Systems Programming & Low-Level Concepts Questions

Systems programming concepts including memory management, pointers, memory layout, CPU architecture considerations, concurrency primitives, OS interactions, and performance optimization in low-level languages (C, C++). Covers how languages expose low-level resources, toolchains, and platform-specific behaviors; excludes high-level application development.

MediumTechnical

43 practiced

A binary file format is being parsed by the same C++ code on x86 servers and ARM-based test machines. One test only fails on ARM after someone rewrote the parser to cast a byte buffer directly to a struct. What would you inspect, and how would you make the parser safe across platforms?

Sample Answer

**I would inspect three things immediately: alignment, endianness, and object layout.** Casting a raw byte buffer to a struct is fragile because the file format and the C++ struct are not guaranteed to match. x86 often tolerates unaligned access, while ARM may fault or behave differently, which is why the bug can appear only on ARM.

**What I would check:**- Whether the struct has padding inserted by the compiler.- Whether the buffer address satisfies the struct's alignment requirements.- Whether the file format uses little-endian or big-endian byte order.- Whether the code violates strict aliasing by treating bytes as a different type.

**Concrete example:** if the file stores a 32-bit length as bytes `01 00 00 00`, that means `1` in little-endian. A direct struct cast assumes the host layout matches the file, but that is not safe across platforms.

**Safer approach:** parse fields from bytes explicitly, or copy bytes into fixed-width integers and convert them. For example:

cpp

bool parse_len(const unsigned char* b, std::uint32_t& len) {
    len = std::uint32_t(b[0]) |
          (std::uint32_t(b[1]) << 8) |
          (std::uint32_t(b[2]) << 16) |
          (std::uint32_t(b[3]) << 24);
    return true;
}

That keeps the parser portable, alignment-safe, and explicit about byte order.

MediumTechnical

51 practiced

A request-handling thread needs to read and update a small shared state object on every request. A mutex keeps the code simple, but latency is too high under load. How would you decide whether to keep the lock, change the data layout, or use a different synchronization strategy?

EasyTechnical

48 practiced

You're designing an in-memory index in C++ that stores millions of small objects. Some objects are short-lived, others stay alive for the entire process. How would you decide where to allocate them, and what trade-offs would matter most for latency, fragmentation, and cache locality?

MediumTechnical

56 practiced

A long-running service suddenly shows a large memory spike right after it forks a worker process, even though the child does very little work. What does the OS do in this situation, and what would you inspect to tell whether the spike is expected or a real problem?

HardTechnical

43 practiced

You have a hot loop that processes tens of millions of fixed-size records and spends most of its time on CPU, not I/O. If algorithmic complexity cannot change, what measurements and code changes would you consider to improve throughput?

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