What happens in a situation of overflow in floating-point representation?

In the context of overflow in floating-point representation, the correct statement is that a positive exponent becomes too large to fit in the exponent field. This occurs when calculations result in a value that's outside the representable range of the floating-point format, specifically in the case of normalized numbers where the exponent exceeds the maximum value that can be stored in its designated field.

When a floating-point value is computed and the exponent exceeds the maximum allowable value for representation, the system cannot represent the result accurately. This is a crucial aspect of floating-point arithmetic, as it can lead to significant errors in computations if not properly handled. In this scenario, it is the positive exponent that causes the overflow since its growing limit leads to a situation where it cannot be contained within the prescribed bits of the exponent field.

Thus, it is essential to grasp that overflow is tied to the limitations of the floating-point format in terms of both precision and range. Understanding how exponents can factor into overflow situations helps in grasping the constraints and possible errors in numeric computations in computer systems.