Persona: Heradio Gil, Rubén
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Heradio Gil
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Rubén
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Publicación Pragmatic Random Sampling of the Linux Kernel: Enhancing the Randomness and Correctness of the conf Tool(Association for Computing Machinery, New York, 2024-09-02) Fernández Amoros, David José; Heradio Gil, Rubén; Horcas Aguilera, Jose Miguel; Galindo, José A.; Benavides, David; Fuentes, Lidia; https://orcid.org/0000-0003-3758-0195; https://orcid.org/0000-0002-5677-7156; https://orcid.org/0000-0002-8449-3273; https://orcid.org/0000-0001-9293-9784The configuration space of some systems is so large that it cannot be computed. This is the case with the Linux Kernel, which provides almost 19,000 configurable options described across more than 1,600 files in the Kconfig language. As a result, many analyses of the Kernel rely on sampling its configuration space (e.g., debugging compilation errors, predicting configuration performance, finding the configuration that optimizes specific performance metrics, etc.). The Kernel can be sampled pragmatically, with its built-in tool conf, or idealistically, translating the Kconfig files into logic formulas. The pros of the idealistic approach are that it provides statistical guarantees for the sampled configurations, but the cons are that it sets out many challenging problems that have not been solved yet, such as scalability issues. This paper introduces a new version of conf called randconfig+, which incorporates a series of improvements that increase the randomness and correctness of pragmatic sampling and also help validate the Boolean translation required for the idealistic approach. randconfig+ has been tested on 20,000 configurations generated for 10 different Kernel versions from 2003 to the present day. The experimental results show that randconfig+ is compatible with all tested Kernel versions, guarantees the correctness of the generated configurations, and increases conf’s randomness for numeric and string options.Publicación A bibliometric analysis of off-line handwritten document analysis literature (1990–2020)(Elsevier, 2022-05) Ruiz Parrado, Victoria; Vélez, José F.; Heradio Gil, Rubén; Aranda Escolástico, Ernesto; Sánchez Ávila, ÁngelProviding computers with the ability to process handwriting is both important and challenging, since many difficulties (e.g., different writing styles, alphabets, languages, etc.) need to be overcome for addressing a variety of problems (text recognition, signature verification, writer identification, word spotting, etc.). This paper reviews the growing literature on off-line handwritten document analysis over the last thirty years. A sample of 5389 articles is examined using bibliometric techniques. Using bibliometric techniques, this paper identifies (i) the most influential articles in the area, (ii) the most productive authors and their collaboration networks, (iii) the countries and institutions that have led research on the topic, (iv) the journals and conferences that have published most papers, and (v) the most relevant research topics (and their related tasks and methodologies) and their evolution over the years.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 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.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 Teaching Automation with Factory I/O under a Competency-Based Curriculum(Springer, 2022-10-22) Vargas Oyarzún, Héctor; Heradio Gil, Rubén; Donoso, Matias; Farias, GonzaloSome of the most critical competencies students need to acquire to become control engineers require performing practices under actual industrial conditions. This means that they must not only master the theoretical aspects of the discipline but also acquire skills and attitudes to face unpredictable real-world situations. Software tools such as Matlab/Simulink are widely used to train the design and validation of controllers, but they fail to provide real industrial contexts. Nowadays, there are 3D simulation tools that support recreating industrial environments to a remarkable extent, making them very attractive for university courses. Nevertheless, their application in engineering courses is scarce yet. This paper presents a methodological framework for seizing into competency-based courses one of these simulation tools, called Factory I/O. Our approach was evaluated in a master’s course on Industrial PID Control at Pontifical Catholic University of Valparaíso (PUCV) in Chile. The evaluation comprised the qualitative analysis of students’ grades over four consecutive course editions and the qualitative study of students’ opinion on Factory I/O educational value. The objectives of our evaluation were (i) testing if Factory I/O helped students develop skills hard to practice in academic contexts, such as detecting faults or recognizing the importance of having well-defined operation protocols; (ii) validating our methodology for competency-based courses; and (iii) surveying our students about Matlab/Simulink and Factory I/O strengths/weaknesses to teach control engineering. According to the results, (a) Factory I/O complements Simulink by providing an adequate virtual environment to learn the aforementioned skills; and (b) our methodology supports courses’ continuous improvement through the statistical analysis of students’ achievements at different abstraction levels.Publicación A bibliometric analysis of 10 years of research on symptom networks in psychopathology and mental health(Elsevier, 2022-02) Ausín, Berta; Castellanos, Miguel Ángel; González Sanguino, Clara; Heradio Gil, RubénPsychopathology networks consist of aspects (e.g., symptoms) of mental disorders (nodes) and the connections between those aspects (edges). This article aims to analyze the research literature on network analysis in psychopathology and mental health for the last ten years. Statistical descriptive analysis was complemented with two bibliometric techniques: performance analysis and co-word analysis. There is an increase in publications that has passed from 1 article published in 2010 to 172 papers published in 2020. The 398 articles in the sample have 1,910 authors in total, being most of them occasional contributors. The Journal of Affective Disorders is the one with the highest number of publications on network analysis in psychopathology and mental health, followed by the Journal of Abnormal Psychology and Psychological Medicine stand out. The present study shows that this perspective in psychopathology and mental health is a recent field of study, but with solid advances in recent years from a wide variety of researchers, mainly from USA and Europe, who have extensively studied symptom networks in depression, anxiety, and post-traumatic stress disorders. However, gaps are identified in other psychological behaviors such as suicide, populations such as the elderly, and gender studies.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.