diff --git a/vlib/math/exp.v b/vlib/math/exp.v
index 9a6890b666..4e5f59e57b 100644
--- a/vlib/math/exp.v
+++ b/vlib/math/exp.v
@@ -96,6 +96,7 @@ pub fn exp2(x f64) f64 {
 	return expmulti(hi, lo, k)
 }
 
+// ldexp calculates frac*(2**exp)
 pub fn ldexp(frac f64, exp int) f64 {
 	return scalbn(frac, exp)
 }
@@ -146,6 +147,7 @@ pub fn frexp(x f64) (f64, int) {
 	return f64_from_bits(y), e_
 }
 
+// expm1 calculates e**x - 1
 // special cases are:
 // expm1(+inf) = +inf
 // expm1(-inf) = -1
@@ -176,7 +178,6 @@ pub fn expm1(x f64) f64 {
 	}
 }
 
-// exp1 returns e**r × 2**k where r = hi - lo and |r| ≤ ln(2)/2.
 fn expmulti(hi f64, lo f64, k int) f64 {
 	exp_p1 := 1.66666666666666657415e-01 // 0x3FC55555; 0x55555555
 	exp_p2 := -2.77777777770155933842e-03 // 0xBF66C16C; 0x16BEBD93
diff --git a/vlib/math/hypot.v b/vlib/math/hypot.v
index 41375057b6..c7cb9e54df 100644
--- a/vlib/math/hypot.v
+++ b/vlib/math/hypot.v
@@ -1,5 +1,6 @@
 module math
 
+// hypot returns the hypotenuse of the triangle give two sides
 pub fn hypot(x f64, y f64) f64 {
 	if is_inf(x, 0) || is_inf(y, 0) {
 		return inf(1)
diff --git a/vlib/math/invhyp.v b/vlib/math/invhyp.v
index 4ef93cbce1..5884b4e5ad 100644
--- a/vlib/math/invhyp.v
+++ b/vlib/math/invhyp.v
@@ -1,6 +1,7 @@
 module math
 
 import math.internal
+// acosh returns the non negative area hyperbolic cosine of x
 
 pub fn acosh(x f64) f64 {
 	if x == 0.0 {
@@ -19,6 +20,7 @@ pub fn acosh(x f64) f64 {
 	}
 }
 
+// asinh returns the area hyperbolic sine of x
 pub fn asinh(x f64) f64 {
 	a := abs(x)
 	s := if x < 0 { -1.0 } else { 1.0 }
@@ -34,6 +36,7 @@ pub fn asinh(x f64) f64 {
 	}
 }
 
+// atanh returns the area hyperbolic tangent of x
 pub fn atanh(x f64) f64 {
 	a := abs(x)
 	s := if x < 0 { -1.0 } else { 1.0 }
diff --git a/vlib/math/log.v b/vlib/math/log.v
index f274d0fc2a..da7eaedaa5 100644
--- a/vlib/math/log.v
+++ b/vlib/math/log.v
@@ -1,5 +1,6 @@
 module math
 
+// log_n returns log base b of x
 pub fn log_n(x f64, b f64) f64 {
 	y := log(x)
 	z := log(b)
@@ -24,6 +25,7 @@ pub fn log2(x f64) f64 {
 	return log(frac) * (1.0 / ln2) + f64(exp)
 }
 
+// log1p returns log(1+x)
 pub fn log1p(x f64) f64 {
 	y := 1.0 + x
 	z := y - 1.0
diff --git a/vlib/math/math.v b/vlib/math/math.v
index 0d0d7a56f9..71562b04df 100644
--- a/vlib/math/math.v
+++ b/vlib/math/math.v
@@ -155,6 +155,7 @@ pub fn signbit(x f64) bool {
 	return f64_bits(x) & sign_mask != 0
 }
 
+// tolerance checks if a and b difference are less than or equal to the tolerance value
 pub fn tolerance(a f64, b f64, tol f64) bool {
 	mut ee := tol
 	// Multiplying by ee here can underflow denormal values to zero.
@@ -178,14 +179,17 @@ pub fn tolerance(a f64, b f64, tol f64) bool {
 	return d < ee
 }
 
+// close checks if a and b are within 1e-14 of each other
 pub fn close(a f64, b f64) bool {
 	return tolerance(a, b, 1e-14)
 }
 
