DoorDash Entry-Level Embedded Developer Interview Preparation Guide

Approach

• Use volatile pointers to memory-mapped registers.
• Use bit masks for pin 3 (bit 3).
• Do a read-modify-write for DIR and PULLUP to avoid altering other pins.
• Return logical 0/1 from GPIO_IN masked and shifted.

#include <stdint.h>

#define GPIO_DIR_ADDR     ((volatile uint32_t *)0x40000000)
#define GPIO_PULLUP_ADDR  ((volatile uint32_t *)0x40000004)
#define GPIO_IN_ADDR      ((volatile uint32_t *)0x40000008)

#define PIN3_MASK         (1U << 3)

/* Configure pin 3 as input with pull-up enabled and return its value (0 or 1) */
static inline int read_pin3_with_pullup(void)
{
    /* Set as input: clear bit in DIR (1 = output, 0 = input) */
    uint32_t dir = *GPIO_DIR_ADDR;
    dir &= ~PIN3_MASK;
    *GPIO_DIR_ADDR = dir;

    /* Enable pull-up: set bit in PULLUP register */
    uint32_t pu = *GPIO_PULLUP_ADDR;
    pu |= PIN3_MASK;
    *GPIO_PULLUP_ADDR = pu;

    /* Read pin value, return 0 or 1 */
    return ( ( *GPIO_IN_ADDR & PIN3_MASK ) ? 1 : 0 );
}

Why volatile and RMW

• volatile prevents compiler optimizations that could cache register values or reorder accesses; required for hardware registers.
• Read-modify-write preserves other pins' configuration.
• Using explicit masks keeps code clear and safe for concurrent peripheral usage.

Situation & goal
Design a robust RTOS watchdog strategy that detects stuck/livelocked tasks, minimizes false positives for legitimate blocking (I/O, network), and supports graded recovery (task restart, log capture, system reset).

Per-task heartbeat design

• Each critical task obtains a small heartbeat structure:
  • task_id, last_beat_timestamp, allowed_block_ms, state_mask (RUNNING/WAIT_IO/SUSPENDED).
• Task calls heartbeat_kick(task_id) at safe checkpoints (loop iteration, state transition).
• For blocking waits, tasks set state_mask = WAIT_IO and call heartbeat_pause(task_id, expected_block_ms) before blocking; on wake, call heartbeat_resume(task_id).

Central watchdog petting policy

• A supervisory Watchdog Manager task runs at interval T_check (e.g., 100 ms).
• It scans heartbeats and computes:
  • if state == RUNNING and now - last_beat > run_threshold → mark unhealthy
  • if state == WAIT_IO and now - last_beat > allowed_block_ms + hysteresis → mark unhealthy
• Only if no tasks unhealthy for a short quiescent window and system health overall ok does the manager pet the hardware watchdog.

Allowed blocking periods

• Per-task allowed_block_ms set per task class (e.g., sensor read 50 ms, network 5s).
• Use conservative defaults + dynamic extension: tasks can request heartbeat_extend(extra_ms) with quota tracking to avoid abuse.

Recovery actions (graded)

• First detection → capture context: task backtrace, CPU registers, minimal ring log (use lockless single-writer buffer), increment fault counter.
• Attempt soft recovery: signal task to restart via RTOS API (vTaskDelete + vTaskCreate / safe restart function). If task restart succeeds → resume.
• If repeated failures or multiple critical tasks fail → escalate: stop petting watchdog to force system reset, or call platform-appropriate system_reset().
• Always persist minimal fault summary to nonvolatile storage when possible before reset.

Implementation notes (practical)

• Use RTOS hooks (task notify, idle hook) and low-overhead atomic operations for heartbeat updates.
• Keep heartbeat update cheap (single atomic store of timestamp).
• Protect manager scan with priority above typical tasks but below interrupts.
• Example heartbeat API (C):

// lightweight API
void heartbeat_kick(uint8_t task_id);            // update timestamp, state RUNNING
void heartbeat_pause(uint8_t task_id, uint32_t ms); // set WAIT_IO and allowed_block_ms
void heartbeat_resume(uint8_t task_id);          // set RUNNING

Trade-offs & safeguards

• Hysteresis and multiple-sample confirmation reduce false positives.
• Quotas for extensions prevent misbehaving tasks from disabling watchdog.
• Keep hardware watchdog petting decision centralized to avoid tasks accidentally starving reset.

