Update nitrokey crate to 0.2.3

This change updates the nitrokey crate to version 0.2.3. This version
bumps the rand crate used to 0.6.1, which in turn requires an additional
set of dependencies.

Import subrepo nitrokey/:nitrokey at b3e2adc5bb1300441ca74cc7672617c042f3ea31
Import subrepo rand/:rand at 73613ff903512e9503e41cc8ba9eae76269dc598
Import subrepo rustc_version/:rustc_version at 0294f2ba2018bf7be672abd53db351ce5055fa02
Import subrepo semver-parser/:semver-parser at 750da9b11a04125231b1fb293866ca036845acee
Import subrepo semver/:semver at 5eb6db94fa03f4d5c64a625a56188f496be47598

1 files changed, 0 insertions, 754 deletions

diff --git a/rand/src/jitter.rs b/rand/src/jitter.rs
deleted file mode 100644
index 3693481..0000000
--- a/rand/src/jitter.rs
+++ /dev/null
@@ -1,754 +0,0 @@
-// Copyright 2017 The Rust Project Developers. See the COPYRIGHT
-// file at the top-level directory of this distribution and at
-// http://rust-lang.org/COPYRIGHT.
-//
-// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
-// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
-// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
-// option. This file may not be copied, modified, or distributed
-// except according to those terms.
-//
-// Based on jitterentropy-library, http://www.chronox.de/jent.html.
-// Copyright Stephan Mueller <smueller@chronox.de>, 2014 - 2017.
-//
-// With permission from Stephan Mueller to relicense the Rust translation under
-// the MIT license.
-
-//! Non-physical true random number generator based on timing jitter.
-
-use Rng;
-
-use core::{fmt, mem, ptr};
-#[cfg(feature="std")]
-use std::sync::atomic::{AtomicUsize, ATOMIC_USIZE_INIT, Ordering};
-
-const MEMORY_BLOCKS: usize = 64;
-const MEMORY_BLOCKSIZE: usize = 32;
-const MEMORY_SIZE: usize = MEMORY_BLOCKS * MEMORY_BLOCKSIZE;
-
-/// A true random number generator based on jitter in the CPU execution time,
-/// and jitter in memory access time.
-///
-/// This is a true random number generator, as opposed to pseudo-random
-/// generators. Random numbers generated by `JitterRng` can be seen as fresh
-/// entropy. A consequence is that is orders of magnitude slower than `OsRng`
-/// and PRNGs (about 10^3 .. 10^6 slower).
-///
-/// There are very few situations where using this RNG is appropriate. Only very
-/// few applications require true entropy. A normal PRNG can be statistically
-/// indistinguishable, and a cryptographic PRNG should also be as impossible to
-/// predict.
-///
-/// Use of `JitterRng` is recommended for initializing cryptographic PRNGs when
-/// `OsRng` is not available.
-///
-/// This implementation is based on
-/// [Jitterentropy](http://www.chronox.de/jent.html) version 2.1.0.
-//
-// Note: the C implementation relies on being compiled without optimizations.
-// This implementation goes through lengths to make the compiler not optimise
-// out what is technically dead code, but that does influence timing jitter.
-pub struct JitterRng {
-    data: u64, // Actual random number
-    // Number of rounds to run the entropy collector per 64 bits
-    rounds: u32,
-    // Timer and previous time stamp, used by `measure_jitter`
-    timer: fn() -> u64,
-    prev_time: u64,
-    // Deltas used for the stuck test
-    last_delta: i64,
-    last_delta2: i64,
-    // Memory for the Memory Access noise source
-    mem_prev_index: usize,
-    mem: [u8; MEMORY_SIZE],
-    // Make `next_u32` not waste 32 bits
-    data_remaining: Option<u32>,
-}
-
-// Custom Debug implementation that does not expose the internal state
-impl fmt::Debug for JitterRng {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
-        write!(f, "JitterRng {{}}")
-    }
-}
-
-/// An error that can occur when `test_timer` fails.
