The field of graph theory and algorithms is witnessing significant developments, with a focus on understanding the complexity of Boolean functions and improving algorithms for graph problems. Researchers are exploring new measures of complexity, such as disjunctive complexity, and comparing them with existing measures like space complexity and nondeterministic branching programs. These efforts have led to a deeper understanding of the relationships between different complexity measures and the development of new algorithms with improved performance guarantees. Notably, there have been breakthroughs in the study of minor-free graphs, including the resolution of long-standing open questions and the development of new techniques for analyzing graph structures. Furthermore, advances in distributed algorithms and counting complexity have enabled the design of faster and more efficient algorithms for solving graph problems. Noteworthy papers include:

• A study introducing a generalization of streaming algorithms that captures the full power of disjunctive complexity, and a phenomenon of uniformly hard functions.
• A paper proving that the shortest path metric of every K_r-minor-free graph has a padding parameter of O(log r), resolving a long-standing open question.