This approach balances detection sensitivity with flexibility for legitimate blocking, provides graded recovery, and keeps runtime overhead minimal for embedded constraints.

High-level summary
Metastability and input jitter require trade-offs between reliability, latency and CPU. Below I list common software-level mitigations, their costs, and a testing plan to estimate MTBF for your target.

Mitigations (what, why, cost)

• Double-flop synchronizer (2-stage FF): simple, industry standard for single-bit crossing. Latency = 2 clock cycles; CPU cost = none (hardware flip-flops). Reduces metastability escape probability by giving extra resolve time.
• Multi-stage synchronizer (3+ FFs): further reduces failure probability exponentially; latency = N cycles; CPU cost = none.
• Oversampling (sample input multiple times per bit using software/GPIO interrupts or ADC): increases robustness to narrow glitches and jitter. Latency = depends on sample window (often tens–hundreds µs); CPU cost = high if polling; moderate if using DMA + timer.
• Majority voting (N samples, take majority): works with oversampling; extra memory/CPU to collect and compute majority; latency = sampling window length + compute (very small).
• Hysteresis / Schmitt-trigger inputs: analog front-end reduces noise-induced transitions; latency = negligible; CPU cost = none if hardware; software equivalent = require stable run-length before accept (debounce) — increases latency and CPU if polled.

Trade-offs summary

• Hardware FFs: minimal CPU, fixed latency (clock cycles).
• Software oversampling/majority: flexible but high CPU and higher latency; good for low-rate signals.
• Hysteresis/debounce: low CPU (if implemented in hardware); increases detection time.

MTBF estimation (design tests + extrapolation)

1. Controlled stress: use FPGA or signal generator to create asynchronous transitions at controlled rates and adjustable timing relative to destination clock; inject worst-case pulses and jitter.
2. Measure failure rate: run long-duration tests counting corrupted captures. Vary synchronizer resolve time (extra wait cycles) or sampling window.
3. Fit exponential model to observed failure rate to extract device/time constant and constant K:

MTBF = e^(T_res / tau) / (f_input * f_clock * K)

Plain-English: increasing resolve time T_res exponentially increases MTBF; f_input and f_clock scale collision opportunities.
4. Extrapolate to field conditions using measured f_input, f_clock and fitted tau, K. Include confidence intervals and run time sufficient to observe >10 failures for statistical validity or use accelerated stressing to get failures faster.
5. Practical checks: use oscilloscope to capture ambiguous transitions, validate with multiple input patterns, and combine hardware (Schmitt) + 2-stage sync + optional software debounce for high-assurance.

Notes: document assumptions (clock domains, measured jitter), include safety margins (design for MTBF >> expected device lifetime).

Approach

A byte-by-byte memcpy on a microcontroller unit (MCU) with a 32-bit bus issues one bus transaction per byte. Each transaction pays the same fixed overhead (address setup plus wait states) whether it moves 1 byte or 4, so a byte loop is using at most a quarter of the bus's real capacity per transfer. The fix is to move data 4 bytes (one word) at a time whenever alignment allows, and fall back to byte copies only for the unaligned edges.

Cortex-M4 cores generally have no data cache (that shows up on Cortex-M7 and above), so this optimization is not about cache locality at all. It is purely about cutting the number of bus transactions. Some silicon (e.g. ST's ART Accelerator) adds a flash prefetch buffer, but that speeds up instruction fetch from flash, not this data copy.