-#[derive(Debug, Clone, PartialEq, Eq)]
-pub enum TimerError {
-    /// No timer available.
-    NoTimer,
-    /// Timer too coarse to use as an entropy source.
-    CoarseTimer,
-    /// Timer is not monotonically increasing.
-    NotMonotonic,
-    /// Variations of deltas of time too small.
-    TinyVariantions,
-    /// Too many stuck results (indicating no added entropy).
-    TooManyStuck,
-    #[doc(hidden)]
-    __Nonexhaustive,
-}
-
-impl TimerError {
-    fn description(&self) -> &'static str {
-        match *self {
-            TimerError::NoTimer => "no timer available",
-            TimerError::CoarseTimer => "coarse timer",
-            TimerError::NotMonotonic => "timer not monotonic",
-            TimerError::TinyVariantions => "time delta variations too small",
-            TimerError::TooManyStuck => "too many stuck results",
-            TimerError::__Nonexhaustive => unreachable!(),
-        }
-    }
-}
-
-impl fmt::Display for TimerError {
-    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
-        write!(f, "{}", self.description())
-    }
-}
-
-#[cfg(feature="std")]
-impl ::std::error::Error for TimerError {
-    fn description(&self) -> &str {
-        self.description()
-    }
-}
-
-// Initialise to zero; must be positive
-#[cfg(feature="std")]
-static JITTER_ROUNDS: AtomicUsize = ATOMIC_USIZE_INIT;
-
-impl JitterRng {
-    /// Create a new `JitterRng`.
-    /// Makes use of `std::time` for a timer.
-    ///
-    /// During initialization CPU execution timing jitter is measured a few
-    /// hundred times. If this does not pass basic quality tests, an error is
-    /// returned. The test result is cached to make subsequent calls faster.
-    #[cfg(feature="std")]
-    pub fn new() -> Result<JitterRng, TimerError> {
-        let mut ec = JitterRng::new_with_timer(platform::get_nstime);
-        let mut rounds = JITTER_ROUNDS.load(Ordering::Relaxed) as u32;
-        if rounds == 0 {
-            // No result yet: run test.
-            // This allows the timer test to run multiple times; we don't care.
-            rounds = ec.test_timer()?;
-            JITTER_ROUNDS.store(rounds as usize, Ordering::Relaxed);
-        }
-        ec.set_rounds(rounds);
-        Ok(ec)
-    }
-
-    /// Create a new `JitterRng`.
-    /// A custom timer can be supplied, making it possible to use `JitterRng` in
-    /// `no_std` environments.
-    ///
-    /// The timer must have nanosecond precision.
-    ///
-    /// This method is more low-level than `new()`. It is the responsibility of
-    /// the caller to run `test_timer` before using any numbers generated with
-    /// `JitterRng`, and optionally call `set_rounds()`.
-    pub fn new_with_timer(timer: fn() -> u64) -> JitterRng {
-        let mut ec = JitterRng {
-            data: 0,
-            rounds: 64,
-            timer: timer,
-            prev_time: 0,
-            last_delta: 0,
-            last_delta2: 0,
-            mem_prev_index: 0,
-            mem: [0; MEMORY_SIZE],
-            data_remaining: None,
-        };
-
-        // Fill `data`, `prev_time`, `last_delta` and `last_delta2` with
-        // non-zero values.
-        ec.prev_time = timer();
-        ec.gen_entropy();
-
-        // Do a single read from `self.mem` to make sure the Memory Access noise
-        // source is not optimised out.
-        // Note: this read is important, it effects optimisations for the entire
-        // module!
-        black_box(ec.mem[0]);
-
-        ec
-    }
-
-    /// Configures how many rounds are used to generate each 64-bit value.
-    /// This must be greater than zero, and has a big impact on performance
-    /// and output quality.