+// veryclose checks if a and b are within 4e-16 of each other
 pub fn veryclose(a f64, b f64) bool {
 	return tolerance(a, b, 4e-16)
 }
 
+// alike checks if a and b are equal
 pub fn alike(a f64, b f64) bool {
 	if is_nan(a) && is_nan(b) {
 		return true
diff --git a/vlib/math/sin.c.v b/vlib/math/sin.c.v
index 39a4b8518f..ef313af18e 100644
--- a/vlib/math/sin.c.v
+++ b/vlib/math/sin.c.v
@@ -4,13 +4,13 @@ fn C.cosf(x f32) f32
 
 fn C.sinf(x f32) f32
 
-// cosf calculates cosine. (float32)
+// cosf calculates cosine in radians (float32)
 [inline]
 pub fn cosf(a f32) f32 {
 	return C.cosf(a)
 }
 
-// sinf calculates sine. (float32)
+// sinf calculates sine in radians (float32)
 [inline]
 pub fn sinf(a f32) f32 {
 	return C.sinf(a)
diff --git a/vlib/math/sin.js.v b/vlib/math/sin.js.v
index 40ef854bfc..ab6acf1fe0 100644
--- a/vlib/math/sin.js.v
+++ b/vlib/math/sin.js.v
@@ -4,13 +4,13 @@ fn JS.Math.cos(x f64) f64
 
 fn JS.Math.sin(x f64) f64
 
-// cos calculates cosine.
+// cos calculates cosine in radians
 [inline]
 pub fn cos(a f64) f64 {
 	return JS.Math.cos(a)
 }
 
-// sin calculates sine.
+// sin calculates sine in radians
 [inline]
 pub fn sin(a f64) f64 {
 	return JS.Math.sin(a)
diff --git a/vlib/math/sin.v b/vlib/math/sin.v
index 193eb798ab..a2a2e05d7b 100644
--- a/vlib/math/sin.v
+++ b/vlib/math/sin.v
@@ -44,6 +44,7 @@ const (
 	}
 )
 
+// sin calculates the sine of the angle in radians
 pub fn sin(x f64) f64 {
 	p1 := 7.85398125648498535156e-1
 	p2 := 3.77489470793079817668e-8
@@ -82,6 +83,7 @@ pub fn sin(x f64) f64 {
 	}
 }
 
+// cos calculates the cosine of the angle in radians
 pub fn cos(x f64) f64 {
 	p1 := 7.85398125648498535156e-1
 	p2 := 3.77489470793079817668e-8
@@ -122,18 +124,19 @@ pub fn cos(x f64) f64 {
 	}
 }
 
-// cosf calculates cosine. (float32).
+// cosf calculates cosine in radians (float32).
 [inline]
 pub fn cosf(a f32) f32 {
 	return f32(cos(a))
 }
 
-// sinf calculates sine. (float32)
+// sinf calculates sine in radians (float32)
 [inline]
 pub fn sinf(a f32) f32 {
 	return f32(sin(a))
 }
 
+// sincos calculates the sine and cosine of the angle in radians
 pub fn sincos(x f64) (f64, f64) {
 	p1 := 7.85398125648498535156e-1
 	p2 := 3.77489470793079817668e-8
diff --git a/vlib/math/sinh.js.v b/vlib/math/sinh.js.v
index 8c7d72f5c4..5fb0f5c6d0 100644
--- a/vlib/math/sinh.js.v
+++ b/vlib/math/sinh.js.v
@@ -4,13 +4,13 @@ fn JS.Math.cosh(x f64) f64
 
 fn JS.Math.sinh(x f64) f64
 
-// cosh calculates hyperbolic cosine.
+// cosh calculates hyperbolic cosine in radians
 [inline]
 pub fn cosh(a f64) f64 {
 	return JS.Math.cosh(a)
 }
 
-// sinh calculates hyperbolic sine.
+// sinh calculates hyperbolic sine in radians
 [inline]
 pub fn sinh(a f64) f64 {
 	return JS.Math.sinh(a)
diff --git a/vlib/math/sinh.v b/vlib/math/sinh.v
index 6bbf88088b..bfb818f22d 100644
--- a/vlib/math/sinh.v
+++ b/vlib/math/sinh.v
@@ -33,7 +33,7 @@ pub fn sinh(x_ f64) f64 {
 	return temp
 }
 
