Zobrazeno 1 - 10
of 153
pro vyhledávání: '"Arcaini, Paolo"'
The most promising applications of quantum computing are centered around solving search and optimization tasks, particularly in fields such as physics simulations, quantum chemistry, and finance. However, the current quantum software testing methods
Externí odkaz:
http://arxiv.org/abs/2408.00501
Foundation models are trained on a large amount of data to learn generic patterns. Consequently, these models can be used and fine-tuned for various purposes. Naturally, studying such models' use in the context of digital twins for cyber-physical sys
Externí odkaz:
http://arxiv.org/abs/2407.18779
Quantum computers have the potential to outperform classical computers for some complex computational problems. However, current quantum computers (e.g., from IBM and Google) have inherent noise that results in errors in the outputs of quantum softwa
Externí odkaz:
http://arxiv.org/abs/2404.12892
Autor:
Murillo, Juan M., Garcia-Alonso, Jose, Moguel, Enrique, Barzen, Johanna, Leymann, Frank, Ali, Shaukat, Yue, Tao, Arcaini, Paolo, Castillo, Ricardo Pérez, de Guzmán, Ignacio García Rodríguez, Piattini, Mario, Ruiz-Cortés, Antonio, Brogi, Antonio, Zhao, Jianjun, Miranskyy, Andriy, Wimmer, Manuel
As quantum computers evolve, so does the complexity of the software that they can run. To make this software efficient, maintainable, reusable, and cost-effective, quality attributes that any industry-grade software should strive for, mature software
Externí odkaz:
http://arxiv.org/abs/2404.06825
Quantum Extreme Learning Machine (QELM) is an emerging technique that utilizes quantum dynamics and an easy-training strategy to solve problems such as classification and regression efficiently. Although QELM has many potential benefits, its real-wor
Externí odkaz:
http://arxiv.org/abs/2402.12777
In the near term, quantum approximate optimization algorithms (QAOAs) hold great potential to solve combinatorial optimization problems. These are hybrid algorithms, i.e., a combination of quantum and classical algorithms. Several proof-of-concept ap
Externí odkaz:
http://arxiv.org/abs/2312.15547
As a new research area, quantum software testing lacks systematic testing benchmarks to assess testing techniques' effectiveness. Recently, some open-source benchmarks and mutation analysis tools have emerged. However, there is insufficient evidence
Externí odkaz:
http://arxiv.org/abs/2311.16913
Autonomous driving systems (ADSs) must be sufficiently tested to ensure their safety. Though various ADS testing methods have shown promising results, they are limited to a fixed set of vehicle characteristics settings (VCSs). The impact of variation
Externí odkaz:
http://arxiv.org/abs/2311.14461
Quantum software engineering (QSE) is receiving increasing attention, as evidenced by increasing publications on topics, e.g., quantum software modeling, testing, and debugging. However, in the literature, quantum software requirements engineering (Q
Externí odkaz:
http://arxiv.org/abs/2309.13358
With the increased developments in quantum computing, the availability of systematic and automatic testing approaches for quantum programs is becoming increasingly essential. To this end, we present the quantum software testing tool QuCAT for combina
Externí odkaz:
http://arxiv.org/abs/2309.00119