Floating-point will quietly corrupt your emissions math, and 0.1 + 0.2 already warned you
Floating-point arithmetic can lead to significant errors in emissions calculations, particularly when reconciling totals. A common example is the discrepancy seen in the sum of 0.1 and 0.2, which results in 0.30000000000000004 instead of the expected 0.3. This issue becomes critical in emissions accounting, where exact figures are necessary for audits and compliance.
- ▪Floating-point errors can accumulate significantly when summing large datasets.
- ▪In emissions accounting, even small discrepancies can lead to audit failures.
- ▪The IEEE 754 standard for floating-point representation can introduce rounding errors that affect calculations.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3923050) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Jeremiah Say Posted on May 23 Floating-point will quietly corrupt your emissions math, and 0.1 + 0.2 already warned you #javascript #programming #math #carbon Every developer has seen this: 0.1 + 0.2 // 0.30000000000000004 Enter fullscreen mode Exit fullscreen mode It's the most-shared bug in programming. You learn it, you nod, you move on — because in most code the error is so far down the decimal that nothing notices. A pixel is off by a billionth. A timer fires a nanosecond late.
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