-// cosh returns the hyperbolic cosine of x.
+// cosh returns the hyperbolic cosine of x in radians
 //
 // special cases are:
 // cosh(±0) = 1
diff --git a/vlib/math/stats/stats.v b/vlib/math/stats/stats.v
index 544391019d..2b19e613d5 100644
--- a/vlib/math/stats/stats.v
+++ b/vlib/math/stats/stats.v
@@ -2,7 +2,7 @@ module stats
 
 import math
 
-// Measure of Occurance
+// freq calculates the Measure of Occurance
 // Frequency of a given number
 // Based on
 // https://www.mathsisfun.com/data/frequency-distribution.html
@@ -19,8 +19,8 @@ pub fn freq<T>(data []T, val T) int {
 	return count
 }
 
-// Measure of Central Tendancy
-// Mean of the given input array
+// mean calculates the average
+// of the given input array, sum(data)/data.len
 // Based on
 // https://www.mathsisfun.com/data/central-measures.html
 pub fn mean<T>(data []T) T {
@@ -34,8 +34,8 @@ pub fn mean<T>(data []T) T {
 	return sum / T(data.len)
 }
 
-// Measure of Central Tendancy
-// Geometric Mean of the given input array
+// geometric_mean calculates the central tendency
+// of the given input array, product(data)**1/data.len
 // Based on
 // https://www.mathsisfun.com/numbers/geometric-mean.html
 pub fn geometric_mean<T>(data []T) T {
@@ -49,8 +49,8 @@ pub fn geometric_mean<T>(data []T) T {
 	return math.pow(sum, 1.0 / T(data.len))
 }
 
-// Measure of Central Tendancy
-// Harmonic Mean of the given input array
+// harmonic_mean calculates the reciprocal of the average of reciprocals
+// of the given input array
 // Based on
 // https://www.mathsisfun.com/numbers/harmonic-mean.html
 pub fn harmonic_mean<T>(data []T) T {
@@ -64,8 +64,7 @@ pub fn harmonic_mean<T>(data []T) T {
 	return T(data.len) / sum
 }
 
-// Measure of Central Tendancy
-// Median of the given input array ( input array is assumed to be sorted )
+// median returns the middlemost value of the given input array ( input array is assumed to be sorted )
 // Based on
 // https://www.mathsisfun.com/data/central-measures.html
 pub fn median<T>(sorted_data []T) T {
@@ -80,8 +79,7 @@ pub fn median<T>(sorted_data []T) T {
 	}
 }
 
-// Measure of Central Tendancy
-// Mode of the given input array
+// mode calculates the highest occuring value of the given input array
 // Based on
 // https://www.mathsisfun.com/data/central-measures.html
 pub fn mode<T>(data []T) T {
@@ -101,7 +99,7 @@ pub fn mode<T>(data []T) T {
 	return data[max]
 }
 
-// Root Mean Square of the given input array
+// rms, Root Mean Square, calculates the sqrt of the mean of the squares of the given input array
 // Based on
 // https://en.wikipedia.org/wiki/Root_mean_square
 pub fn rms<T>(data []T) T {
@@ -115,8 +113,8 @@ pub fn rms<T>(data []T) T {
 	return math.sqrt(sum / T(data.len))
 }
 
-// Measure of Dispersion / Spread
-// Population Variance of the given input array
+// population_variance is the Measure of Dispersion / Spread
+// of the given input array
 // Based on
 // https://www.mathsisfun.com/data/standard-deviation.html
 [inline]
@@ -128,8 +126,8 @@ pub fn population_variance<T>(data []T) T {
 	return population_variance_mean<T>(data, data_mean)
 }
 
-// Measure of Dispersion / Spread
-// Population Variance of the given input array
+// population_variance_mean is the Measure of Dispersion / Spread
+// of the given input array, with the provided mean
 // Based on
 // https://www.mathsisfun.com/data/standard-deviation.html
 pub fn population_variance_mean<T>(data []T, mean T) T {
@@ -143,8 +141,7 @@ pub fn population_variance_mean<T>(data []T, mean T) T {
 	return sum / T(data.len)
 }
 