-    ///
-    /// `new_with_timer` conservatively uses 64 rounds, but often less rounds
-    /// can be used. The `test_timer()` function returns the minimum number of
-    /// rounds required for full strength (platform dependent), so one may use
-    /// `rng.set_rounds(rng.test_timer()?);` or cache the value.
-    pub fn set_rounds(&mut self, rounds: u32) {
-        assert!(rounds > 0);
-        self.rounds = rounds;
-    }
-
-    // Calculate a random loop count used for the next round of an entropy
-    // collection, based on bits from a fresh value from the timer.
-    //
-    // The timer is folded to produce a number that contains at most `n_bits`
-    // bits.
-    //
-    // Note: A constant should be added to the resulting random loop count to
-    // prevent loops that run 0 times.
-    #[inline(never)]
-    fn random_loop_cnt(&mut self, n_bits: u32) -> u32 {
-        let mut rounds = 0;
-
-        let mut time = (self.timer)();
-        // Mix with the current state of the random number balance the random
-        // loop counter a bit more.
-        time ^= self.data;
-
-        // We fold the time value as much as possible to ensure that as many
-        // bits of the time stamp are included as possible.
-        let folds = (64 + n_bits - 1) / n_bits;
-        let mask = (1 << n_bits) - 1;
-        for _ in 0..folds {
-            rounds ^= time & mask;
-            time = time >> n_bits;
-        }
-
-        rounds as u32
-    }
-
-    // CPU jitter noise source
-    // Noise source based on the CPU execution time jitter
-    //
-    // This function injects the individual bits of the time value into the
-    // entropy pool using an LFSR.
-    //
-    // The code is deliberately inefficient with respect to the bit shifting.
-    // This function not only acts as folding operation, but this function's
-    // execution is used to measure the CPU execution time jitter. Any change to
-    // the loop in this function implies that careful retesting must be done.
-    #[inline(never)]
-    fn lfsr_time(&mut self, time: u64, var_rounds: bool) {
-        fn lfsr(mut data: u64, time: u64) -> u64{
-            for i in 1..65 {
-                let mut tmp = time << (64 - i);
-                tmp = tmp >> (64 - 1);
-
-                // Fibonacci LSFR with polynomial of
-                // x^64 + x^61 + x^56 + x^31 + x^28 + x^23 + 1 which is
-                // primitive according to
-                // http://poincare.matf.bg.ac.rs/~ezivkovm/publications/primpol1.pdf
-                // (the shift values are the polynomial values minus one
-                // due to counting bits from 0 to 63). As the current
-                // position is always the LSB, the polynomial only needs
-                // to shift data in from the left without wrap.
-                data ^= tmp;
-                data ^= (data >> 63) & 1;
-                data ^= (data >> 60) & 1;
-                data ^= (data >> 55) & 1;
-                data ^= (data >> 30) & 1;
-                data ^= (data >> 27) & 1;
-                data ^= (data >> 22) & 1;
-                data = data.rotate_left(1);
-            }
-            data
-        }
-
-        // Note: in the reference implementation only the last round effects
-        // `self.data`, all the other results are ignored. To make sure the
-        // other rounds are not optimised out, we first run all but the last
-        // round on a throw-away value instead of the real `self.data`.
-        let mut lfsr_loop_cnt = 0;
-        if var_rounds { lfsr_loop_cnt = self.random_loop_cnt(4) };
-
-        let mut throw_away: u64 = 0;
-        for _ in 0..lfsr_loop_cnt {
-            throw_away = lfsr(throw_away, time);
-        }
-        black_box(throw_away);
-
-        self.data = lfsr(self.data, time);
-    }
-
-    // Memory Access noise source
-    // This is a noise source based on variations in memory access times
-    //
-    // This function performs memory accesses which will add to the timing
-    // variations due to an unknown amount of CPU wait states that need to be
-    // added when accessing memory. The memory size should be larger than the L1
-    // caches as outlined in the documentation and the associated testing.
