Computer-assisted graph theory: a survey

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Paper Summary

Conflicts of Interest

Identified Weaknesses

Rating Explanation

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Paper Summary

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Graph Theory Gets a Computer Upgrade: Algorithms and Databases Help Mathematicians Find Patterns

This survey paper explores how computers and algorithms are transforming graph theory research. It covers methods for generating graphs, analyzing their properties using databases and invariants, and applying techniques like linear programming, SAT solvers, and machine learning. The authors also present some smaller, new results obtained using computer-assisted methods.

Possible Conflicts of Interest

None identified

Identified Weaknesses

Limited Scope

This paper primarily focuses on the computer science aspects of graph theory, not the practical applications. It does not delve deep into the specific real-world problems that these techniques could solve.

Lack of Contextualization

Although the new results are interesting, their practical significance and broader implications within graph theory are not fully explored or explained.

Lack of Novel Research

The paper is a survey of existing techniques, so it does not present original research or novel methodological contributions.

Rating Explanation

This survey is a comprehensive overview of computer-assisted techniques in graph theory. It covers many different approaches, provides clear examples, and even showcases some new findings obtained using these techniques. Although it lacks novel research and has a limited scope, its thoroughness and informative nature make it a valuable resource. It promotes a useful approach that could accelerate progress in graph theory.

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