Alignment matters, though not for the reason it's easy to assume. Cortex-M0/M0+ (ARMv6-M) parts always fault on an unaligned word or halfword access, there's no way to enable support for it. Cortex-M3/M4/M7 (ARMv7-M), the family named in this question, are different: by default (the CCR.UNALIGN_TRP bit is 0 at reset) a single-register LDR/STR to an unaligned address is handled transparently in hardware, it does not fault, it just costs extra bus cycles for the split access. A project can set UNALIGN_TRP to make the M4 trap on unaligned accesses instead, and multi-register transfers (LDM/STM) and exclusive accesses (LDREX/STREX) fault on misalignment regardless of that bit's setting. So on the Cortex-M4 in this question, the naive byte loop wasn't faulting, it was just slow, one bus transaction per byte; the word-aligned implementation below is still the right call, because it avoids the extra per-access bus cycles unaligned hardware accesses cost, and it stays correct if this code is ever reused on an M0/M0+ part or built with UNALIGN_TRP set. It word-aligns the destination first with a byte-wise prefix, does the bulk of the copy as words, then mops up a trailing partial word byte-by-byte. If the source and destination have different alignment offsets relative to each other, no single shift makes both word-aligned at once, so it has to fall back to a safe byte copy for that case.

#include <stdint.h>
#include <stddef.h>
#include <stdio.h>
#include <string.h>

void *fast_memcpy(void *dst, const void *src, size_t n) {
    uint8_t *d = (uint8_t *)dst;
    const uint8_t *s = (const uint8_t *)src;

    /* Different alignment offsets: can't word-align both, use safe byte copy. */
    if (((uintptr_t)d & 3) != ((uintptr_t)s & 3)) {
        while (n--) *d++ = *s++;
        return dst;
    }

    /* Byte-copy the unaligned prefix until dst is 4-byte aligned. */
    while (((uintptr_t)d & 3) != 0 && n > 0) {
        *d++ = *s++;
        n--;
    }

    /* Bulk-copy full words: 1 bus transaction per 4 bytes instead of 1 per byte. */
    uint32_t *d32 = (uint32_t *)d;
    const uint32_t *s32 = (const uint32_t *)s;
    size_t words = n / 4;
    while (words--) *d32++ = *s32++;

    /* Byte-copy the trailing remainder. */
    d = (uint8_t *)d32;
    s = (const uint8_t *)s32;
    n = n % 4;
    while (n--) *d++ = *s++;

    return dst;
}

#define BUF_LEN 64

static int run_case(const char *name, size_t src_off, size_t dst_off, size_t n) {
    uint8_t backing_src[BUF_LEN + 8];
    uint8_t ref[BUF_LEN + 8];
    uint8_t got[BUF_LEN + 8];

    for (size_t i = 0; i < sizeof(backing_src); i++) backing_src[i] = (uint8_t)(i * 37 + 11);
    memset(ref, 0xAA, sizeof(ref));
    memset(got, 0xAA, sizeof(got));

    memcpy(ref + dst_off, backing_src + src_off, n);
    fast_memcpy(got + dst_off, backing_src + src_off, n);

    int match = memcmp(ref, got, sizeof(ref)) == 0;
    printf("%-28s src_off=%zu dst_off=%zu n=%2zu -> %s\n",
           name, src_off, dst_off, n, match ? "MATCH" : "MISMATCH");
    return match;
}

int main(void) {
    int all_ok = 1;
    all_ok &= run_case("aligned/aligned",            0, 0, 23);
    all_ok &= run_case("matching-offset unaligned a", 1, 1, 23);
    all_ok &= run_case("matching-offset unaligned b", 2, 2, 23);
    all_ok &= run_case("mismatched offsets",          1, 2, 23);
    all_ok &= run_case("zero length",                 0, 0, 0);
    all_ok &= run_case("shorter than one word",        0, 0, 3);
    printf("all cases matched standard memcpy: %s\n", all_ok ? "yes" : "no");
    return 0;
}

Output

aligned/aligned              src_off=0 dst_off=0 n=23 -> MATCH
matching-offset unaligned a  src_off=1 dst_off=1 n=23 -> MATCH
matching-offset unaligned b  src_off=2 dst_off=2 n=23 -> MATCH
mismatched offsets           src_off=1 dst_off=2 n=23 -> MATCH
zero length                  src_off=0 dst_off=0 n= 0 -> MATCH
shorter than one word        src_off=0 dst_off=0 n= 3 -> MATCH
all cases matched standard memcpy: yes

Compiled with clang -Wall -Wextra -O2 and run unchanged: these are exactly the six cases described (aligned/aligned, matching-offset unaligned at two different offsets, mismatched offsets, zero length, and a length shorter than one word), each diffed byte-for-byte against the standard library memcpy on the same buffers, and every case matched.

