Review
Engineering, Industrial
Hamzea Al-Jabouri, Ahmed Saif, Abdelhakim Khatab, Claver Diallo, Uday Venkatadri
Summary: This paper provides a critical review of 136 research articles related to the selective maintenance problem (SMP) and discusses a selection of key representative models. The review is framed according to formulation characteristics and solution approaches, aiming to identify drawbacks and blind spots of the SMP literature and provide a roadmap for innovative research topics to advance the academic and industrial contributions of SMP.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Information Systems
Mauro Pipponzi, Alberto Sangiovanni-Vincentelli
Summary: Test for Reliability involves continuously stressing an IC device under various corner conditions and dynamically adjusting the test based on real-time observation of critical signals. Our approach goes beyond traditional reliability methods, covering the entire process from design to failure analysis.
Article
Computer Science, Artificial Intelligence
Zhaopin Su, Guofu Zhang, Feng Yue, Dezhi Zhan, Miqing Li, Bin Li, Xin Yao
Summary: The article introduces a MOTRAP model with a predetermined reliability and theoretically deduces new lower bounds on testing time invested in different modules based on the necessary condition for achieving the given reliability. Enhanced constraint-handling techniques (ECHTs) are developed to correct and reduce constraint violation in combination with MOEAs. The proposed ECHTs are evaluated and shown to work well with MOEAs, focusing the search on the feasible region of the predetermined reliability and providing better and more diverse choices in test planning for software project managers.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Jian Chen, Tao Wang, Jie Jia, Liang Guo, Xingwei Wang
Summary: This article investigates the reliable analysis and joint optimization over Nakagami-m fading for coordinated multi-point (CoMP) assisted multi-cell systems. By proposing the ABC algorithm framework, the joint sub-carrier assignment and power allocation problem for reliability optimization are successfully solved. Simulation results show that the proposed frameworks can significantly enhance the reliability of user equipment.
APPLIED SOFT COMPUTING
(2022)
Article
Chemistry, Multidisciplinary
Nam Eung Hwang, Hyung Jun Kim, Jae Gwan Kim
Summary: This paper proposes a centralized mission planning algorithm for solving multi-robot-multi-mission problems by minimizing total mission completion time. The algorithm first addresses single-robot-multi-mission problems, and then extends it to multi-robot-multi-mission problems with a mission-plan-adjustment step. Simulation results demonstrate the superior performance of the proposed algorithm in diverse situations.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Industrial
Xian Zhao, Ying Dai, Qingan Qiu, Yaguang Wu
Summary: This paper studies the optimal mission abort and allocation of standby components policies for the k-out-of-(n+m):F system considering partial mission loss. By dynamically controlling the mission abort decision and using a recursive algorithm to calculate mission reliability and system survivability, the paper aims to minimize the expected cost and balance the mission reliability and the system survivability.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Multidisciplinary Sciences
Sohail Razzaq, Costas Xydeas, Anzar Mahmood, Saeed Ahmed, Naeem Iqbal Ratyal, Jamshed Iqbal
Summary: This study considers the problem of selecting appropriate operators by a central authority for optimized mission performance. The focus is on the use of UAVs as firefighting operators, and the comparison of deterministic and stochastic resource allocation optimization techniques. Simulation results show the proposed stochastic schemes to be accurate and computationally efficient for time-critical resource allocation optimization. The development of a comprehensive UAV firefighting mission framework and time-efficient search schemes make this work valuable for other UAV applications and resource allocation in various fields.
Article
Computer Science, Information Systems
Chaebeen Nam, Sa Math, Prohim Tam, Seokhoon Kim
Summary: This paper presents an intelligent MANO solution using software-defined mobile edge computing and support vector machine algorithm to address resource utilization and allocation in large-scale and complicated network environments. The proposed scheme demonstrates remarkable QoS performance, including communication reliability, latency, and throughput.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Chemistry, Analytical
Hongxing Zheng, Jinpeng Yuan
Summary: This paper proposes an integrated mission planning framework using a two-level adaptive variable neighborhood search algorithm to maximize profit and minimize costs, showing better performance compared to conventional methods through simulation results.
Article
Engineering, Electrical & Electronic
Dachao Yu, Yao Sun, Yuetai Li, Lei Zhang, Muhammad Ali Imran
Summary: This article focuses on the importance of distributed consensus in wireless connected autonomous systems, emphasizing the significance of communication resource allocation schemes in achieving high reliability and low latency. It provides optimized resource allocation solutions and investigates the optimal number of nodes for the best reliability performance.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Deepa Jagyasi, Marceau Coupechoux
Summary: This paper proposes a secure and robust MIMO transceiver for supporting multicast MCC in the presence of multiple eavesdroppers. Security is achieved through physical layer security mechanisms and reliability is achieved through robust system design. Numerical results demonstrate the importance of robust design for reliable MCC.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Industrial
Xiuzhen Yang, Yihai He, Ruoyu Liao, Yuqi Cai, Wei Dai
Summary: This paper proposes a mission reliability-centered opportunistic maintenance optimization model for multistate manufacturing systems to realize the optimal combination of maintenance activities. By predicting the actual operational state and analyzing the failure mechanism, the optimal maintenance strategy is obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Public, Environmental & Occupational Health
Sean Shao Wei Lam, Ahmad Reza Pourghaderi, Hairil Rizal Abdullah, Francis Ngoc Hoang Long Nguyen, Fahad Javaid Siddiqui, John Pastor Ansah, Jenny G. Low, David Bruce Matchar, Marcus Eng Hock Ong
Summary: This article describes the development of a dynamic simulation framework in Singapore during the COVID-19 pandemic to support agile resource planning. The study data was derived from Singapore General Hospital and public domain sources, and the models were calibrated against historical data. Several variants of the model were rapidly developed to adapt to the quickly changing situation, enabling the quick deployment of resources to sustain high-quality health services.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Computer Science, Software Engineering
Jacob Aubertine, Kenan Chen, Vidhyashree Nagaraju, Lance Fiondella
Summary: C-SFRAT is a tool that automatically applies software reliability engineering methods to accurately characterize test activities during the defect discovery process, guiding the allocation of limited resources to maximize defect discovery and improve reliability.