-    //
-    // The L1 cache has a very high bandwidth, albeit its access rate is usually
-    // slower than accessing CPU registers. Therefore, L1 accesses only add
-    // minimal variations as the CPU has hardly to wait. Starting with L2,
-    // significant variations are added because L2 typically does not belong to
-    // the CPU any more and therefore a wider range of CPU wait states is
-    // necessary for accesses. L3 and real memory accesses have even a wider
-    // range of wait states. However, to reliably access either L3 or memory,
-    // the `self.mem` memory must be quite large which is usually not desirable.
-    #[inline(never)]
-    fn memaccess(&mut self, var_rounds: bool) {
-        let mut acc_loop_cnt = 128;
-        if var_rounds { acc_loop_cnt += self.random_loop_cnt(4) };
-
-        let mut index = self.mem_prev_index;
-        for _ in 0..acc_loop_cnt {
-            // Addition of memblocksize - 1 to index with wrap around logic to
-            // ensure that every memory location is hit evenly.
-            // The modulus also allows the compiler to remove the indexing
-            // bounds check.
-            index = (index + MEMORY_BLOCKSIZE - 1) % MEMORY_SIZE;
-
-            // memory access: just add 1 to one byte
-            // memory access implies read from and write to memory location
-            let tmp = self.mem[index];
-            self.mem[index] = tmp.wrapping_add(1);
-        }
-        self.mem_prev_index = index;
-    }
-
-
-    // Stuck test by checking the:
-    // - 1st derivation of the jitter measurement (time delta)
-    // - 2nd derivation of the jitter measurement (delta of time deltas)
-    // - 3rd derivation of the jitter measurement (delta of delta of time
-    //   deltas)
-    //
-    // All values must always be non-zero.
-    // This test is a heuristic to see whether the last measurement holds
-    // entropy.
-    fn stuck(&mut self, current_delta: i64) -> bool {
-        let delta2 = self.last_delta - current_delta;
-        let delta3 = delta2 - self.last_delta2;
-
-        self.last_delta = current_delta;
-        self.last_delta2 = delta2;
-
-        current_delta == 0 || delta2 == 0 || delta3 == 0
-    }
-
-    // This is the heart of the entropy generation: calculate time deltas and
-    // use the CPU jitter in the time deltas. The jitter is injected into the
-    // entropy pool.
-    //
-    // Ensure that `self.prev_time` is primed before using the output of this
-    // function. This can be done by calling this function and not using its
-    // result.
-    fn measure_jitter(&mut self) -> Option<()> {
-        // Invoke one noise source before time measurement to add variations
-        self.memaccess(true);
-
-        // Get time stamp and calculate time delta to previous
-        // invocation to measure the timing variations
-        let time = (self.timer)();
-        // Note: wrapping_sub combined with a cast to `i64` generates a correct
-        // delta, even in the unlikely case this is a timer that is not strictly
-        // monotonic.
-        let current_delta = time.wrapping_sub(self.prev_time) as i64;
-        self.prev_time = time;
-
-        // Call the next noise source which also injects the data
-        self.lfsr_time(current_delta as u64, true);
-
-        // Check whether we have a stuck measurement (i.e. does the last
-        // measurement holds entropy?).
-        if self.stuck(current_delta) { return None };
-
-        // Rotate the data buffer by a prime number (any odd number would
-        // do) to ensure that every bit position of the input time stamp
-        // has an even chance of being merged with a bit position in the
-        // entropy pool. We do not use one here as the adjacent bits in
-        // successive time deltas may have some form of dependency. The
-        // chosen value of 7 implies that the low 7 bits of the next
-        // time delta value is concatenated with the current time delta.
-        self.data = self.data.rotate_left(7);
-
-        Some(())
-    }
-
-    // Shuffle the pool a bit by mixing some value with a bijective function
-    // (XOR) into the pool.