-// Measure of Dispersion / Spread
-// Sample Variance of the given input array
+// sample_variance calculates the spread of dataset around the mean
 // Based on
 // https://www.mathsisfun.com/data/standard-deviation.html
 [inline]
@@ -156,8 +153,7 @@ pub fn sample_variance<T>(data []T) T {
 	return sample_variance_mean<T>(data, data_mean)
 }
 
-// Measure of Dispersion / Spread
-// Sample Variance of the given input array
+// sample_variance calculates the spread of dataset around the provided mean
 // Based on
 // https://www.mathsisfun.com/data/standard-deviation.html
 pub fn sample_variance_mean<T>(data []T, mean T) T {
@@ -171,8 +167,7 @@ pub fn sample_variance_mean<T>(data []T, mean T) T {
 	return sum / T(data.len - 1)
 }
 
-// Measure of Dispersion / Spread
-// Population Standard Deviation of the given input array
+// population_stddev calculates how spread out the dataset is
 // Based on
 // https://www.mathsisfun.com/data/standard-deviation.html
 [inline]
@@ -183,8 +178,7 @@ pub fn population_stddev<T>(data []T) T {
 	return math.sqrt(population_variance<T>(data))
 }
 
-// Measure of Dispersion / Spread
-// Population Standard Deviation of the given input array
+// population_stddev_mean calculates how spread out the dataset is, with the provide mean
 // Based on
 // https://www.mathsisfun.com/data/standard-deviation.html
 [inline]
@@ -219,8 +213,7 @@ pub fn sample_stddev_mean<T>(data []T, mean T) T {
 	return T(math.sqrt(f64(sample_variance_mean<T>(data, mean))))
 }
 
-// Measure of Dispersion / Spread
-// Mean Absolute Deviation of the given input array
+// absdev calculates the average distance between each data point and the mean
 // Based on
 // https://en.wikipedia.org/wiki/Average_absolute_deviation
 [inline]
@@ -232,8 +225,7 @@ pub fn absdev<T>(data []T) T {
 	return absdev_mean<T>(data, data_mean)
 }
 
-// Measure of Dispersion / Spread
-// Mean Absolute Deviation of the given input array
+// absdev_mean calculates the average distance between each data point and the provided mean
 // Based on
 // https://en.wikipedia.org/wiki/Average_absolute_deviation
 pub fn absdev_mean<T>(data []T, mean T) T {
@@ -247,7 +239,7 @@ pub fn absdev_mean<T>(data []T, mean T) T {
 	return sum / T(data.len)
 }
 
-// Sum of squares
+// tts, Sum of squares, calculates the sum over all squared differences between values and overall mean
 [inline]
 pub fn tss<T>(data []T) T {
 	if data.len == 0 {
@@ -257,7 +249,7 @@ pub fn tss<T>(data []T) T {
 	return tss_mean<T>(data, data_mean)
 }
 
-// Sum of squares about the mean
+// tts_mean, Sum of squares, calculates the sum over all squared differences between values and the provided mean
 pub fn tss_mean<T>(data []T, mean T) T {
 	if data.len == 0 {
 		return T(0)
@@ -269,7 +261,7 @@ pub fn tss_mean<T>(data []T, mean T) T {
 	return tss
 }
 
-// Minimum of the given input array
+// min finds the minimum value from the dataset
 pub fn min<T>(data []T) T {
 	if data.len == 0 {
 		return T(0)
@@ -283,7 +275,7 @@ pub fn min<T>(data []T) T {
 	return min
 }
 
-// Maximum of the given input array
+// max finds the maximum value from the dataset
 pub fn max<T>(data []T) T {
 	if data.len == 0 {
 		return T(0)
@@ -297,7 +289,7 @@ pub fn max<T>(data []T) T {
 	return max
 }
 
-// Minimum and maximum of the given input array
+// minmax finds the minimum and maximum value from the dataset
 pub fn minmax<T>(data []T) (T, T) {
 	if data.len == 0 {
 		return T(0), T(0)
@@ -315,7 +307,7 @@ pub fn minmax<T>(data []T) (T, T) {
 	return min, max
 }
 
