Persona: Heradio Gil, Rubén
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rheradio@issi.uned.es
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0000-0002-7131-0482
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Heradio Gil
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Rubén
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18 resultados
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Publicación Using Extended Logical Primitives for Efficient BDD Building(MDPI, 2020) Fernández Amoros, David José; Bra Gutiérrez, Sergio; Aranda Escolástico, Ernesto; Heradio Gil, RubénBinary Decision Diagrams (BDDs) have been used to represent logic models in a variety of research contexts, such as software product lines, circuit testing, and plasma confinement, among others. Although BDDs have proven to be very useful, the main problem with this technique is that synthesizing BDDs can be a frustratingly slow or even unsuccessful process, due to its heuristic nature. We present an extension of propositional logic to tackle one recurring phenomenon in logic modeling, namely groups of variables related by an exclusive-or relationship, and also consider two other extensions: one in which at least n variables in a group are true and another one for in which at most n variables are true. We add XOR, atLeast-n and atMost-n primitives to logic formulas in order to reduce the size of the input and also present algorithms to efficiently incorporate these constructions into the building of BDDs. We prove, among other results, that the number of nodes created during the process for XOR groups is reduced from quadratic to linear for the affected clauses. the XOR primitive is tested against eight logical models, two from industry and six from Kconfig-based open-source projects. Results range from no negative effects in models without XOR relations to performance gains well into two orders of magnitude on models with an abundance of this kind of relationship.Publicación Evidence-Based Control Engineering Education: Evaluating the LCSD Simulation Tool(IEEE, 2020-09-25) Marin, Loreto; Vargas, Héctor; Heradio Gil, Rubén; Torre Cubillo, Luis de la; Díaz Martínez, José Manuel; Dormido Canto, SebastiánThe advance in control engineering education needs well-designed studies that validate what methods and tools work best. This paper addresses the lack of empirical evidence supporting innovations in control engineering education by proposing a methodology that works at different abstraction levels. Hence, innovations' impact on students' performance can be statistically analyzed either globally or locally by examining competencies or fine-grained indicators, respectively. The article reports the application of the methodology for evaluating an interactive simulation tool, named LCSD, on 101 students at the Pontifical Catholic University of Valparaiso in Chile. According to the experimental results, LCSD is an effective free alternative to enhance the student's skills on control system analysis for our automatic control course. Also, some improvements have been identified for future LCSD versions.Publicación Scalable Sampling of Highly-Configurable Systems: Generating Random Instances of the Linux Kernel(Association for Computing Machinery (ACM), 2023-01-05) Mayr Dorn, Christoph; Egyed, Alexander; Fernández Amoros, David José; Heradio Gil, RubénSoftware systems are becoming increasingly configurable. A paradigmatic example is the Linux kernel, which can be adjusted for a tremendous variety of hardware devices, from mobile phones to supercomputers, thanks to the thousands of configurable features it supports. In principle, many relevant problems on configurable systems, such as completing a partial configuration to get the system instance that consumes the least energy or optimizes any other quality attribute, could be solved through exhaustive analysis of all configurations. However, configuration spaces are typically colossal and cannot be entirely computed in practice. Alternatively, configuration samples can be analyzed to approximate the answers. Generating those samples is not trivial since features usually have inter-dependencies that constrain the configuration space. Therefore, getting a single valid configuration by chance is extremely unlikely. As a result, advanced samplers are being proposed to generate random samples at a reasonable computational cost. However, to date, no sampler can deal with highly configurable complex systems, such as the Linux kernel. This paper proposes a new sampler that does scale for those systems, based on an original theoretical approach called extensible logic groups. The sampler is compared against five other approaches. Results show our tool to be the fastest and most scalable one.Publicación Group Decision-Making Based on Artificial Intelligence: A Bibliometric Analysis(MDPI, 2020) Heradio Gil, Rubén; Fernández Amoros, David José; Cobo, Manuel J.; Cerrada Collado, Cristina; https://orcid.org/0000-0002-7131-0482; https://orcid.org/0000-0001-6575-803XDecisions concerning crucial and complicated problems are seldom made by a single person. Instead, they require the cooperation of a group of experts in which each participant has their own individual opinions, motivations, background, and interests regarding the existing alternatives. In the last 30 years, much research has been undertaken to provide automated assistance to reach a consensual solution supported by most of the group members. Artificial intelligence techniques are commonly applied to tackle critical group decision-making difficulties. For instance, experts’ preferences are often vague and imprecise; hence, their opinions are combined using fuzzy linguistic approaches. This paper reports a bibliometric analysis of the ample literature published in this regard. In particular, our analysis: (i) shows the impact and upswing publication trend on this topic; (ii) identifies the most productive authors, institutions, and countries; (iii) discusses authors’ and journals’ productivity patterns; and (iv) recognizes the most relevant research topics and how the interest on them has evolved over the years.Publicación Event-based Control: A Bibliometric Analysis of Twenty Years of Research(IEEE, 2020-03-04) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Heradio Gil, Rubén; Chacón, Jesús; Vargas Oyarzún, Héctor; Sánchez, José; Sánchez Moreno, José; Dormido Canto, SebastiánThe potential benefits of networked control systems are tremendous, as they can be easily upgraded by just including new components (i.e., sensors, actuators, or controllers), avoiding any further modifications to their structure. A critical approach to unleash such potential benefits is event-based control, where the system output turns to be sampled on demand, instead of being sampled constantly at rigid periods of time. This paper analyzes from a bibliometric point of view the literature published for the last twenty years on event-based control, identifying the most relevant articles, authors, institutions, and journals. Moreover, the principal topics, motivations, and problems faced by the researchers are discussed, identifying distinct challenges and opportunities for future research.Publicación Uniform and scalable sampling of highly configurable systems(Springer, 2022-01-21) Galindo, José A.; Benavides, David; Batory, Don; Heradio Gil, Rubén; Fernández Amoros, David José; Heradio Gil, Rubén; Fernández Amoros, David JoséMany analyses on configurable software systems are intractable when confronted with colossal and highly-constrained configuration spaces. These analyses could instead use statistical inference, where a tractable sample accurately predicts results for the entire space. To do so, the laws of statistical inference requires each member of the population to be equally likely to be included in the sample, i.e., the sampling process needs to be “uniform”. SAT-samplers have been developed to generate uniform random samples at a reasonable computational cost. However, there is a lack of experimental validation over colossal spaces to show whether the samplers indeed produce uniform samples or not. This paper (i) proposes a new sampler named BDDSampler, (ii) presents a new statistical test to verify sampler uniformity, and (iii) reports the evaluation of BDDSampler and five other state-of-the-art samplers: KUS, QuickSampler, Smarch, Spur, and Unigen2. Our experimental results show only BDDSampler satisfies both scalability and uniformity.Publicación Finding Near-optimal Configurations in Colossal Spaces with Statistical Guarantees(Association for Computing Machinery (ACM), 2023-11-23) Oh, Jeho; Batory, Don; Heradio Gil, RubénA Software Product Line (SPL) is a family of similar programs. Each program is defined by a unique set of features, called a configuration, that satisfies all feature constraints. “What configuration achieves the best performance for a given workload?” is the SPLOptimization (SPLO) challenge. SPLO is daunting: just 80 unconstrained features yield 1024 unique configurations, which equals the estimated number of stars in the universe. We explain (a) how uniform random sampling and random search algorithms solve SPLO more efficiently and accurately than current machine-learned performance models and (b) how to compute statistical guarantees on the quality of a returned configuration; i.e., it is within x% of optimal with y% confidence.Publicación Circuit Testing Based on Fuzzy Sampling with BDD Bases(University of Hawaiʻi at Mānoa, 2023) Pinilla, Elena; Fernández Amoros, David José; Heradio Gil, RubénFuzzy testing of integrated circuits is an established technique. Current approaches generate an approximately uniform random sample from a translation of the circuit to Boolean logic. These approaches have serious scalability issues, which become more pressing with the ever-increasing size of circuits. We propose using a base of binary decision diagrams to sample the translations as a soft computing approach. Uniformity is guaranteed by design and scalability is greatly improved. We test our approach against five other state-of-the-art tools and find our tool to outperform all of them, both in terms of performance and scalability.Publicación A Rule-Learning Approach for Detecting Faults in Highly Configurable Software Systems from Uniform Random Samples(2022) Heradio Gil, Rubén; Fernández Amoros, David José; Ruiz Parrado, Victoria; Cobo, Manuel J.; https://orcid.org/0000-0003-2993-7705; http://orcid.org/ 0000-0001-6575-803XSoftware systems tend to become more and more configurable to satisfy the demands of their increasingly varied customers. Exhaustively testing the correctness of highly configurable software is infeasible in most cases because the space of possible configurations is typically colossal. This paper proposes addressing this challenge by (i) working with a representative sample of the configurations, i.e., a ``uniform'' random sample, and (ii) processing the results of testing the sample with a rule induction system that extracts the faults that cause the tests to fail. The paper (i) gives a concrete implementation of the approach, (ii) compares the performance of the rule learning algorithms AQ, CN2, LEM2, PART, and RIPPER, and (iii) provides empirical evidence supporting our procedurePublicación Scalable Hybrid Laboratories: Application in Industrial Automation(ELSEVIER, 2025-05-27) Vilches, Marco; Vargas, Héctor; Torre Cubillo, Luis de la; Heradio Gil, RubénSome of the most critical competencies that automation and control students must acquire to become capable engineers require hands-on laboratory expe- riences under conditions that closely resemble real-world work environments. However, current practical laboratories often face challenges in recreating re- alistic and scalable industrial contexts, making it difficult to develop these competencies. This article presents the development and implementation of a hybrid laboratory proposal to address these challenges. The prototype, de- signed for training automation engineers, integrates real control devices with simulated digital replicas of processes, allowing the scalability of the system to address a wide variety of industry-like scenarios. The general design, its physical and virtual implementation, the communication of its components, and the installation and operation context are detailed. The article concludes with the potential advantages and benefits of the hybrid laboratory from an academic teaching perspective, the training of industry professionals, and the technical optimization of the engineering problem addressed.