Find the number of bytes used to store an expression:

Plot the ByteCount for different types of expressions:

Growth of storage sizes for a sequence of integrals:

Make Simplify pick expressions with minimum ByteCount:

LeafCount does not account for sizes of numbers:

Show that lists with symbolic elements require more storage than lists of numbers:

On the computer system used for this example, each ordinary integer takes 4 bytes to store:

Approximate numbers take double:

ByteCount does not account for sharing in the actual storage of expressions:

Symbols are effectively always shared, so they give 0 byte count:

For ASCII strings, ByteCount on average increases by 1 for each character:

Unicode characters on average add 2 bytes each:

For integers, there is a jump in going beyond machine numbers:

The average rate of increase is about 0.4 bytes per decimal digit:

Each element of a list effectively adds an internal pointer:

MemoryConstrained aborts the generation of expressions that exceed a specified ByteCount:

Small changes can have large effects on memory usage:

The presence of the exact 0 prevents the data from being packed:

ByteCount only gives the size of handles to external objects: