Authors are invited to submit an extended abstract of no more than 12 pages, excluding references and the front page(s) (authors, affiliation, keywords, abstract, ...), presenting original research on the theory of computer science. All submissions must be formatted in the LIPIcs style and submitted via Easychair to the appropriate track of the conference, using the following link:

https://easychair.org/conferences/?conf=icalp2020

The use of pdflatex and the LIPIcs style are mandatory: papers that deviate significantly from the required format may be rejected without consideration of merit.

No prior publication and no simultaneous submission to other publication outlets (either a conference or a journal) is allowed.

Technical details necessary for a proper scientific evaluation of a submission must be included in the 12-page submission or in a clearly labelled appendix, to be consulted at the discretion of program committee members. Authors are strongly encouraged to also make full versions of their submissions freely accessible in an on-line repository such as ArXiv, HAL, ECCC.

According to the ICALP policy, for every accepted paper it is required that at least one author attends the meeting and delivers the talk. The paper may be excluded from the proceedings if none of the authors attends the conference.


Best Paper Awards


As in previous editions of ICALP, there will be best paper and best student paper awards for each track of the conference. In order to be eligible for a best student paper award, a paper should be authored only by students and should be marked as such upon submission.


Topics


Papers presenting original research on all aspects of theoretical computer science are sought. Typical but not exclusive topics of interest are:
Track A (Algorithms, Complexity and Games)


Algorithmic Aspects of Networks and Networking

Algorithms for Computational Biology

Algorithmic Game Theory

Combinatorial Optimization

Combinatorics in Computer Science

Computational Complexity

Computational Geometry

Computational Learning Theory

Cryptography

Data Structures

Design and Analysis of Algorithms

Foundations of Machine Learning

Foundations of Privacy, Trust and Reputation in Network

Network Models for Distributed Computing

Network Economics and Incentive-Based Computing Related to Networks

Network Mining and Analysis

Parallel, Distributed and External Memory Computing

Quantum Computing

Randomness in Computation

Theory of Security in Networks


Track B (Automata, Logic, Semantics and Theory of Programming)


Algebraic and Categorical Models

Automata, Games, and Formal Languages

Emerging and Non-standard Models of Computation

Databases, Semi-Structured Data and Finite Model Theory

Formal and Logical Aspects of Learning

Logic in Computer Science, Theorem Proving and Model Checking

Models of Concurrent, Distributed, and Mobile Systems

Models of Reactive, Hybrid and Stochastic Systems

Principles and Semantics of Programming Languages

Program Analysis and Transformation

Specification, Verification and Synthesis

Type Systems and Theory, Typed Calculi