Article
Computer Science, Information Systems
Melisa Lopez, Troels B. Sorensen, Istvan Z. Kovacs, Jeroen Wigard, Preben Mogensen
Summary: Accurately estimating the service quality that users will experience along a route is crucial for mission-critical services, but different estimation methods may lead to uncertainty. Using a data-driven estimation approach can help reduce uncertainty and improve accuracy.
Article
Computer Science, Software Engineering
Antonia Bertolino, Guglielmo De Angelis, Antonio Guerriero, Breno Miranda, Roberto Pietrantuono, Stefano Russo
Summary: In DevOps practices, candidate software releases need to pass quality gates and meet key indicators, with software reliability being an important one. This research proposes DevOpRET, a reliability testing approach that utilizes operational-profile-based testing and usage/failure data to evaluate software reliability.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Article
Engineering, Industrial
Roberto Pietrantuono, Peter Popov, Stefano Russo
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2020)
Article
Computer Science, Software Engineering
Antonia Bertolino, Breno Miranda, Roberto Pietrantuono, Stefano Russo
Summary: The study presents an adaptive software testing strategy covrel+, which combines operational profile and coverage spectrum to enhance the reliability of the test program. Experimental results show that this strategy generally outperforms traditional operational testing in achieving a given reliability target or detecting faults within the same testing budget, with greater ability to detect hard-to-detect faults.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Theory & Methods
Antonia Bertolino, Pietro Braione, Guglielmo De Angelis, Luca Gazzola, Fitsum Kifetew, Leonardo Mariani, Matteo Orru, Mauro Pezze, Roberto Pietrantuono, Stefano Russo, Paolo Tonella
Summary: Field testing refers to testing techniques that uncover faults missed during in-house testing by operating in the field. It is becoming more popular as software systems become more complex. By categorizing field testing approaches based on environment and system, and addressing research questions related to field testing requirements and management, this article highlights challenging research directions in field testing.
ACM COMPUTING SURVEYS
(2021)
Article
Computer Science, Software Engineering
Domenico Cotroneo, Luigi De Simone, Roberto Natella, Roberto Pietrantuono, Stefano Russo
Summary: The article introduces a configurable micro-rejuvenation technique to counter software aging in Android-based mobile devices, focusing on fine-grained manipulation of system data structures. Experimental results demonstrate significant improvements in responsiveness and time to failure of mobile operating systems.
JOURNAL OF SYSTEMS AND SOFTWARE
(2022)
Article
Computer Science, Hardware & Architecture
Ermeson Andrade, Roberto Pietrantuono, Fumio Machida, Domenico Cotroneo
Summary: This paper investigates the software aging issue in an image classification system running on cloud and edge computing environments, and analyzes the degradation trends in system performance and memory resources. It is found that the edge environment has less impact on performance degradation compared to the cloud environment under high workload, despite having fewer allocated memory resources.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Roberto Pietrantuono, Massimo Ficco, Francesco Palmieri
Summary: This paper proposes a hybrid method to assess the survivability of an IoT system under resource-exhaustion attacks and optimize the preventive maintenance trigger period. The method combines measurements and model-based analysis to estimate resource consumption and simulate system behavior during attacks.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Proceedings Paper
Computer Science, Software Engineering
Matteo Camilli, Antonio Guerriero, Andrea Janes, Barbara Russo, Stefano Russo
Summary: Continuous quality assurance for extra-functional properties of modern software systems is a challenge. We propose a novel methodology and platform, called MIPaRT, for automatically testing the performance and reliability of microservice operations. The platform supports continuous testing and monitoring, and provides additional insights into the performance and reliability behavior of microservices.
3RD ACM/IEEE INTERNATIONAL CONFERENCE ON AUTOMATION OF SOFTWARE TEST (AST 2022)
(2022)
Proceedings Paper
Computer Science, Software Engineering
Ermeson Andrade, Fumio Machida, Roberto Pietrantuono, Domenico Cotroneo
Summary: The study indicates that memory degradation trends in cloud computing environments have significant impacts on the performance and stability of applications. Through experimental investigation in private and public cloud environments, potential causes of memory degradation were identified.
2021 IEEE INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING WORKSHOPS (ISSREW 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Roberto Pietrantuono
Summary: The article introduces a new class called Combinatorial Causal Optimization Problems (CCOP) and discusses its application in causal inference. The research uses optimization algorithms to automatically construct cause-effect solutions for plausibility and novelty, providing useful solutions for real-world problems in various domains.
2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021)
(2021)
Proceedings Paper
Computer Science, Software Engineering
Antonia Bertolino, Antonio Guerriero, Breno Miranda, Roberto Pietrantuono, Stefano Russo
2020 ACM/IEEE 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2020)
(2020)
