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ACM Transactions on Algorithms

The ACM Transactions on Algorithms (TALG) is a prestigious peer-reviewed scientific journal focusing on the domain of algorithms. This journal is published by the Association for Computing Machinery (ACM), a key organization in the realm of computing and information technology. TALG has been disseminating high-quality research since its inaugural issue in 2005.

Purpose and Scope

TALG is dedicated to publishing original research papers that are centered on algorithms which are inherently discrete and finite. The journal emphasizes algorithms that incorporate mathematical content either in their objectives or through analytical processes. Contributions to the journal typically include the development of new algorithms, data structures, improved analyses, and novel complexity results.

Editorial Leadership

The journal has benefited from excellent editorial leadership over the years. Notably, Aravind Srinivasan served as the Editor-in-Chief from 2014 to 2020. During his tenure, the journal maintained its reputation for academic rigor and scholarly excellence.

Open Access Policy

ACM is fully committed to providing open access to all its publications, including TALG. This shift towards open access ensures that cutting-edge research is accessible to a wider audience, promoting greater dissemination of knowledge. Authors are provided with information on article processing charges (APC) and potential waivers or discounts.

Peer Review and Authorship

The ACM has implemented an updated Peer Review Policy, ensuring that the research published meets the highest standards of academic integrity. Additionally, a new Policy on Authorship addresses key issues, including the appropriate use of generative AI tools.

Related Journals and Fields

The ACM Transactions on Algorithms is part of a broader collection of journals under ACM, each focusing on different aspects of computing and information science. Related journals include:

The journal is essential for those involved in theoretical computer science and is closely aligned with research areas covered by the ACM's Special Interest Group on Algorithms and Computation Theory (SIGACT).

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