Key points

• The win is bus-transaction count, not cache behavior: 4x fewer transactions for the aligned bulk region.
• A secondary lever on top of this is unrolling the word loop (copy 2 or 4 words per iteration) to amortize loop-branch overhead further, worth it once the byte-by-byte cost is already fixed.
• For large, infrequent copies, offloading to a DMA (direct memory access) controller is the next step up: it moves the copy off the CPU entirely, but has its own setup latency and interrupt/polling overhead, so it only pays off above some size threshold, not for small copies.

Complexity

Same O(n) as the naive version, this is a constant-factor optimization: roughly 4x fewer bus transactions for the aligned middle section, at the cost of a small fixed amount of extra branching logic for the prefix/suffix handling.

Edge cases

• Source and destination overlapping (this implementation assumes non-overlapping regions, like standard memcpy; overlapping regions need memmove semantics with direction-aware copying).
• Very short copies (fewer than 4 bytes) where the word loop never runs and the whole thing degenerates to the safe byte path, which is correct but gets none of the speedup.
• Mismatched alignment between source and destination, which forces the byte-by-byte fallback for the entire copy, not just the edges.

Direct answer

Use STAR, and be ready for the fact this scenario shows up with different flavors depending on your field: the constraint that forces the pivot might be a compute or ad-spend budget, a compliance or regulatory trigger, an architecture limit, or a competitive shift. Whichever flavor your real story has, cover the same four things: what you adapted, what you reprioritized in flight, what trade-off you communicated and to whom, and how you checked afterward that the pivot actually delivered value rather than just assuming it did.

STAR skeleton to fill in

• Situation: the original plan and the trigger for the shift (leadership change, urgency, client need, or roadmap shift).
• Task: what you were responsible for delivering.
• Adapt the plan: what changed structurally, not just "we reprioritized."
• Reprioritize in-flight work: specifically what you paused, cut, or kept, and which requirement you refused to cut and why.
• Communicate trade-offs: what you told each stakeholder who owned a different constraint (cost, timeline, compliance, quality), not a single generic update.
• Deliver value and measure it: what you shipped given the new priorities, and what you checked afterward to confirm the pivot held up.

Worked example instance

Situation: midway through a three-week plan to train and deploy a new fraud-detection model feature, two things hit at once: a new regulatory request required a documented fairness audit before any model touching credit decisions could ship, and a company-wide cost push cut the quarter's compute budget by 30%. Adapt the plan: I paused two of five planned hyperparameter-sweep experiments, the ones consuming the most compute for marginal gains, and switched from a broad grid search to a narrower, warm-started search seeded from the best prior model's parameters. The original sweep plan was budgeted at 640 graphics-processing-unit hours (GPU-hours, a standard way to measure compute usage) across five experiments; the narrowed plan used 210 GPU-hours across two experiments plus the audit's own compute, a 67% reduction (640 minus 210, divided by 640), measured on the same GPU-hour basis for the same job accounting period. Reprioritize, non-negotiable requirement: the fairness audit ran on the full 12,000 case held-out evaluation set, not a sampled-down version, so the audit's statistical validity wasn't compromised by the cost pressure; the exploratory hyperparameter sweep, the lower-stakes item, is what I cut instead. The audit also required re-architecting part of the pipeline to log per-decision feature attributions, an added four engineering days. Communicate trade-offs: I presented one joint plan to both the sales stakeholder, who owned the client delivery date, and the engineering stakeholder, who owned the compute budget: a two-day slip (17 business days instead of the original 15), full fairness audit, and a reduced hyperparameter search, at no additional compute cost beyond the already-cut 210 GPU-hour budget. I was explicit that skipping the audit to hit the original date wasn't actually an option once it was flagged as a regulatory requirement, not a soft preference. Deliver value: we shipped two days late, audit complete, under the new compute ceiling, and the narrowed search's best model matched the broad search's baseline within 0.4 percentage points of area under the ROC curve (AUC, a measure of how well the model separates good from bad cases), so the compute cut didn't quietly cost accuracy. Measure afterward: six weeks post-launch, I compared the shipped model's live precision and recall against the pre-pivot baseline to confirm the narrower search hadn't cost anything in production that the offline holdout missed, and I kept the audit's finding, no significant disparate impact detected across the three protected groups examined, as a concrete artifact for the next time the regulatory question came up.

