Why is appending to a vector cheap on average despite copying?

A strong answer

A strong candidate frames Why is appending to a vector cheap on average despite copying? around the exact memory layout, compiler semantics, and hardware execution model covered in How a Vector Grows: Size, Capacity and Reallocation. Explain size versus capacity, doubling growth, and why references expire on reallocation.

A vector can grow whenever you call push_back. But its elements form one contiguous block of memory, and a block cannot always be stretched, because the memory right after it may belong to something else. So what does the vector do when the block is full? And if the answer involves copying everything to a bigger block, how can appending a million items be fast?

Size and capacity. The size of a vector is the number of elements it holds. Its capacity is the number of elements the current buffer can hold before it must be replaced. The elements at indexes from 0 up to but not including the size are real. The slots after them are raw, unused memory. The first two cells of the trace show both numbers, and you can read them with size() and capacity().

In a production interview, always connect the specification rule to its concrete runtime consequence: state what lives on the stack versus the heap or static storage segment, how the compiler or operating system validates alignments, lifetimes, and error codes, and what happens under adversarial or boundary inputs (such as zero-length buffers, integer overflow, concurrent mutation, or partial I/O). Backing your explanation with a small trace of register/memory state transitions immediately separates senior systems engineers from candidates who only memorized syntax.

What the interviewer is listening for

• Mastery of core invariant: Distinguish a vector's size from its capacity and trace push_back through a reallocation.
• Mastery of core invariant: Explain why geometric growth gives amortized constant-time appends.
• Mastery of core invariant: Predict which pointers, references and iterators become invalid after an operation.
• Hardware and ABI awareness: Explaining how sizes, alignments, calling conventions, or kernel boundaries behave on real 64-bit targets rather than relying on implementation-defined assumptions.
• Defensive engineering: Naming the exact compiler flags (-Wall -Wextra -Werror), static analyzers, or runtime sanitizers (-fsanitize=address,undefined,thread) that verify correctness in CI.

Common mistakes

• Explaining only surface syntax without tracing the underlying memory addresses, ownership lifetime, or kernel/user-space state transitions.
• Assuming undefined behavior (such as signed overflow, uninitialized reads, strict-aliasing violations, or dangling pointers) will "just work" because it passed an unoptimized -O0 debug build.
• Ignoring return codes, partial reads/writes, alignment padding, or cleanup paths when an allocation or syscall fails midway through a function.