-// Minimum of the given input array
+// min_index finds the first index of the minimum value
 pub fn min_index<T>(data []T) int {
 	if data.len == 0 {
 		return 0
@@ -331,7 +323,7 @@ pub fn min_index<T>(data []T) int {
 	return min_index
 }
 
-// Maximum of the given input array
+// max_index finds the first index of the maximum value
 pub fn max_index<T>(data []T) int {
 	if data.len == 0 {
 		return 0
@@ -347,7 +339,7 @@ pub fn max_index<T>(data []T) int {
 	return max_index
 }
 
-// Minimum and maximum of the given input array
+// minmax_index finds the first index of the minimum and maximum value
 pub fn minmax_index<T>(data []T) (int, int) {
 	if data.len == 0 {
 		return 0, 0
@@ -369,7 +361,7 @@ pub fn minmax_index<T>(data []T) (int, int) {
 	return min_index, max_index
 }
 
-// Measure of Dispersion / Spread
+// range calculates the difference between the min and max
 // Range ( Maximum - Minimum ) of the given input array
 // Based on
 // https://www.mathsisfun.com/data/range.html
@@ -381,6 +373,8 @@ pub fn range<T>(data []T) T {
 	return max - min
 }
 
+// covariance calculates directional association between datasets
+// positive value denotes variables move in same direction and negative denotes variables move in opposite directions
 [inline]
 pub fn covariance<T>(data1 []T, data2 []T) T {
 	mean1 := mean<T>(data1)
@@ -388,7 +382,7 @@ pub fn covariance<T>(data1 []T, data2 []T) T {
 	return covariance_mean<T>(data1, data2, mean1, mean2)
 }
 
-// Compute the covariance of a dataset using
+// covariance_mean computes the covariance of a dataset with means provided
 // the recurrence relation
 pub fn covariance_mean<T>(data1 []T, data2 []T, mean1 T, mean2 T) T {
 	n := int(math.min(data1.len, data2.len))
@@ -404,13 +398,16 @@ pub fn covariance_mean<T>(data1 []T, data2 []T, mean1 T, mean2 T) T {
 	return covariance
 }
 
+// lag1_autocorrelation_mean calculates the correlation between values that are one time period apart
+// of a dataset, based on the mean
 [inline]
 pub fn lag1_autocorrelation<T>(data []T) T {
 	data_mean := mean<T>(data)
 	return lag1_autocorrelation_mean<T>(data, data_mean)
 }
 
-// Compute the lag-1 autocorrelation of a dataset using
+// lag1_autocorrelation_mean calculates the correlation between values that are one time period apart
+// of a dataset, using
 // the recurrence relation
 pub fn lag1_autocorrelation_mean<T>(data []T, mean T) T {
 	if data.len == 0 {
@@ -427,6 +424,7 @@ pub fn lag1_autocorrelation_mean<T>(data []T, mean T) T {
 	return q / v
 }
 
+// kurtosis calculates the measure of the 'tailedness' of the data by finding mean and standard of deviation
 [inline]
 pub fn kurtosis<T>(data []T) T {
 	data_mean := mean<T>(data)
@@ -434,7 +432,7 @@ pub fn kurtosis<T>(data []T) T {
 	return kurtosis_mean_stddev<T>(data, data_mean, sd)
 }
 
-// Takes a dataset and finds the kurtosis
+// kurtosis_mean_stddev calculates the measure of the 'tailedness' of the data
 // using the fourth moment the deviations, normalized by the sd
 pub fn kurtosis_mean_stddev<T>(data []T, mean T, sd T) T {
 	mut avg := T(0) // find the fourth moment the deviations, normalized by the sd
@@ -449,6 +447,7 @@ pub fn kurtosis_mean_stddev<T>(data []T, mean T, sd T) T {
 	return avg - T(3.0)
 }
 
+// skew calculates the mean and standard of deviation to find the skew from the data
 [inline]
 pub fn skew<T>(data []T) T {
 	data_mean := mean<T>(data)
@@ -456,6 +455,7 @@ pub fn skew<T>(data []T) T {
 	return skew_mean_stddev<T>(data, data_mean, sd)
 }
 