-    //
-    // The function generates a mixer value that depends on the bits set and
-    // the location of the set bits in the random number generated by the
-    // entropy source. Therefore, based on the generated random number, this
-    // mixer value can have 2^64 different values. That mixer value is
-    // initialized with the first two SHA-1 constants. After obtaining the
-    // mixer value, it is XORed into the random number.
-    //
-    // The mixer value is not assumed to contain any entropy. But due to the
-    // XOR operation, it can also not destroy any entropy present in the
-    // entropy pool.
-    #[inline(never)]
-    fn stir_pool(&mut self) {
-        // This constant is derived from the first two 32 bit initialization
-        // vectors of SHA-1 as defined in FIPS 180-4 section 5.3.1
-        // The order does not really matter as we do not rely on the specific
-        // numbers. We just pick the SHA-1 constants as they have a good mix of
-        // bit set and unset.
-        const CONSTANT: u64 = 0x67452301efcdab89;
-
-        // The start value of the mixer variable is derived from the third
-        // and fourth 32 bit initialization vector of SHA-1 as defined in
-        // FIPS 180-4 section 5.3.1
-        let mut mixer = 0x98badcfe10325476;
-
-        // This is a constant time function to prevent leaking timing
-        // information about the random number.
-        // The normal code is:
-        // ```
-        // for i in 0..64 {
-        //     if ((self.data >> i) & 1) == 1 { mixer ^= CONSTANT; }
-        // }
-        // ```
-        // This is a bit fragile, as LLVM really wants to use branches here, and
-        // we rely on it to not recognise the opportunity.
-        for i in 0..64 {
-            let apply = (self.data >> i) & 1;
-            let mask = !apply.wrapping_sub(1);
-            mixer ^= CONSTANT & mask;
-            mixer = mixer.rotate_left(1);
-        }
-
-        self.data ^= mixer;
-    }
-
-    fn gen_entropy(&mut self) -> u64 {
-        // Prime `self.prev_time`, and run the noice sources to make sure the
-        // first loop round collects the expected entropy.
-        let _ = self.measure_jitter();
-
-        for _ in 0..self.rounds {
-            // If a stuck measurement is received, repeat measurement
-            // Note: we do not guard against an infinite loop, that would mean
-            // the timer suddenly became broken.
-            while self.measure_jitter().is_none() {}
-        }
-
-        self.stir_pool();
-        self.data
-    }
-
-    /// Basic quality tests on the timer, by measuring CPU timing jitter a few
-    /// hundred times.
-    ///
-    /// If succesful, this will return the estimated number of rounds necessary
-    /// to collect 64 bits of entropy. Otherwise a `TimerError` with the cause
-    /// of the failure will be returned.
-    pub fn test_timer(&mut self) -> Result<u32, TimerError> {
-        // We could add a check for system capabilities such as `clock_getres`
-        // or check for `CONFIG_X86_TSC`, but it does not make much sense as the
-        // following sanity checks verify that we have a high-resolution timer.
-
-        #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))]
-        return Err(TimerError::NoTimer);
-
-        let mut delta_sum = 0;
-        let mut old_delta = 0;
-
-        let mut time_backwards = 0;
-        let mut count_mod = 0;
-        let mut count_stuck = 0;
-
-        // TESTLOOPCOUNT needs some loops to identify edge systems.
-        // 100 is definitely too little.
-        const TESTLOOPCOUNT: u64 = 300;
-        const CLEARCACHE: u64 = 100;
-
-        for i in 0..(CLEARCACHE + TESTLOOPCOUNT) {
-            // Measure time delta of core entropy collection logic
-            let time = (self.timer)();
-            self.memaccess(true);
-            self.lfsr_time(time, true);
-            let time2 = (self.timer)();
-
-            // Test whether timer works
-            if time == 0 || time2 == 0 {
-                return Err(TimerError::NoTimer);
-            }
-            let delta = time2.wrapping_sub(time) as i64;
-
-            // Test whether timer is fine grained enough to provide delta even
-            // when called shortly after each other -- this implies that we also
-            // have a high resolution timer
-            if delta == 0 {
-                return Err(TimerError::CoarseTimer);
-            }
-
-            // Up to here we did not modify any variable that will be
-            // evaluated later, but we already performed some work. Thus we
-            // already have had an impact on the caches, branch prediction,
-            // etc. with the goal to clear it to get the worst case
-            // measurements.
