The field of graph algorithms is moving towards developing more efficient solutions for complex problems. Recent research has focused on improving the time and space complexity of algorithms for problems such as Subset Sum, Single-Source Shortest Paths, and Eulerian Cycles. Notably, there has been significant progress in reducing the space complexity of algorithms while maintaining their time efficiency. Additionally, parameterized algorithms have been explored for problems like Spanning Tree Isomorphism and Isometric Path Partition, with a focus on treewidth and diameter as parameters. These advances have the potential to impact various applications of graph algorithms. Noteworthy papers include: Subset Sum in Near-Linear Pseudopolynomial Time and Polynomial Space, which answers two open questions affirmatively. Space-Efficient Hierholzer: Eulerian Cycles in O(m) Time and O(n) Space, which presents a simple variant of Hierholzer's algorithm with improved space efficiency. Parameterized Algorithms for Spanning Tree Isomorphism by Redundant Set Size, which achieves fixed-parameter tractability for both undirected and directed versions of the problem. Parameterized complexity of isometric path partition: treewidth and diameter, which proves W[1]-hardness when parameterized by treewidth and presents a tailored dynamic programming algorithm.