Selection: an Industrial Case Study (Practical Experience Report)
(IEEE, 2022)
Metamorphic testing is a technique that has shown great potential to alleviate the test oracle problem by exploiting the relations among the inputs and outputs of different executions of a system. However, this approach ...
On the Cost-Effectiveness of Composite Metamorphic Relations for Testing Deep Learning Systems
(IEEE, 2022)
Deep Learning (DL) components are increasing their presence in mission and safety-critical systems, such as autonomous vehicles. The verification process of such systems needs to be rigorous, for which automated solutions ...
Evolutionary generation of metamorphic relations for cyber-physical systems
(ACM, 2022)
A problem when testing Cyber-Physical Systems (CPS) is the difficulty of determining whether a particular system output or behaviour is correct or not. Metamorphic testing alleviates such a problem by reasoning on the ...
Uncertainty-aware Robustness Assessment of Industrial Elevator Systems
(ACM, 2022)
Industrial elevator systems are commonly used software systems in our daily lives, which operate in uncertain environments such as unpredictable passenger traffic, uncertain passenger attributes and behaviors, and hardware ...
Spectrum-based feature localization for families of systems
(Elsevier, 2022)
In large code bases, locating the elements that implement concrete features of a system is challenging. This information is paramount for maintenance and evolution tasks, although not always explicitly available. In this ...