some cosmetics

Signed-off-by: Helge Wehder <[email protected]>

Author: myteron

docs/Secure-Coding-Guide-for-Python/CWE-703/CWE-230/README.md

@@ -1,9 +1,9 @@
 # CWE-230: Improper Handling of Missing Values
 
-In python, some datasets use NaN (not-a-number) to represent the missing data. This can be problematic as the NaN values are unordered. The NaN value should be stripped before as they can cause surprising or undefined behaviours in the statistics functions that sort or count occurrences [[2024 doc.python.org]](https://docs.python.org/3/library/statistics.html) Any ordered comparison of a number to a not-a-number value are False. A counter-intuitive implication is that not-a-number values are not equal to themselves.
+In python, some datasets use `NaN` (not-a-number) to represent the missing data. This can be problematic as the `NaN` values are unordered. The `NaN` value should be stripped before as they can cause surprising or undefined behaviours in the statistics functions that sort or count occurrences [[2024 doc.python.org]](https://docs.python.org/3/library/statistics.html) Any ordered comparison of a number to a not-a-number value are `False`. A counter-intuitive implication is that `not-a-number` values are not equal to themselves.
 
 This behavior is compliant with IEEE 754[[2024 Wikipedia]](https://en.wikipedia.org/wiki/IEEE_754) a hardware induced compromise.
-The [example01.py](example01.py) code demonstrates various comparisons of float('NaN') all resulting in False
+The [example01.py](example01.py) code demonstrates various comparisons of `float('NaN')` all resulting in `False`.
 
 ```python
 """ Code Example """
@@ -23,9 +23,7 @@ print(foo == float("NaN") or
 
 ## Non-Compliant Code Example
 
-This noncompliant code example [[2024 docs.python.org]](https://docs.python.org/3/reference/expressions.html#value-comparisons) attempts a direct comparison with NaN in
-
-_value == float("NaN").
+This noncompliant code example [[2024 docs.python.org]](https://docs.python.org/3/reference/expressions.html#value-comparisons) attempts a direct comparison with `NaN` in `_value == float("NaN")`.
 
 *[noncompliant01.py](noncompliant01.py):*
 
@@ -53,13 +51,13 @@ print(balance_is_positive("NaN"))
 
 ```
 
-The balance_is_positive method returns True for all 3 cases instead of throwing an ValureError exception for balance_is_positive("NaN")
+The `balance_is_positive` method returns `True` for all 3 cases instead of throwing an `ValureError` exception for `balance_is_positive("NaN")`.
 
 ## Compliant Solution
 
 The `compliant01.py` the method Decimal.quantize is used to gain control over known rounding errors in floating point values.
 
-The decision by the balance_is_positive method is to ROUND_DOWN instead of the default ROUND_HALF_EVEN.
+The decision by the balance_is_positive method is to `ROUND_DOWN` instead of the default `ROUND_HALF_EVEN`.
 
 *[compliant01.py](compliant01.py):*
 
@@ -88,9 +86,9 @@ print(balance_is_positive("NaN"))
 
 ```
 
-Decimal throws a decimal.InvalidOperation for NaN values, the controlled rounding causes only "0.01" to return True.
+`Decimal` throws a `decimal.InvalidOperation` for `NaN` values, the controlled rounding causes only `"0.01"` to return `True`.
 
-In `compliant02.py` we use the math.isnan to very if the value passed is a valid float value.
+In `compliant02.py` we use the math.isnan to very if the value passed is a valid `float` value.
 
 *[compliant02.py](compliant02.py):*
 
@@ -122,7 +120,7 @@ print(balance_is_positive("NaN"))
 
 ```
 
-The balance_is_poitive method will raise an ValueError for NaN values.
+The `balance_is_poitive` method will raise an `ValueError` for `NaN` values.
 
 ## Automated Detection
 

docs/Secure-Coding-Guide-for-Python/readme.md

@@ -92,7 +92,7 @@ It is __not production code__ and requires code-style or python best practices t
 
 |[CWE-703: Improper Check or Handling of Exceptional Conditions](https://cwe.mitre.org/data/definitions/703.html)|Prominent CVE|
 |:----------------------------------------------------------------|:----|
-|[CWE-230: Improper Handling of Missing Values](CWE-703/CWE-230/.)||
+|[CWE-230: Improper Handling of Missing Values](CWE-703/CWE-230/README.md)||
 |[CWE-252: Unchecked Return Value](CWE-703/CWE-252/README.md)||
 |[CWE-390: Detection of Error Condition without Action](CWE-703/CWE-390/README.md)||
 |[CWE-392: Missing Report of Error Condition](CWE-703/CWE-392/README.md)||