-            if i < CLEARCACHE { continue; }
-
-            if self.stuck(delta) { count_stuck += 1; }
-
-            // Test whether we have an increasing timer.
-            if !(time2 > time) { time_backwards += 1; }
-
-            // Count the number of times the counter increases in steps of 100ns
-            // or greater.
-            if (delta % 100) == 0 { count_mod += 1; }
-
-            // Ensure that we have a varying delta timer which is necessary for
-            // the calculation of entropy -- perform this check only after the
-            // first loop is executed as we need to prime the old_delta value
-            delta_sum += (delta - old_delta).abs() as u64;
-            old_delta = delta;
-        }
-
-        // We allow the time to run backwards for up to three times.
-        // This can happen if the clock is being adjusted by NTP operations.
-        // If such an operation just happens to interfere with our test, it
-        // should not fail. The value of 3 should cover the NTP case being
-        // performed during our test run.
-        if time_backwards > 3 {
-            return Err(TimerError::NotMonotonic);
-        }
-
-        // Test that the available amount of entropy per round does not get to
-        // low. We expect 1 bit of entropy per round as a reasonable minimum
-        // (although less is possible, it means the collector loop has to run
-        // much more often).
-        // `assert!(delta_average >= log2(1))`
-        // `assert!(delta_sum / TESTLOOPCOUNT >= 1)`
-        // `assert!(delta_sum >= TESTLOOPCOUNT)`
-        if delta_sum < TESTLOOPCOUNT {
-            return Err(TimerError::TinyVariantions);
-        }
-
-        // Ensure that we have variations in the time stamp below 100 for at
-        // least 10% of all checks -- on some platforms, the counter increments
-        // in multiples of 100, but not always
-        if count_mod > (TESTLOOPCOUNT * 9 / 10) {
-            return Err(TimerError::CoarseTimer);
-        }
-
-        // If we have more than 90% stuck results, then this Jitter RNG is
-        // likely to not work well.
-        if count_stuck > (TESTLOOPCOUNT * 9 / 10) {
-            return Err(TimerError::TooManyStuck);
-        }
-
-        // Estimate the number of `measure_jitter` rounds necessary for 64 bits
-        // of entropy.
-        //
-        // We don't try very hard to come up with a good estimate of the
-        // available bits of entropy per round here for two reasons:
-        // 1. Simple estimates of the available bits (like Shannon entropy) are
-        //    too optimistic.
-        // 2)  Unless we want to waste a lot of time during intialization, there
-        //     only a small number of samples are available.
-        //
-        // Therefore we use a very simple and conservative estimate:
-        // `let bits_of_entropy = log2(delta_average) / 2`.
-        //
-        // The number of rounds `measure_jitter` should run to collect 64 bits
-        // of entropy is `64 / bits_of_entropy`.
-        //
-        // To have smaller rounding errors, intermediate values are multiplied
-        // by `FACTOR`. To compensate for `log2` and division rounding down,
-        // add 1.
-        let delta_average = delta_sum / TESTLOOPCOUNT;
-        // println!("delta_average: {}", delta_average);
-
-        const FACTOR: u32  = 3;
-        fn log2(x: u64) -> u32 { 64 - x.leading_zeros() }
-
-        // pow(δ, FACTOR) must be representable; if you have overflow reduce FACTOR
-        Ok(64 * 2 * FACTOR / (log2(delta_average.pow(FACTOR)) + 1))
-    }
-
-    /// Statistical test: return the timer delta of one normal run of the
-    /// `JitterEntropy` entropy collector.
