Statically-sized variables (everything except mapping and dynamically-sized array types) are laid out contiguously in storage starting from position ``0``. Multiple items that need less than 32 bytes are packed into a single storage slot if possible, according to the following rules:
- The first item in a storage slot is stored lower-order aligned.
- Elementary types use only that many bytes that are necessary to store them.
- If an elementary type does not fit the remaining part of a storage slot, it is moved to the next storage slot.
- Structs and array data always start a new slot and occupy whole slots (but items inside a struct or array are packed tightly according to these rules).
recursively applying this rule for mappings to mappings or arrays of arrays). For a dynamic array, this slot stores the number of elements in the array (byte arrays and strings are an exception here, see below). For a mapping, the slot is unused (but it is needed so that two equal mappings after each other will use a different hash distribution).
``bytes`` and ``string`` store their data in the same slot where also the length is stored if they are short. In particular: If the data is at most ``31`` bytes long, it is stored in the higher-order bytes (left aligned) and the lowest-order byte stores ``length * 2``. If it is longer, the main slot stores ``length * 2 + 1`` and the data is stored as usual in ``keccak256(slot)``.
Scratch space can be used between statements (ie. within inline assembly).
Solidity always places new objects at the free memory pointer and memory is never freed (this might change in the future).
..warning::
There are some operations in Solidity that need a temporary memory area larger than 64 bytes and therefore will not fit into the scratch space. They will be placed where the free memory points to, but given their short lifecycle, the pointer is not updated. The memory may or may not be zeroed out. Because of this, one shouldn't expect the free memory to be zeroed out.
The Solidity optimizer operates on assembly, so it can be and also is used by other languages. It splits the sequence of instructions into basic blocks at ``JUMPs`` and ``JUMPDESTs``. Inside these blocks, the instructions are analysed and every modification to the stack, to memory or storage is recorded as an expression which consists of an instruction and a list of arguments which are essentially pointers to other expressions. The main idea is now to find expressions that are always equal (on every input) and combine them into an expression class. The optimizer first tries to find each new expression in a list of already known expressions. If this does not work, the expression is simplified according to rules like ``constant + constant = sum_of_constants`` or ``X * 1 = X``. Since this is done recursively, we can also apply the latter rule if the second factor is a more complex expression where we know that it will always evaluate to one. Modifications to storage and memory locations have to erase knowledge about storage and memory locations which are not known to be different: If we first write to location x and then to location y and both are input variables, the second could overwrite the first, so we actually do not know what is stored at x after we wrote to y. On the other hand, if a simplification of the expression x - y evaluates to a non-zero constant, we know that we can keep our knowledge about what is stored at x.
At the end of this process, we know which expressions have to be on the stack in the end and have a list of modifications to memory and storage. This information is stored together with the basic blocks and is used to link them. Furthermore, knowledge about the stack, storage and memory configuration is forwarded to the next block(s). If we know the targets of all ``JUMP`` and ``JUMPI`` instructions, we can build a complete control flow graph of the program. If there is only one target we do not know (this can happen as in principle, jump targets can be computed from inputs), we have to erase all knowledge about the input state of a block as it can be the target of the unknown ``JUMP``. If a ``JUMPI`` is found whose condition evaluates to a constant, it is transformed to an unconditional jump.
As the last step, the code in each block is completely re-generated. A dependency graph is created from the expressions on the stack at the end of the block and every operation that is not part of this graph is essentially dropped. Now code is generated that applies the modifications to memory and storage in the order they were made in the original code (dropping modifications which were found not to be needed) and finally, generates all values that are required to be on the stack in the correct place.
These steps are applied to each basic block and the newly generated code is used as replacement if it is smaller. If a basic block is split at a ``JUMPI`` and during the analysis, the condition evaluates to a constant, the ``JUMPI`` is replaced depending on the value of the constant, and thus code like
* Use shorter types for struct elements and sort them such that short types are grouped together. This can lower the gas costs as multiple ``SSTORE`` operations might be combined into a single (``SSTORE`` costs 5000 or 20000 gas, so this is what you want to optimise). Use the gas price estimator (with optimiser enabled) to check!
* Initialize storage structs with a single assignment: ``x = MyStruct({a: 1, b: 2});``
..note::
If the storage struct has tightly packed properties, initialize it with separate assignments: ``x.a = 1; x.b = 2;``. In this way it will be easier for the optimizer to update storage in one go, thus making assignment cheaper.
-``require(bool condition)``: abort execution and revert state changes if condition is ``false`` (use for malformed input or error in external component)
-``ecrecover(bytes32 hash, uint8 v, bytes32 r, bytes32 s) returns (address)``: recover address associated with the public key from elliptic curve signature, return zero on error
-``addmod(uint x, uint y, uint k) returns (uint)``: compute ``(x + y) % k`` where the addition is performed with arbitrary precision and does not wrap around at ``2**256``. Assert that ``k != 0`` starting from version 0.5.0.
-``mulmod(uint x, uint y, uint k) returns (uint)``: compute ``(x * y) % k`` where the multiplication is performed with arbitrary precision and does not wrap around at ``2**256``. Assert that ``k != 0`` starting from version 0.5.0.
