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Advanced Information Systems: Novel Techniques and Data-Driven Solutions

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (16 June 2026) | Viewed by 591

Editors


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Guest Editor
Department of Computer and Telematic System Engineering, University of Extremadura, Av. De la Universidad s/n., 10004 Cáceres, Spain
Interests: software engineering; quantum computing; smart systems; UAVs
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Computer and Telematic System Engineering, University of Extremadura, 10004 Cáceres, Spain
Interests: software engineering; machine learning; computing continuum; digital twins

Special Issue Information

Dear Colleagues,

The rapid evolution of digital technologies, the proliferation of data-intensive applications, and the growing demand for intelligent, adaptive, and scalable solutions have transformed the landscape of modern information systems. Today’s systems must integrate advanced algorithms, heterogeneous data sources, high-performance computing infrastructures, and real-time decision-making capabilities. This Special Issue, “Advanced Information Systems: Novel Techniques and Data-Driven Solutions”, aims to highlight the latest theoretical developments, practical methodologies, and innovative applications that push the boundaries of how information systems are designed, optimized, and deployed.

The focus of this Special Issue is on cutting-edge architectures, models, and computational approaches that enable next-generation information systems. This includes algorithmic advances, data-centric strategies, and intelligent frameworks that enhance automation, efficiency, security, and interoperability.

The scope spans a wide range of topics, including, but not limited to, data engineering, machine learning-driven systems, distributed and cloud infrastructures, real-time analytics, cybersecurity solutions, human–computer interaction, quantum computing, and domain-specific intelligent platforms. We welcome contributions that address theoretical foundations, system-level innovations, emerging technologies, and multidisciplinary applications in fields such as healthcare, Industry 4.0, transportation, smart cities, and digital services.

The purpose of the Special Issue is to provide an integrated view of how novel computational techniques and data-driven paradigms are reshaping the capabilities of information systems. By bringing together research from academia and industry, this collection seeks to foster dialogue, highlight cross-disciplinary approaches, and inspire future innovations.

Dr. Enrique Moguel
Dr. Sergio Laso
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced information systems
  • data-driven solutions
  • intelligent computing
  • machine learning and AI
  • big data analytics
  • distributed systems
  • real-time decision making
  • system architectures
  • quantum computing
  • cybersecurity
  • smart applications

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Published Papers (1 paper)

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Research

21 pages, 440 KB  
Article
Feedback-Driven SQL Optimization with Validated Query Rewrites
by Martin Kostov and Kalinka Kaloyanova
Electronics 2026, 15(13), 2931; https://doi.org/10.3390/electronics15132931 - 3 Jul 2026
Viewed by 91
Abstract
Cost-based query optimizers are essential for relational database systems, but SQL formulation can still affect selected execution plans and runtime, especially in recurring analytical workloads and machine-generated queries. This paper proposes a feedback-driven lifecycle for SQL optimization, based on empirically validated query rewrites. [...] Read more.
Cost-based query optimizers are essential for relational database systems, but SQL formulation can still affect selected execution plans and runtime, especially in recurring analytical workloads and machine-generated queries. This paper proposes a feedback-driven lifecycle for SQL optimization, based on empirically validated query rewrites. The contribution of the presented approach is a persistent candidate-management process that covers the path from candidate intake to provenance recording, structural admissibility checks, empirical result-equivalence validation, paired runtime evidence, guarded activation, retention, rejection, and later deactivation. Candidate rewrites may come from deterministic rules, local large language models, manual alternatives, or external rewrite systems; the source is recorded but does not determine acceptance. The evaluation uses a controlled research implementation with deterministic-rule cases, repeated TPC-H SF1 runs, a real-world-style anti-pattern corpus, and JOB/IMDB. The results show conservative behavior on mature analytical templates, including mostly withheld TPC-H candidates with one held-out positive case, stable evidence for selected anti-patterns, and comparable but non-identical JOB/IMDB positives across runs. The findings support a source-neutral lifecycle in which alternative SQL formulations are admitted, measured, retained, activated, or rejected according to accumulated evidence rather than the generating mechanism. Full article
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