-    ///
-    /// Setting `var_rounds` to `true` will execute the memory access and the
-    /// CPU jitter noice sources a variable amount of times (just like a real
-    /// `JitterEntropy` round).
-    ///
-    /// Setting `var_rounds` to `false` will execute the noice sources the
-    /// minimal number of times. This can be used to measure the minimum amount
-    /// of entropy one round of entropy collector can collect in the worst case.
-    ///
-    /// # Example
-    ///
-    /// Use `timer_stats` to run the [NIST SP 800-90B Entropy Estimation Suite]
-    /// (https://github.com/usnistgov/SP800-90B_EntropyAssessment).
-    ///
-    /// This is the recommended way to test the quality of `JitterRng`. It
-    /// should be run before using the RNG on untested hardware, after changes
-    /// that could effect how the code is optimised, and after major compiler
-    /// compiler changes, like a new LLVM version.
-    ///
-    /// First generate two files `jitter_rng_var.bin` and `jitter_rng_var.min`.
-    ///
-    /// Execute `python noniid_main.py -v jitter_rng_var.bin 8`, and validate it
-    /// with `restart.py -v jitter_rng_var.bin 8 <min-entropy>`.
-    /// This number is the expected amount of entropy that is at least available
-    /// for each round of the entropy collector. This number should be greater
-    /// than the amount estimated with `64 / test_timer()`.
-    ///
-    /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and
-    /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`.
-    /// This number is the expected amount of entropy that is available in the
-    /// last 4 bits of the timer delta after running noice sources. Note that
-    /// a value of 3.70 is the minimum estimated entropy for true randomness.
-    ///
-    /// Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, and
-    /// validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 <min-entropy>`.
-    /// This number is the expected amount of entropy that is available to the
-    /// entropy collecter if both noice sources only run their minimal number of
-    /// times. This measures the absolute worst-case, and gives a lower bound
-    /// for the available entropy.
-    ///
-    /// ```rust,no_run
-    /// use rand::JitterRng;
-    ///
-    /// # use std::error::Error;
-    /// # use std::fs::File;
-    /// # use std::io::Write;
-    /// #
-    /// # fn try_main() -> Result<(), Box<Error>> {
-    /// fn get_nstime() -> u64 {
-    ///     use std::time::{SystemTime, UNIX_EPOCH};
-    ///
-    ///     let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();
-    ///     // The correct way to calculate the current time is
-    ///     // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64`
-    ///     // But this is faster, and the difference in terms of entropy is
-    ///     // negligible (log2(10^9) == 29.9).
-    ///     dur.as_secs() << 30 | dur.subsec_nanos() as u64
-    /// }
-    ///
-    /// // Do not initialize with `JitterRng::new`, but with `new_with_timer`.
-    /// // 'new' always runst `test_timer`, and can therefore fail to
-    /// // initialize. We want to be able to get the statistics even when the
-    /// // timer test fails.
-    /// let mut rng = JitterRng::new_with_timer(get_nstime);
-    ///
-    /// // 1_000_000 results are required for the NIST SP 800-90B Entropy
-    /// // Estimation Suite
-    /// // FIXME: this number is smaller here, otherwise the Doc-test is too slow
-    /// const ROUNDS: usize = 10_000;
-    /// let mut deltas_variable: Vec<u8> = Vec::with_capacity(ROUNDS);
-    /// let mut deltas_minimal: Vec<u8> = Vec::with_capacity(ROUNDS);
-    ///
-    /// for _ in 0..ROUNDS {
-    ///     deltas_variable.push(rng.timer_stats(true) as u8);
-    ///     deltas_minimal.push(rng.timer_stats(false) as u8);
-    /// }
-    ///
-    /// // Write out after the statistics collection loop, to not disturb the
-    /// // test results.
