Floating Point Comparison with Incorrect Operator
The code performs a comparison such as an equality test between two float (floating point) values, but it uses comparison operators that do not account for the possibility of loss of precision.
Numeric calculation using floating point values can generate imprecise results because of rounding errors. As a result, two different calculations might generate numbers that are mathematically equal, but have slightly different bit representations that do not translate to the same mathematically-equal values. As a result, an equality test or other comparison might produce unexpected results.
This issue can prevent the software from running reliably. If the relevant code is reachable by an attacker, then this reliability problem might introduce a vulnerability.
Weaknesses in this category are related to the CISQ Quality Measures for Reliability. Presence of these weaknesses could reduce the reliability of the software.
Weaknesses in this category are related to the CISQ Quality Measures for Reliability, as documented in 2016 with the Automated Source Code CISQ Reliability Measure (AS...
Weaknesses in this category are related to improper calculation or conversion of numbers.
This view (slice) covers all the elements in CWE.
CWE identifiers in this view (slice) are quality issues that only indirectly make it easier to introduce a vulnerability and/or make the vulnerability more difficult t...
CWE identifiers in this view are weaknesses that do not have associated Software Fault Patterns (SFPs), as covered by the CWE-888 view. As such, they represent gaps in...