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I knew the amortized O(1) answer but fumbled a bit when they pushed on the growth factor specifics.
Start by defining amortized and worst-case complexities for push_back, then explain the capacity growth strategy and its implications for reallocation. Detail the move vs. copy semantics during reallocation and the invalidation of iterators and references, using a concrete example to illustrate.
Pro tip: Mention that the growth factor is implementation-defined but typically 1.5x or 2x, and that this choice balances memory usage and performance; also note that move semantics are used only if the move constructor is noexcept, otherwise copy is used for strong exception safety.
State that push_back has amortized O(1) time complexity and worst-case O(n) when reallocation occurs.
Describe how vector doubles (or grows by a factor) its capacity when size equals capacity, involving allocation of new memory and deallocation of old.
Explain that during reallocation, existing elements are moved (if move constructor is noexcept) or copied to the new memory, and the old elements are destroyed.
Emphasize that reallocation invalidates all iterators, pointers, and references to elements; even without reallocation, insertions may invalidate the end iterator.
Provide a concrete example (e.g., pushing 1,000,000 elements) to illustrate the amortized constant time and the occasional O(n) cost.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by explaining that unordered_map is a hash table with separate chaining, then systematically cover the hashing mechanism, bucket array, collision handling, load factor and rehashing, iterator/reference invalidation rules, and time complexity guarantees. Emphasize that average-case operations are O(1) but worst-case is O(n), and mention that rehashing invalidates iterators but not references/pointers to elements.
Pro tip: Mention that in libstdc++ (GCC), unordered_map uses a singly-linked list of all elements and buckets point into that list, so iterators remain valid across rehashing except for erased elements—this shows deep implementation knowledge that impresses trading firms.
Explain that unordered_map uses a hash function (std::hash) to map keys to bucket indices, and the bucket array is typically a vector of pointers to nodes. Mention that the number of buckets is usually a prime number to reduce collisions.
Describe separate chaining: each bucket contains a linked list of all elements that hash to that bucket. In libstdc++, all elements are in a single forward list, and buckets point to the first node in their chain.
Define load factor as size()/bucket_count(). When it exceeds max_load_factor (default 1.0), rehashing occurs: a new bucket array (usually roughly double the size, next prime) is allocated, and all elements are rehashed into it.
Rehashing invalidates all iterators but does not invalidate references or pointers to elements. Insertion invalidates iterators only if rehashing occurs; erasure invalidates only iterators to the erased element.
Average-case: insert, find, erase are O(1). Worst-case: O(n) due to collisions. Rehashing takes O(n) time. Mention that these are average-case guarantees, not worst-case.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Felt like the most open-ended of the three.
Start by defining virtual functions and their role in runtime polymorphism, then explain the vtable/vptr mechanism and associated overheads. Next, cover the necessity of virtual destructors and contrast dynamic polymorphism with template-based static polymorphism, highlighting trade-offs in performance, flexibility, and code size.
Pro tip: Emphasize that in latency-sensitive systems like trading, static polymorphism is often preferred to avoid vtable overhead, but dynamic polymorphism remains valuable for extensibility; mention that final classes and devirtualization can mitigate costs.
Explain that virtual functions enable runtime polymorphism by allowing derived classes to override base class behavior, and that dynamic dispatch resolves the correct function at runtime based on the object's actual type.
Describe how each class with virtual functions has a vtable (array of function pointers) and each object contains a hidden vptr pointing to its class's vtable; dynamic dispatch involves dereferencing the vptr to call the appropriate function.
Detail the runtime overhead (indirection, potential cache misses, inability to inline) and memory overhead (vptr per object, vtable per class), and note that these costs are per-object and per-call.
Explain that a virtual destructor ensures the correct destructor is called when deleting a derived object through a base pointer, preventing undefined behavior and resource leaks.
Contrast dynamic polymorphism with templates (static polymorphism), which resolve at compile time, eliminate vtable overhead, enable inlining, but increase code size and reduce flexibility for runtime polymorphism.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.