-    /// File::create("jitter_rng_var.bin")?.write(&deltas_variable)?;
-    /// File::create("jitter_rng_min.bin")?.write(&deltas_minimal)?;
-    /// #
-    /// # Ok(())
-    /// # }
-    /// #
-    /// # fn main() {
-    /// #     try_main().unwrap();
-    /// # }
-    /// ```
-    #[cfg(feature="std")]
-    pub fn timer_stats(&mut self, var_rounds: bool) -> i64 {
-        let time = platform::get_nstime();
-        self.memaccess(var_rounds);
-        self.lfsr_time(time, var_rounds);
-        let time2 = platform::get_nstime();
-        time2.wrapping_sub(time) as i64
-    }
-}
-
-#[cfg(feature="std")]
-mod platform {
-    #[cfg(not(any(target_os = "macos", target_os = "ios", target_os = "windows", all(target_arch = "wasm32", not(target_os = "emscripten")))))]
-    pub fn get_nstime() -> u64 {
-        use std::time::{SystemTime, UNIX_EPOCH};
-
-        let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();
-        // The correct way to calculate the current time is
-        // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64`
-        // But this is faster, and the difference in terms of entropy is negligible
-        // (log2(10^9) == 29.9).
-        dur.as_secs() << 30 | dur.subsec_nanos() as u64
-    }
-
-    #[cfg(any(target_os = "macos", target_os = "ios"))]
-    pub fn get_nstime() -> u64 {
-        extern crate libc;
-        // On Mac OS and iOS std::time::SystemTime only has 1000ns resolution.
-        // We use `mach_absolute_time` instead. This provides a CPU dependent unit,
-        // to get real nanoseconds the result should by multiplied by numer/denom
-        // from `mach_timebase_info`.
-        // But we are not interested in the exact nanoseconds, just entropy. So we
-        // use the raw result.
-        unsafe { libc::mach_absolute_time() }
-    }
-
-    #[cfg(target_os = "windows")]
-    pub fn get_nstime() -> u64 {
-        extern crate winapi;
-        unsafe {
-            let mut t = super::mem::zeroed();
-            winapi::um::profileapi::QueryPerformanceCounter(&mut t);
-            *t.QuadPart() as u64
-        }
-    }
-
-    #[cfg(all(target_arch = "wasm32", not(target_os = "emscripten")))]
-    pub fn get_nstime() -> u64 {
-        unreachable!()
-    }
-}
-
-// A function that is opaque to the optimizer to assist in avoiding dead-code
-// elimination. Taken from `bencher`.
-fn black_box<T>(dummy: T) -> T {
-    unsafe {
-        let ret = ptr::read_volatile(&dummy);
-        mem::forget(dummy);
-        ret
-    }
-}
-
-impl Rng for JitterRng {
-    fn next_u32(&mut self) -> u32 {
-        // We want to use both parts of the generated entropy
-        if let Some(high) = self.data_remaining.take() {
-            high
-        } else {
-            let data = self.next_u64();
-            self.data_remaining = Some((data >> 32) as u32);
-            data as u32
-        }
-    }
-
-    fn next_u64(&mut self) -> u64 {
-       self.gen_entropy()
-    }
-
-    fn fill_bytes(&mut self, dest: &mut [u8]) {
-        let mut left = dest;
-        while left.len() >= 8 {
-            let (l, r) = {left}.split_at_mut(8);
-            left = r;
-            let chunk: [u8; 8] = unsafe {
-                mem::transmute(self.next_u64().to_le())
-            };
-            l.copy_from_slice(&chunk);
-        }
-        let n = left.len();
-        if n > 0 {
-            let chunk: [u8; 8] = unsafe {
-                mem::transmute(self.next_u64().to_le())
-            };
-            left.copy_from_slice(&chunk[..n]);
-        }
-    }
-}
-
-// There are no tests included because (1) this is an "external" RNG, so output
-// is not reproducible and (2) `test_timer` *will* fail on some platforms.