Final answer:
Big endian representation in computers can have the disadvantage of requiring word address boundaries. The claim that big endian representation requires words to be written on word address boundaries is false; both big endian and little endian systems generally have this alignment requirement for performance optimization.
Step-by-step explanation:
Big endian representation refers to the way in which computer systems store and retrieve the bytes of data. In big endian representation, the most significant byte is stored first in memory. One disadvantage of big endian representation is that most computers require the bytes to be written on word address boundaries. This means that the memory address must be divisible by the word size, which can lead to wasted memory if the data is not aligned properly.
The claim that big endian representation requires words to be written on word address boundaries is false; both big endian and little endian systems generally have this alignment requirement for performance optimization.
The statement that one disadvantage to big endian representation is that most computers require words to be written on word address boundaries is false. The endianness of a system refers to the order of byte significance in memory. Big endian and little endian are two different methods of storing the most significant byte of a word of data in computer memory. Big endian stores the most significant byte first, at the lowest memory address, while little endian stores it last. The requirement for words to be aligned on word boundaries in memory is not inherently linked to big endian representation, but is often a general requirement of many CPU architectures to optimize performance. This requirement for word alignment applies to both big endian and little endian systems.