+// skew_mean_stddev calculates the skewness of data
 pub fn skew_mean_stddev<T>(data []T, mean T, sd T) T {
 	mut skew := T(0) // find the sum of the cubed deviations, normalized by the sd.
 	/*
diff --git a/vlib/math/unsigned/uint256.v b/vlib/math/unsigned/uint256.v
index 8b1d6dc0ad..37645b6717 100644
--- a/vlib/math/unsigned/uint256.v
+++ b/vlib/math/unsigned/uint256.v
@@ -14,26 +14,32 @@ pub mut:
 	hi Uint128 = uint128_zero // upper 128 bit half
 }
 
+// uint256_from_128 creates a new `unsigned.Uint256` from the given Uint128 value
 pub fn uint256_from_128(v Uint128) Uint256 {
 	return Uint256{v, uint128_zero}
 }
 
+// uint256_from_64 creates a new `unsigned.Uint256` from the given u64 value
 pub fn uint256_from_64(v u64) Uint256 {
 	return uint256_from_128(uint128_from_64(v))
 }
 
+// is_zero checks if specified Uint256 is zero
 pub fn (u Uint256) is_zero() bool {
 	return u.lo.is_zero() && u.hi.is_zero()
 }
 
+// equals checks if the two Uint256 values match one another
 pub fn (u Uint256) equals(v Uint256) bool {
 	return u.lo.equals(v.lo) && u.hi.equals(v.hi)
 }
 
-pub fn (u Uint256) euqals_128(v Uint128) bool {
+// equals_128 checks if the Uint256 value matches the Uint128 value
+pub fn (u Uint256) equals_128(v Uint128) bool {
 	return u.lo.equals(v) && u.hi.is_zero()
 }
 
+// cmp returns 1 if u is greater than v, -1 if u is less than v, or 0 if equal
 pub fn (u Uint256) cmp(v Uint256) int {
 	h := u.hi.cmp(v.hi)
 	if h != 0 {
@@ -42,6 +48,7 @@ pub fn (u Uint256) cmp(v Uint256) int {
 	return u.lo.cmp(v.lo)
 }
 
+// cmp_128 returns 1 if u is greater than v (Uint128), -1 if u is less than v, or 0 if equal
 pub fn (u Uint256) cmp_128(v Uint128) int {
 	if !u.hi.is_zero() {
 		return 1
@@ -49,34 +56,42 @@ pub fn (u Uint256) cmp_128(v Uint128) int {
 	return u.lo.cmp(v)
 }
 
+// not returns a binary negation of the Uint256 value
 pub fn (u Uint256) not() Uint256 {
 	return Uint256{u.lo.not(), u.hi.not()}
 }
 
+// and returns a Uint256 value that is the bitwise and of u and v
 pub fn (u Uint256) and(v Uint256) Uint256 {
 	return Uint256{u.lo.and(v.lo), u.hi.and(v.hi)}
 }
 
+// and_128 returns a Uint256 value that is the bitwise and of u and v, which is a Uint128
 pub fn (u Uint256) and_128(v Uint128) Uint256 {
 	return Uint256{u.lo.and(v), uint128_zero}
 }
 
+// or_ returns a Uint256 value that is the bitwise or of u and v
 pub fn (u Uint256) or_(v Uint256) Uint256 {
 	return Uint256{u.lo.or_(v.lo), u.hi.or_(v.hi)}
 }
 
+// or_128 returns a Uint256 value that is the bitwise or of u and v, which is a Uint128
 pub fn (u Uint256) or_128(v Uint128) Uint256 {
 	return Uint256{u.lo.or_(v), u.hi}
 }
 
+// xor returns a Uint256 value that is the bitwise xor of u and v
 pub fn (u Uint256) xor(v Uint256) Uint256 {
 	return Uint256{u.lo.xor(v.lo), u.hi.xor(v.hi)}
 }
 
+// xor_128 returns a Uint256 value that is the bitwise xor of u and v, which is a Uint128
 pub fn (u Uint256) xor_128(v Uint128) Uint256 {
 	return Uint256{u.lo.xor(v), u.hi}
 }
 
+// add_256 - untested
 pub fn add_256(x Uint256, y Uint256, carry u64) (Uint256, u64) {
 	mut sum := Uint256{}
 	mut carry_out := u64(0)
@@ -85,6 +100,7 @@ pub fn add_256(x Uint256, y Uint256, carry u64) (Uint256, u64) {
 	return sum, carry_out
 }
 
