World's Best Scientists 2026 revealed!
ACM Transactions on Programming Languages and Systems
H-index 10

ACM Transactions on Programming Languages and Systems

0164-0925

Published by: ACM

https://dl.acm.org/journal/toplas

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 557 41 43 10

Additional Metrics

Number of Best Scientists*: 44
Documents by Best Scientists*: 45
Top 100 Ranked Scientists*: 1
SCIMAGO H-index: 75
SCIMAGO SJR: 0.564
Impact Factor: 1.6

Overview

Top Research Topics at ACM Transactions on Programming Languages and Systems?

The aim of ACM Transactions on Programming Languages and Systems is to expand the discussion of research in Programming language, Theoretical computer science, Algorithm, Compiler and Parallel computing. The journal tackles issues in Programming language, particularly in the topics of Semantics (computer science), Correctness, Operational semantics, Java and Concurrency. The study on Theoretical computer science presented in it intersects with the topics under Program analysis.

ACM Transactions on Programming Languages and Systems centers on topics in Algorithm, with a focus on Time complexity. Discussions in ACM Transactions on Programming Languages and Systems are anchored in the subject of Compiler and the similar topic of Code generation. Cache is part of Parallel computing studies tackled in the journal.

It links adjacent topics like Abstract interpretation with Static analysis.

  • Programming language (47.73%)
  • Theoretical computer science (31.73%)
  • Algorithm (21.73%)

What are the most cited papers published in the journal?

  • The Byzantine Generals Problem (4419 citations)
  • Automatic verification of finite-state concurrent systems using temporal logic specifications (3252 citations)
  • Linearizability: a correctness condition for concurrent objects (2753 citations)

Research areas of the most cited articles at ACM Transactions on Programming Languages and Systems:

The published papers mainly deal with areas of study such as Programming language, Theoretical computer science, Algorithm, Compiler and Parallel computing. The journal papers dive deep in exploring the relationship between the study of Programming language and Code (cryptography). The works on Theoretical computer science tackled in the journal articles bring together disciplines like Mathematical proof and Operational semantics.

What topics the last edition of the journal is best known for?

  • Programming language
  • Operating system
  • Artificial intelligence

The previous edition focused in particular on these issues:

The scientific interests tackled in the journal are Programming language, Concurrency, Theoretical computer science, Component (UML) and Compiler. Some problems in Programming language that were presented in it overlapped with concepts under Abstraction (linguistics) and Information privacy. The journal facilitates discussions on Concurrency that incorporate concepts from other fields like Sequential consistency, Consistency model, x86, ARM architecture and Suite.

The Theoretical computer science study presented in the journal encompasses related topics like Reachability and also examines its connection to subjects such as Control theory. The journal addresses concerns in Component (UML) which are intertwined with other disciplines, such as Functional programming, Taint checking, Set (abstract data type), Software framework and Differential privacy. It explores topics in Compiler which can be helpful for research in disciplines like Memory corruption, Formal language, Syntax highlighting, Code (cryptography) and Compiled language.

The most cited articles from the last journal are:

  • Armed Cats: Formal Concurrency Modelling at Arm (1 citations)
  • On Polymorphic Sessions and Functions: A Tale of Two (Fully Abstract) Encodings (1 citations)
  • Polymorphic Iterable Sequential Effect Systems (1 citations)

Papers citation over time

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 ACM Transactions on Programming Languages and Systems (based on the number of publications) are:

  • Thomas Reps (17 papers) absent at the last edition,
  • Leslie Lamport (14 papers) absent at the last edition,
  • Peter J. Stuckey (10 papers) published 1 paper at the last edition,
  • Kathryn S. McKinley (9 papers) absent at the last edition,
  • Jens Palsberg (9 papers) absent at the last edition.

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 ACM Transactions on Programming Languages and Systems (based on the number of publications) are:

  • IBM (65 papers) absent at the last edition,
  • Carnegie Mellon University (39 papers) absent at the last edition,
  • Massachusetts Institute of Technology (37 papers) published 1 paper at the last edition,
  • University of Arizona (31 papers) absent at the last edition,
  • University of Wisconsin-Madison (30 papers) absent at the last edition.

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.

Publication chance based on affiliation

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 2021 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 21.43% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.43% of all publications and 57.14% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Prospects in Computer Science

For professionals dedicated to the field of Computer Science and Programming, the areas of research discussed in ACM Transactions offer promising career opportunities. These fields are burgeoning with advancements that hold potential for numerous career avenues. From becoming experts in Programming language, Theoretical computer science, Algorithm, Compiler, or Parallel computing to specializing in important concepts such as Time Complexity, Code Generation, or Cache, there are endless possibilities.

However, every career track requires certain qualifications. For instance, if you are interested in early childhood education and wish to become a {anchor}preschool teacher education requirements in maine, you would need a specific set of credentials and skills. Similarly, the field of computer science and programming also has its unique requirements. Having a basic understanding of computer systems, being proficient in one or more programming languages, and being familiar with algorithms and data structures are some of them. In addition, a degree in Computer Science or a related field is often necessary.

The future of Computer Science and Programming looks bright and promising, with ACM Transactions serving as a strong platform to disseminate cutting-edge research in these fields. For those interested and motivated, it's a promising path with a wealth of opportunity.

Top Publications

  • A Principled Approach to Selective Context Sensitivity for Pointer Analysis

    Yue Li;Tian Tan;Anders Møller;Yannis Smaragdakis

    (2020)
    41 Citations
  • Obsidian: Typestate and Assets for Safer Blockchain Programming

    Michael Coblenz;Reed Oei;Tyler Etzel;Paulette Koronkevich

    (2020)
    28 Citations
  • Passport: Improving Automated Formal Verification Using Identifiers

    (2022)
    22 Citations
  • TF-Coder: Program Synthesis for Tensor Manipulations

    (2022)
    17 Citations
  • An Extended Account of Trace-relating Compiler Correctness and Secure Compilation

    Carmine Abate;Roberto Blanco;Ştefan Ciobâcă;Adrien Durier

    (2021)
    15 Citations
  • CFLOBDDs: Context-Free-Language Ordered Binary Decision Diagrams

    (2022)
    15 Citations
  • Gradualizing the Calculus of Inductive Constructions

    (2022)
    14 Citations
  • Inferring Lower Runtime Bounds for Integer Programs

    Florian Frohn;Matthias Naaf;Marc Brockschmidt;Jürgen Giesl

    (2020)
    12 Citations
  • Securing Interruptible Enclaved Execution on Small Microprocessors

    (2021)
    11 Citations
  • Contextual Linear Types for Differential Privacy

    (2023)
    10 Citations

Related Online Degrees & Career Pathways

For students interested in expanding their knowledge beyond traditional Computer Science, there are several related online degrees that open diverse career pathways. For example, pursuing an online degree for mechanical engineering allows learners to explore the design and development of mechanical systems, which often intersects with software applications in robotics and automation.

If your interests lean toward the fundamental sciences, you may wonder, can you get a physics degree online? The answer is yes—several reputable institutions offer fully online physics programs, providing a strong foundation in analytical thinking and problem-solving that complements computing skills.

For those focused on data-driven roles, the cheapest data science course in the US can be an attractive option. Understanding what is the cheapest data science course in the us? helps students make informed choices about affordable yet high-quality education in data analysis, machine learning, and statistical modeling.

Additionally, online electrical engineering courses USA offer exciting opportunities for students passionate about circuit design, embedded systems, and electronic communications. These fields complement computer science skills and expand career prospects in tech industries.

Best Scientists Contributing to This Journal

Recently Published Articles