Due to the nature of floating path arithmetic, almost all floating point arithmetic is imprecise. The computer can only maintain a finite number of digits. As a result, it is impossible to precisely represent repeating binary-representation values, such as 1/3 or 1/5.
When precise computations are necessary, consider alternative representations that may be able to completely represent your values. For example, if you are doing arithmetic on decimal values and need an exact rounding mode based on decimal values, represent your values in decimal instead of using floating point, which uses binary representation.
When precise computation is necessary, carefully and methodically evaluate the cumulative error of the computations, regardless of whether decimal or binary is used, to ensure that the resulting error is within tolerances. Consider using numerical analysis to properly understand the numerical properties of the problem. A useful introduction is Goldberg 91.
Risk Analysis
Recommendation |
Severity |
Likelihood |
Remediation Cost |
Priority |
Level |
|---|---|---|---|---|---|
FLP00-A |
1 (low) |
2 (probable) |
2 (medium) |
P4 |
L3 |
Search for vulnerabilities resulting from the violation of this rule on the CERT website
References
[[IEEE 754 2006]]
[[ISO/IEC JTC1/SC22/WG11]]
[[Goldberg 91]]