Second, shorter example (different discipline): a field-marketing team running a six-week campaign gets a leadership-driven pivot when a competitor announces a similar product, creating urgency to move up the launch. The lead cuts two lower-priority content pieces, keeps the core launch asset shipping on time as the non-negotiable requirement, tells the sales stakeholder who needed the materials exactly what got cut and why, and afterward checks whether the compressed review window introduced more post-launch corrections than usual, to decide whether that shortcut is safe to repeat.

Trap to avoid

The mediocre answer stops at "we reprioritized and delivered," without ever returning to check whether the pivot actually held up, and treats "communicate trade-offs" as one announcement rather than a decision made jointly with the specific stakeholders who each owned a different constraint.

Approach (brief)
Use branchless two's‑complement trick to compute abs: create a sign mask from x >> 31, compute (x + mask) ^ mask. That yields |x| for all values except INT_MIN (where negation overflows and result stays INT_MIN). Detect INT_MIN with an equality against 0x80000000u (unsigned compare), produce a 0 or -1 mask, and XOR to convert INT_MIN (0x80000000) into INT_MAX (0x7FFFFFFF). All operations are arithmetic/bitwise — no conditional branches.

#include <stdint.h>
#include <limits.h>

int32_t abs_saturated_branchless(int32_t x) {
    /* sign: 0 for non-negative, -1 for negative */
    int32_t sign = x >> 31;
    /* branchless absolute (wraps for INT_MIN) */
    int32_t y = (x + sign) ^ sign;
    /* detect INT_MIN without branching: (unsigned)x == 0x80000000u -> 0 or 1 */
    int32_t is_min = -((unsigned int)x == 0x80000000u); /* 0 or -1 */
    /* if is_min == -1, XOR flips 0x80000000 -> 0x7FFFFFFF; otherwise XOR 0 */
    return y ^ is_min;
}

Key points / reasoning

• x >> 31 yields arithmetic sign extension; safe for two's‑complement.
• (x + sign) ^ sign computes absolute value without branches.
• INT_MIN special-case detected via unsigned equality; negating produces 0 or -1 mask.
• XOR with -1 transforms INT_MIN (0x80000000) to INT_MAX (0x7FFFFFFF).

Time/space: O(1) time, O(1) space. No undefined behavior: no signed overflow, no conditional branches, only well-defined bitwise and shifts on two's‑complement targets typical in embedded systems.

Edge cases: works for all int32 values, returns INT_MAX for INT_MIN. Ensure compiler uses arithmetic right shift for signed >> (common on embedded ABIs) — if target uses logical shift, cast to int32_t/ensure implementation-defined behavior or use unsigned arithmetic with ((uint32_t)x >> 31) and adjust accordingly.

Brief approach / steps

• Copy initialized data (.data) from its load address in flash to its run address in RAM.
• Zero the .bss region in RAM.
• Optionally call constructors (C++), init hardware, then jump to main.
• If time-critical functions live in RAM, ensure their flash-load image is copied to RAM before they execute.

