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# 5.5. Local Memory¶

## 5.5.1. Local Memory¶

### 5.5.1.1. Thanks For The Memory: Allocation and Deallocation¶

Local variables are the programming structure everyone uses but no one thinks about. You think about them a little when first mastering the syntax. But after a few weeks, the variables are so automatic that you soon forget to think about how they work. This situation is a credit to modern programming languages—most of the time variables appear automatically when you need them, and they disappear automatically when you are finished. For basic programming, this is a fine situation. However, for advanced programming, it’s going to be useful to have an idea of how variables work.

Variables represent storage space in the computer’s memory. Each variable presents a convenient name like length or sum in the source code. Behind the scenes at runtime, each variable uses an area of the computer’s memory to store its value. It is not the case that every variable in a program has a permanently assigned area of memory. Instead, modern languages are smart about giving memory to a variable only when necessary. The terminology is that a variable is allocated when it is given an area of memory to store its value. While the variable is allocated, it can operate as a variable in the usual way to hold a value. A variable is deallocated when the system reclaims the memory from the variable, so it no longer has an area to store its value. For a variable, the period of time from its allocation until its deallocation is called its lifetime. Within a program, the parts of the program that can see and access the variable are its scope.

The most common variables you use are local variables within functions such as the variables num and result in the following function. All of the local variables and parameters taken together are called its local storage or just its “locals”.

// Local storage example
int Square(int num) {
int result;
result = num * num;
return result;
}

// Local storage example
int Square(int num) {
int result;
result = num * num;
return result;
}


The variables are called “local” to capture the idea that their lifetime is tied to the function where they are declared. Whenever the function runs, its local variables are allocated. When the function exits, its locals are deallocated. For the above example, that means that when the Square() function is called, local storage is allocated for num and result. Statements like result = num * num; in the function use the local storage. When the function finally exits, its local storage is deallocated.

Here is a more detailed version of the rules of local storage:

1. When a function is called, memory is allocated for all of its locals. In other words, when the flow of control hits the starting { symbol for the function, all of its locals are allocated memory. Parameters such as num and local variables such as result in the above example both count as locals. The only difference between parameters and local variables is that parameters start out with a value copied from the caller while local variables start with initial values. Our examples mostly use simple int variables, however local allocation works for any type, including arrays and reference variables. These can also be allocated locally.

2. The memory for the locals continues to be allocated so long as the thread of control is within the owning function. Locals continue to exist even if the function temporarily passes off the thread of control by calling another function. The locals exist undisturbed through all of this.

3. Finally, when the function finishes and exits, its locals are deallocated. Does this make sense? Suppose the locals were somehow to continue to exist—how could the code even refer to them? The names like num and result only make sense within the body of Square() anyway. Once the flow of control leaves that function body, there is no longer a way to refer to the locals even if they were allocated. That locals are available (“scoped”) only within their owning function is known as lexical scoping. Pretty much all languages do it that way now.

Here is a simple example of the lifetime of local storage.

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Here is a larger example that shows how the simple rule “the locals are allocated when their function begins running and are deallocated when it exits” can build more complex behavior. You will need a firm grasp of how local allocation works to understand the material in later modules. The following slides show the sequence of allocations and deallocations that result when the function X() calls the function Y() twice.

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The slideshow showed how the sequence of the locals are allocated and deallocated. Note how in the slideshow we “stacked up” the local variables that are created when a function is called. This is actually how local variables are typically implemented by any programming language’s runtime environment. The local variables are contained in something called the runtime stack. In effect, the slideshow is showing the operation over time of the runtime stack as this example is being executed.

### 5.5.1.2. Local Parameters¶

Local variables are tightly associated with their function—they are used there and nowhere else. Only the X() code can refer to its a and b. Only the Y() code can refer to its p and q. This independence of local storage is the root cause of both its advantages and disadvantages.

