1571-0661
Published by: Elsevier
https://www.journals.elsevier.com/electronic-notes-in-theoretical-computer-science
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1116 | 9 | 7 | 1 |
The journal focuses largely on the fields of Programming language, Theoretical computer science, Discrete mathematics, Algorithm and Algebra. It investigates Programming language research which frequently intersects with Semantics. The studies on Theoretical computer science discussed can also contribute to research in the domains of Correctness and Graph rewriting.
Pure mathematics, Combinatorics and Calculus are some topics wherein Discrete mathematics research discussed in the journal have an impact. Operational semantics works presented in Electronic Notes in Theoretical Computer Science have a specific focus on Denotational semantics.
Programming language, Theoretical computer science, Discrete mathematics, Algorithm and Model checking are the main subjects of interest in the most cited articles. The journal papers investigate Programming language research which frequently intersects with Semantics. The most cited papers address concerns in Theoretical computer science which are intertwined with other disciplines, such as Probabilistic logic, Correctness, Graph rewriting and State (computer science).
The objective of Electronic Notes in Theoretical Computer Science is to combine knowledge in the areas of Algebra, Theoretical computer science, Programming language, Semantics (computer science) and Semantics. The studies in Algebra featured incorporate elements of Completeness (order theory) and Substitution (logic). The journal addresses concerns in the field of Theoretical computer science by exploring it in line with topics in Graph which intersect with Classifier (UML) subjects.
It emphasizes research on Programming language, which includes concerns such as Regression testing. It facilitates discussions on Semantics (computer science) that incorporate concepts from other fields like Object (computer science), Initialization, Selection algorithm and Equational logic. The research on Semantics tackled can also make contributions to studies in the areas of Vagueness, Fuzzy logic, Axiom, Differential equation and Regulation of gene expression.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Electronic Notes in Theoretical Computer Science (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Electronic Notes in Theoretical Computer Science (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2020 edition, 4.84% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 6.78% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.78% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.56% of all publications and 72.88% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
In the pursuit of theoretical and computer science studies, many have wondered about the potential career opportunities that come with attaining a high level of competency in these fields. The array of roles available is diverse and rewarding, offering individuals the chance to contribute to the body of knowledge in theoretical computer science, or to utilize these concepts in practical, innovative ways. For instance, many individuals have proceeded to become professors, conducting research and educating the next generation of theorists and scientists. Others have immersed themselves in industry, becoming software engineers or data scientists. These roles allow them to leverage the principles and methodologies inherent to theoretical computer science to create practical solutions for real-world problems. Some have specifically branched into specialized quarters, such as art education. For example, understanding the principles of programming language and algorithms could prove useful when teaching art in the digital era. An art teacher in Hawaii, for instance could benefit greatly from foundational knowledge in theoretical computer science. For more information on how to combine these areas of interest, discover more in this article about {anchor}, which discusses about how one can become an art teacher in Hawaii with a foundation in theoretical computer science studies. Ultimately, the career paths in theoretical computer science are as diverse as they are promising. Whether you choose to contribute to academia, industry, education or beyond, there is a place for theoretical computer science in virtually every field of work.
Linan Chen;Florence Clerc;Prakash Panangaden
(2020)Gordon D. Plotkin
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