Typical linker symbols

• _sidata : start of initialized data in flash (load address)
• _sdata : start of .data in RAM (run address)
• _edata : end of .data in RAM
• _sbss : start of .bss in RAM
• _ebss : end of .bss in RAM

Concise C startup routine

extern uint32_t _sidata; /* in flash */
extern uint32_t _sdata;  /* in RAM */
extern uint32_t _edata;
extern uint32_t _sbss;
extern uint32_t _ebss;

void Reset_Handler(void) {
    uint32_t *src = &_sidata;
    uint32_t *dst = &_sdata;

    /* copy .data from flash to RAM */
    while (dst < &_edata) {
        *dst++ = *src++;
    }

    /* zero .bss */
    dst = &_sbss;
    while (dst < &_ebss) {
        *dst++ = 0;
    }

    /* If functions are executed from RAM, ensure their image is copied here
       before calling them. Then call system init and main(). */
    SystemInit();
    main();
}

Why place time-critical functions in RAM

• RAM execution removes flash wait states and flash controller contention, reducing latency and improving determinism (critical for ISRs, DMA-sensitive code, or flash-inaccessible modes like during erase/write).
• Impact on startup: you must include an extra copy step in startup to relocate those functions' code from flash to their RAM addresses (with corresponding linker symbols, e.g., _siram_text/_eiram_text and _siram_text_lma). That copy must occur before any code calls those routines (including interrupts). Also ensure vector table points to RAM if ISRs run there.

Clarify goal & constraints

• Reduce generated code across TUs and link time while preserving type safety and low RAM/flash for embedded targets. Keep predictable performance and no RTTI if constrained.

Practical techniques

1. Explicit instantiation / extern template

• Move heavy template impl to one .cpp and instantiate only needed types.

// heavy.h
template<typename T> T heavy_op(T);
// heavy.cpp
#include "heavy.h"
template<typename T> T heavy_op<T>(T x){ /*...*/ }
template double heavy_op<double>(double);
// user.cpp
extern template double heavy_op<double>(double);

• Result: only one copy of code emitted.

2. Pimpl / move implementation to single TU

• Expose thin non-template façade in headers, template internals in .cpp via concrete types or small virtual interface when few types exist.
• Trade-off: small vtable overhead vs code size savings.

3. Type-erasure / runtime-polymorphism for many template combos

• Use small type-erasure wrapper (inlined small-buffer) to hold different concrete instantiations but compile one implementation path.

// simplified: store callable with erased type to avoid templating across TUs
class Erased {
  struct I { virtual void run()=0; };
  template<typename F> struct Impl : I { F f; void run() override{ f(); } };
  std::unique_ptr<I> p;
public:
  template<typename F> Erased(F fn): p(new Impl<F>{fn}){}
  void run(){ p->run(); }
};

• Preserves safety at runtime, reduces template explosion.

4. Reduce template parameter space

• Narrow template axes: prefer traits, enums, tag types, or constexpr parameters grouped into bitfields so compiler sees fewer unique instantiations.
• Example: replace bool template params with runtime flags or a single enum tag.

5. Move heavy templates to single TU (monolithic instantiation)

• If a template truly needs to be generic, provide explicit instantiations for supported types only; reject others with static_assert.

Trade-offs & metrics

• Measure binary size and link time before/after; check stack/heap impact of indirection/vtables.
• Prefer explicit instantiation for deterministic embedded performance; use type-erasure when many combinations impossible to statically enumerate.

Recommendation
Start with extern template/explicit instantiation for top offenders, add Pimpl for large classes, then consider type-erasure or parameter consolidation if instantiation count remains high.

Direct answer
Three boundaries matter most: confidentiality (what's said in a mentoring conversation doesn't automatically become input to a performance review), favoritism (visible time and opportunity should be fair and roughly trackable, not just felt fair), and the evaluator conflict (mentoring someone you also formally evaluate creates a structural incentive problem, since they cannot be fully candid with someone who scores them). The practical fix is not avoiding all overlap, since it is often unavoidable, it is naming the boundary explicitly up front and having a plan for when it blurs.

Structured elaboration

Worked example
Situation: I was mentoring someone I would later be asked to give calibration input on for a promotion cycle.
Task: keep the mentoring relationship honest without compromising the integrity of the eventual evaluation.
Action: I told them directly, early, that promotion calibration might eventually involve my input, so mentoring conversations and evaluation conversations were separate. When something they shared in a mentoring context, a specific technical mistake, later became relevant to an honest performance discussion, I went back to them first rather than using it silently, and asked how they wanted it handled.
Result: the relationship stayed trustworthy because the boundary was named rather than assumed, even though the overlap between mentor and evaluator could not be fully removed.

