![]() ![]() ![]() Perhaps you've heard the statement that floating point values cannot be guaranteed to be accurate. ![]() Now that you know how JavaScript supports the single numerical type and how its storage works from the smallest and largest integer perspective, turn your attention to the initial problem with decimals: 0.1 + 0.2 =. In this case, you simply reverse how the bits are flipped with respect to the largest safe integer value. In JavaScript, there's a simple way to access this number and its negative counterpart with the MAX_SAFE_INTEGER and MIN_SAFE_INTEGER constants hosted in the Number Prototype, as shown in Figure 3.įigure 3: The Min and Max Safe Integer Constants provide quick access to the smallest and largest integers that can be safely relied upon in JavaScript. This 10 th bit however, under the storage scheme illustrated in Figure 2 is in the bit range reserved for the exponent. Reviewing the IEEE 754 standard, the largest integer that can safely be relied upon to be accurately stored is expressed as (2 53) ? 1 or 9,007,199,254,740,991. The question to ask is “how are 64-bit floating point numbers stored?” The answer is that 64-bit floating point storage is divided into three parts, as shown in Figure 2.įigure 2: The IEEE 754 Standard for storage of 64-bit floating point numbers Because I'm talking about a 64-bit (binary) system, base 2 applies. JavaScript supports one mathematical type, 64-bit floating point numbers. Before you can understand how JavaScript behaves, you must first address what JavaScript is and more specifically what JavaScript is in the mathematical context and what numerical data types JavaScript directly supports. This would also be an incorrect assumption. Your next assumption may be that JavaScript can't do math. In C, C#, and other similarly situated languages, the result of 0.1 + 0. Figure 1 shows a simple math problem.įigure 1: JSFiddle output illustrating that. To begin to answer that question, let's see JavaScript in action with a simple task, adding two values and testing for equality. The next question to address is WHY this is the case. Your second assumption may be that JavaScript handles mathematical operations just like your primary language. Your first assumption is probably that JavaScript has an integer type. If you're a developer in a place where JavaScript is not the primary language and you're tasked with something that requires JavaScript, whether on the client or server, you may have some already baked assumptions based on your primary experience with C, C#, VB, Ruby, Python, etc. JavaScript's only native numeric type is the double-precision (floating point) 64-bit type. In this edition's column, I take you through some of JavaScript's mathematical idiosyncrasies and how to work around them. Later in this column, I'll illustrate how C# and JavaScript, as far as floating-point numbers are concerned, behave in the same way. JavaScript often gets bashed because “It can't perform math correctly.” If these same criteria were to be applied to C#, you'd reach the same conclusion. In fact, for the programming world at large, this isn't a new issue. For the JavaScript world at large, this isn't a new issue. Depending on what mathematical requirements your application has, you may have to take special care to ensure that your operations return what you expect with respect to floating point (double) precision.
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