Model the symbol expressions as a directed graph where each symbol points to its dependencies, then perform a topological sort or DFS with memoization to resolve values in dependency order. Detect cycles to handle invalid expressions and return an error or default value.
Pro tip: Clarify with the interviewer whether the graph is guaranteed acyclic and whether symbols can have multiple expressions; this shows you think about edge cases and real-world data quality.
Parse the map of symbol expressions into a graph representation, where each symbol is a node and edges represent dependencies on other symbols.
Use DFS with a recursion stack or topological sort to detect cycles; if a cycle exists, handle it by returning an error or a sentinel value.
Perform a topological sort or DFS with memoization to compute each symbol's value in dependency order, caching results to avoid redundant work.
Consider symbols with no dependencies (base cases), missing symbols, and expressions that reference undefined symbols; decide on appropriate error handling.
Discuss time and space complexity: O(V+E) for graph traversal, where V is number of symbols and E is number of dependencies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.