Trade-offs & pitfalls
Pretending you can be a purely neutral mentor when you structurally have some evaluator influence is dishonest and erodes trust once it surfaces. Over-formalizing boundaries, a written contract for every casual pairing, feels bureaucratic when the stakes don't call for it, so match the formality to the actual overlap: an evaluator relationship needs an explicit conversation, a casual peer pairing usually doesn't. The senior distinction is naming the boundary before it's tested, not scrambling to explain it after a mentee feels burned.

Approach (brief)
Set up SPI peripheral as master full-duplex; configure two DMA channels: one memory->peripheral (TX), one peripheral->memory (RX). Start RX DMA first (so peripheral RX is ready), then start TX DMA and enable SPI. Synchronize via DMA-complete interrupts or checking transfer-complete flags. Handle mismatched sizes by transmitting dummy bytes or discarding extra RX bytes. Maintain cache coherency: clean TX buffer before DMA, invalidate RX buffer after DMA.

Pseudocode (C)

// Pseudocode: configure and kick off full-duplex SPI DMA transfer of N bytes
void spi_dma_transfer(uint8_t *tx_buf, size_t tx_len,
                      uint8_t *rx_buf, size_t rx_len, size_t N) {
    size_t tx_count = (tx_len >= N) ? N : N; // we'll send real bytes then dummies
    size_t rx_count = N;

    // 1) Cache maintenance
    if (HAS_DCACHE) {
        if (tx_buf) dcache_clean_region(tx_buf, tx_len);    // ensure memory visible to DMA
        if (rx_buf) dcache_invalidate_region(rx_buf, rx_len); // avoid stale data
    }

    // 2) Configure SPI peripheral for N bytes (master, full-duplex)
    spi_init_master_full_duplex();

    // 3) Configure DMA channels
    dma_config_t dma_tx = {
      .dir = MEM_TO_PERIPH, .src = tx_buf ? tx_buf : &dummy_byte,
      .dst = &SPI->DR, .len = N, .src_inc = !!tx_buf, .dst_inc = 0
    };
    dma_config_t dma_rx = {
      .dir = PERIPH_TO_MEM, .src = &SPI->DR, .dst = rx_buf,
      .len = N, .src_inc = 0, .dst_inc = 1
    };
    dma_setup_channel(DMA_CH_RX, &dma_rx);
    dma_setup_channel(DMA_CH_TX, &dma_tx);

    // 4) Start sequence: enable RX DMA first, then TX DMA, then enable SPI/DMA requests
    dma_enable(DMA_CH_RX);
    dma_enable(DMA_CH_TX);
    spi_enable_dma_rx(); // enable SPI DMA request for RX
    spi_enable_dma_tx(); // enable SPI DMA request for TX
    spi_enable();        // start SPI clocks

    // 5) Wait/synchronize: use DMA interrupts or poll completion
    wait_for_dma_complete(DMA_CH_RX);
    wait_for_dma_complete(DMA_CH_TX);

    // 6) Post-transfer cache maintenance
    if (HAS_DCACHE && rx_buf) dcache_invalidate_region(rx_buf, rx_len);

    // 7) Cleanup: disable SPI DMA requests, clear flags
    spi_disable_dma_rx(); spi_disable_dma_tx(); spi_disable();
    dma_clear_flags(DMA_CH_RX); dma_clear_flags(DMA_CH_TX);
}

Notes & Reasoning

• Start RX DMA first so peripheral RX writes have destination ready; start TX to generate clocks.
• If tx_buf shorter than N, point TX DMA to a single-word dummy byte (non-incrementing) after real bytes; if rx_buf smaller than N, discard extra bytes or limit RX length.
• Use DMA interrupts (highest priority) to minimize CPU wait; on RTOS signal a task.
• Cache: clean TX before DMA (writeback), invalidate RX after DMA (invalidate) to ensure CPU reads updated data.
• Edge cases: SPI overrun if RX not ready, peripheral FIFO sizes, alignment and DMA burst/size configuration, handling errors/timeouts.