+// sub_256 - untested
 pub fn sub_256(x Uint256, y Uint256, borrow u64) (Uint256, u64) {
 	mut diff := Uint256{}
 	mut borrow_out := u64(0)
@@ -93,6 +109,7 @@ pub fn sub_256(x Uint256, y Uint256, borrow u64) (Uint256, u64) {
 	return diff, borrow_out
 }
 
+// mul_256 - untested
 pub fn mul_256(x Uint256, y Uint256) (Uint256, Uint256) {
 	mut hi := Uint256{}
 	mut lo := Uint256{}
@@ -114,31 +131,37 @@ pub fn mul_256(x Uint256, y Uint256) (Uint256, Uint256) {
 	return hi, lo
 }
 
+// add returns a Uint256 that is equal to u+v
 pub fn (u Uint256) add(v Uint256) Uint256 {
 	sum, _ := add_256(u, v, 0)
 	return sum
 }
 
+// overflowing_add - untested
 pub fn (u Uint256) overflowing_add(v Uint256) (Uint256, u64) {
 	sum, overflow := add_256(u, v, 0)
 	return sum, overflow
 }
 
+// add_128 returns a Uint256 that is equal to u+v, v being a Uint128
 pub fn (u Uint256) add_128(v Uint128) Uint256 {
 	lo, c0 := add_128(u.lo, v, 0)
 	return Uint256{lo, u.hi.add_64(c0)}
 }
 
+// sub returns a Uint256 that is equal to u-v
 pub fn (u Uint256) sub(v Uint256) Uint256 {
 	diff, _ := sub_256(u, v, 0)
 	return diff
 }
 
+// sub_128 returns a Uint256 that is equal to u-v, v being a Uint128
 pub fn (u Uint256) sub_128(v Uint128) Uint256 {
 	lo, b0 := sub_128(u.lo, v, 0)
 	return Uint256{lo, u.hi.sub_64(b0)}
 }
 
+// mul returns a Uint256 that is eqal to u*v
 pub fn (u Uint256) mul(v Uint256) Uint256 {
 	mut hi, mut lo := mul_128(u.lo, v.lo)
 	hi = hi.add(u.hi.mul(v.lo))
@@ -146,11 +169,13 @@ pub fn (u Uint256) mul(v Uint256) Uint256 {
 	return Uint256{lo, hi}
 }
 
+// mul_128 returns a Uint256 that is eqal to u*v, v being a Uint128
 pub fn (u Uint256) mul_128(v Uint128) Uint256 {
 	hi, lo := mul_128(u.lo, v)
 	return Uint256{lo, hi.add(u.hi.mul(v))}
 }
 
+// quo_rem - untested
 pub fn (u Uint256) quo_rem(v Uint256) (Uint256, Uint256) {
 	if v.hi.is_zero() {
 		q, r := u.quo_rem_128(v.lo)
@@ -173,6 +198,7 @@ pub fn (u Uint256) quo_rem(v Uint256) (Uint256, Uint256) {
 	return q, r
 }
 
+// quo_rem_128 - untested
 pub fn (u Uint256) quo_rem_128(v Uint128) (Uint256, Uint128) {
 	if u.hi.cmp(v) < 0 {
 		lo, r := div_128(u.hi, u.lo, v)
@@ -184,6 +210,7 @@ pub fn (u Uint256) quo_rem_128(v Uint128) (Uint256, Uint128) {
 	return Uint256{lo, hi}, r2
 }
 
+// quo_rem_64 - untested
 pub fn (u Uint256) quo_rem_64(v u64) (Uint256, u64) {
 	mut q := Uint256{}
 	mut r := u64(0)
@@ -192,6 +219,7 @@ pub fn (u Uint256) quo_rem_64(v u64) (Uint256, u64) {
 	return q, r
 }
 
+// rsh returns a new Uint256 that has been right bit shifted
 pub fn (u Uint256) rsh(n_ u32) Uint256 {
 	mut n := n_
 	if n > 128 {
@@ -205,6 +233,7 @@ pub fn (u Uint256) rsh(n_ u32) Uint256 {
 	return Uint256{Uint128{u.lo.lo >> n | u.lo.hi << (64 - n), u.lo.hi >> n | u.hi.lo << (64 - n)}, Uint128{u.hi.lo >> n | u.hi.hi << (64 - n), u.hi.hi >> n}}
 }
 