Locals are great for 90% of a program’s memory needs:

• Convenient. Locals satisfy a convenient need—functions often need some temporary memory which exists only during the function’s computation. Local variables conveniently provide this sort of temporary, independent memory.

• Efficient. Relative to other memory use techniques, locals are efficient. Allocating and deallocating them is time efficient (fast) and they are space efficient in the way they use and recycle memory

• Local Copies. Local parameters are basically local copies of the information from the caller. This is also known as pass by value. Parameters are local variables which are initialized with an assignment (=) operation from the caller. The caller is not “sharing” the parameter value with the callee in the pointer sense—the callee is getting its own copy. This has the advantage that the callee can change its local copy without affecting the caller. (Such as with the p parameter in the above example.) This independence is good since it keeps the operation of the caller and callee functions separate which follows the rules of good software engineering—keep separate components as independent as possible.

There are two disadvantages of Locals:

1. Short Lifetime. Their allocation and deallocation schedule (their “lifetime”) is very strict. Sometimes a program needs memory which continues to be allocated even after the function which originally allocated it has exited. Local variables will not work since they are deallocated automatically when their owning function exits. This problem will be solved in a later section with heap memory.

2. Restricted Communication. Since locals are copies of the caller parameters, they do not provide a means of communication from the callee back to the caller. This is the flip side of the “independence” advantage—its not always and advantage. Also, sometimes making copies of a value is undesirable for other reasons. We will see the solution to this problem in the next module.

### 5.5.1.5. Synonyms For “Local”¶

Local variables are also known as automatic variables since their allocation and deallocation is done automatically as part of the function call mechanism. Local variables are also sometimes known as stack variables because, at a low level, languages almost always implement local variables using a stack structure in memory.

### 5.5.1.6. Local Memory Summary¶

Locals are very convenient for what they do—providing convenient and efficient memory for a function which exists only so long as the function is executing. Locals have two deficiencies which we will address in the following section—how a function can communicate back to its caller, and how a function can allocate separate memory with a less constrained lifetime.

### 5.5.1.7. How Does The Function Call Stack Work?¶

You do not need to know how local variables are implemented during a function call to be able to use them correctly, but here is a rough outline of the steps if you are curious. The exact details of the implementation are language and compiler specific. However, the basic structure below approximates the method used by many different systems and languages.

To call a function such as foo(6, x+1):

1. Evaluate the actual parameter expressions, such as the x+1, in the caller’s context.

2. Allocate memory for foo()’s locals by pushing a suitable “local block” of memory onto a runtime call stack dedicated to this purpose. For parameters but not local variables, store the values from step (1) into the appropriate slot in foo()’s local block.

3. Store the caller’s current address of execution (its “return address”) and switch execution to foo().

4. foo() executes with its local block conveniently available at the end of the call stack.

5. When foo() is finished, it exits by popping its locals off the stack and “returns” to the caller using the previously stored return address. Now the caller’s locals are on the end of the stack and it can resume executing.

For the extremely curious, here are other miscellaneous notes on the function call process:

• This is why infinite recursion results in a “Stack Overflow Error”—the code keeps calling and calling resulting in steps (1) (2) (3), (1) (2) (3), but never a step (4). Eventually the call stack literally runs out of memory.

• This is why local variables have specific initial values based on their type. Step (2) just pushes the whole local block in one operation. Each local gets its own area of memory, but the memory will contain whatever the most recent tenant left there. These values will be cleared and a default initial value will be assigned to all of the locals.

• The “local block” is also known as the function’s activation record or stack frame. The entire block can be pushed onto the stack (step 2), in a single CPU operation—it is a very fast operation. Why can this be done in a single CPU operation? Because pushing an activation record is such a fundamental operation for any programming language that CPU designers provide direct support for it.

• For a multithreaded environment, each thread gets its own call stack instead of just having single, global call stack.

• For performance reasons, some languages pass some parameters through registers and others through the stack, so the overall process is complex. However, the apparent the lifetime of the variables will always follow the “stack” model presented here.