+// lsh returns a new Uint256 that has been left bit shifted
 pub fn (u Uint256) lsh(n_ u32) Uint256 {
 	mut n := n_
 	if n > 128 {
@@ -219,36 +248,43 @@ pub fn (u Uint256) lsh(n_ u32) Uint256 {
 	return Uint256{Uint128{u.lo.lo << n, u.lo.hi << n | u.lo.lo >> (64 - n)}, Uint128{u.hi.lo << n | u.lo.hi >> (64 - n), u.hi.hi << n | u.hi.lo >> (64 - n)}}
 }
 
+// div - untested
 pub fn (u Uint256) div(v Uint256) Uint256 {
 	q, _ := u.quo_rem(v)
 	return q
 }
 
+// div_128 - untested
 pub fn (u Uint256) div_128(v Uint128) Uint256 {
 	q, _ := u.quo_rem_128(v)
 	return q
 }
 
+// div_64 - untested
 pub fn (u Uint256) div_64(v u64) Uint256 {
 	q, _ := u.quo_rem_64(v)
 	return q
 }
 
+// mod - untested
 pub fn (u Uint256) mod(v Uint256) Uint256 {
 	_, r := u.quo_rem(v)
 	return r
 }
 
+// mod_128 - untested
 pub fn (u Uint256) mod_128(v Uint128) Uint128 {
 	_, r := u.quo_rem_128(v)
 	return r
 }
 
+// mod_64 - untested
 pub fn (u Uint256) mod_64(v u64) u64 {
 	_, r := u.quo_rem_64(v)
 	return r
 }
 
+// rotate_left returns a new Uint256 that has been left bit shifted
 pub fn (u Uint256) rotate_left(k int) Uint256 {
 	mut n := u32(k) & 255
 	if n < 64 {
@@ -283,10 +319,12 @@ pub fn (u Uint256) rotate_left(k int) Uint256 {
 	return Uint256{Uint128{u.lo.hi << n | u.lo.lo >> (64 - n), u.hi.lo << n | u.lo.hi >> (64 - n)}, Uint128{u.hi.hi << n | u.hi.lo >> (64 - n), u.lo.lo << n | u.hi.hi >> (64 - n)}}
 }
 
+// rotate_right returns a new Uint256 that has been right bit shifted
 pub fn (u Uint256) rotate_right(k int) Uint256 {
 	return u.rotate_left(-k)
 }
 
+// len returns the length of the binary value without the leading zeros
 pub fn (u Uint256) len() int {
 	if !u.hi.is_zero() {
 		return 128 + u.hi.len()
@@ -294,6 +332,7 @@ pub fn (u Uint256) len() int {
 	return u.lo.len()
 }
 
+// leading_zeros returns the number of 0s at the beginning of the binary value of the Uint256 value [0, 256]
 pub fn (u Uint256) leading_zeros() int {
 	if !u.hi.is_zero() {
 		return u.hi.leading_zeros()
@@ -301,6 +340,7 @@ pub fn (u Uint256) leading_zeros() int {
 	return 128 + u.lo.leading_zeros()
 }
 
+// trailing_zeros returns the number of 0s at the end of the binary value of the Uint256 value [0,256]
 pub fn (u Uint256) trailing_zeros() int {
 	if !u.lo.is_zero() {
 		return u.lo.trailing_zeros()
@@ -309,10 +349,12 @@ pub fn (u Uint256) trailing_zeros() int {
 	return 128 + u.hi.trailing_zeros()
 }
 
+// ones_count returns the number of ones in the binary value of the Uint256 value
 pub fn (u Uint256) ones_count() int {
 	return u.lo.ones_count() + u.hi.ones_count()
 }
 
+// str returns the decimal representation of the unsigned integer
 pub fn (u_ Uint256) str() string {
 	mut u := u_
 	if u.hi.is_zero() {
@@ -339,6 +381,7 @@ pub fn (u_ Uint256) str() string {
 	return ''
 }
 
+// uint256_from_dec_str creates a new `unsigned.Uint256` from the given string if possible
 pub fn uint256_from_dec_str(value string) ?Uint256 {
 	mut res := unsigned.uint256_zero
 	for b_ in value.bytes() {