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CS/COE 0449 static data
创建日期：2024-05-30 16:58:14
标签： COE 0449
static data

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CS/COE 0449
Introduction to
Systems SoftwareManagement
6
Memory
Our Story So Far
You Hear a Voice Whisper: “The Memory Layout is a Lie”
2
Reallocating our thoughts
• A program has several sections:
• Code
• Static data
• Stack
• Heap
• Today, we take a deeper dive at how dynamic
memory is allocated in the heap.
3
currently unused but
available memory
code
static data
heap
stack
~ 0xFFFFFFFF
~ 0x00000000
Potential Layout
(32-bit addresses)
Reallocating our thoughts
• We have looked at malloc and calloc.
• They stake out space in the heap and return an
address.
• Right now, we live in a nice ideal world.
• No other programs are running.
• We have access to all of the memory.
• Muhahahaha!!
• The OS is lying to our program.
• This memory is… virtual... reality.
• We will investigate this lie later in the course.
4
currently unused but
available memory
code
static data
heap
stack
~ 0xFFFFFFFF
~ 0x00000000
Potential Layout
(32-bit addresses)
The World of Allocation
It is a puzzle without any optimal solution. Welcome to computers!
5
A heap of possibilities
• Stack access often does not deviate much.
• We allocate a little bit at a time.
• We allocate and free the memory VERY often.
• Heap allocations have many access patterns that are
possible.
• You might allocate a lot at a time and keep it around for a
long time. Or a short time.
• You might allocate a lot of small things, instead.
• Maybe you do a little bit of everything?
• Often, such patterns are not easy to predict.
• Do you get a big file as input? A small file?
6
currently unused but
available memory
code
static data
heap
stack
~ 0xFFFFFFFF
~ 0x00000000
Potential Layout
(32-bit addresses)
available memory
available memory
available memory
A heaping helping of good luck
• Allocations could happen in a nice order.
• When something is allocated, it can be allocated
after everything else.
• When freed, it makes room for new things.
• IF ONLY.
• I mean, it’s possible… but like…
• the heap and stack are different things for a reason.
7
code
static data
heap
stack
~ 0x00000000
available memoryavailable memory
available memoryavailable memory
Digital potholes… as annoying as real ones
• Small allocations interfere with large ones.
• When small gaps interfere with allocation, this is
called fragmentation.
8
available memory
code
static data
heap
stack
~ 0x00000000
?
Next
Allocation
Ugh
Ugh U
gh
free()
malloc()
if we had omniscience of future
allocations, we could avoid this…
but we can’t know ahead of time!
The worst case
• When you allocate a lot of small things…
• Free every other one…
• And then attempt to allocate a bigger thing…
• Even though there is technically enough memory…
• There is no continuous space.
• Therefore, our naïve malloc will fail.
• We have to come up with some strategy.
9
code
static data
heap
stack
~ 0x00000000
malloc() ? ? ?
Moving is never easy
• Why not move things around??
• A defragmentation process/algorithm
• Moving around something in the heap is hard!
• Any pointers referring to data within a block must be updated.
• Finding these pointers automatically is effectively as difficult
as garbage collection.
• Because of this, moving blocks around is discouraged.
(Easier to solve it another way.)
10
code
static data
heap
stack
~ 0x00000000
malloc() ? ? ?
Moving is NEVER easy
• When blocks move, pointers
to anything within them must be updated.
• This is hard to keep track of!
• C does not check validity of pointers after free()
11
available memory
code
static data
heap
stack
~ 0x00000000
int* my_int
float* my_float
3.14-1.8e-6
42?????
old data: int arr[100]
Stressing it out
• If we allocate a large array it will be allocated on the
heap somewhere.
• Other allocations can also happen, and they go “above”
that array.
• What happens when you need to append a 101st
element to this array?
• Uh oh!
• You will need to allocate more space.
• And then copy the array contents.
• Free the old array.
• How long does that take?
12
available memory
heap
stack
~ 0x00000000
int rr[100]
int arr[200]
fragmentation
old data: int arr[100]
Stressing it out: Big Arrays
• This happens in very practical situations!
• Reallocating means getting rid of a small thing
• And replacing it with a larger thing.
• You could have TiBs of memory and this will be a problem.
• This affects performance: (in terms of writes:)
• Appending item arr[0]: 1
• Appending item arr[1]: 1
• …
• Appending item arr[99]: 1
• Appending item arr[100]: + 1 oh no!
• When you would overflow the buffer…
• You then need to copy all previous values as well.
13
available memory
heap
stack
~ 0x00000000
int rr[100]
old data: int arr[100]
Stressing it out: Performance Consistency
• Big arrays want to be continuous.
• Ensuring continuous space is difficult when you do not know
how much you will ultimately need.
• This is exactly why linked lists exist!
• Since a linked list allocates on every append.
• Each append takes the same amount of time.
• However, everything is a trade-off.
• Dang it!!!
• One cost is extra overhead for metadata.
• Linked list traversal can stress memory caches.
• It means traversing the array is slower.
• However, we will mostly ignore this for now. 14
available memory
heap
stack
~ 0x00000000
int rr[100]
The Linked List
A story about trade-offs.
15
What is a linked list?
• A linked list is a non-continuous data structure representing an ordered list.
• Each item in the linked list is represented by metadata called a node.
• This metadata indirectly refers to the actual data.
• Furthermore, it indirectly refers to at least one other item in the list.
16
Node
Node* next
char* data
typedef struct _Node {
struct _Node* next;
char* data;
} Node; “struct” required since
Node is not technically
defined until after it is
defined!
Keeping ahead of the list.
• Creation of a list occurs when one allocates a single node and tracks it in a
pointer. This is the head of our list (first element.)
17
Node
Node* next
char* data
Node* list
Node* list = (Node*)malloc(sizeof(Node));
list->next = NULL; // NULL is our end-of-list marker
list->data = NULL; // Allocate/copy the data you want
Adding some links to our chain
• If we want to append an item, we can add a node anywhere!
18
“tail”
Node* next
char* data
Node* list
void append(Node* tail, const char* value) {
Node* node = (Node*)malloc(sizeof(Node));
node->next = NULL; // The new end of our list
tail->next = node; // We attach this node to the old last node
node->data = (char*)malloc(strnlen(value, 100) + 1);
strncpy(node->data, value, 100);
}
“node”
Node* next
char* data
Remember the
‘\0’ sentinel!
This is a problem!
Why?
We can add them anywhere!!
• Consider what happens if we update our append to take any Node:
19
void linkedListAppend(Node* curNode, const char* value) {
Node* node = (Node*)malloc(sizeof(Node));
node->next = curNode->next;
curNode->next = node;
node->data = (char*)malloc(strnlen(value, 100) + 1);
strcpy(node->data, value);
}
“curNode”
Node* next
char* data
Node* list
Tail
Node* next
char* data
“node”
Node* next
char* data
We can add them anywhere!!
• This function has very consistent performance (constant time):
• The append always allocates the same amount.
• It always copies the same amount.
• Compare to a big array where you may have to copy the entire thing to
append something new!
void linkedListAppend(Node* curNode, const char* value) {
Node* node = (Node*)malloc(sizeof(Node));
node->next = curNode->next;
curNode->next = node;
node->data = (char*)malloc(strnlen(value, 100) + 1);
strcpy(node->data, value);
}
Traversal… on the other hand…
• Accessing an array element is generally very simple.
• arr[42] is the same as *(arr + 42) because its location is very well-known!
• This is because array items are continuous in memory. Not true for linked lists!
• Here is a function that performs the equivalent for linked lists:
21
Node* linkedListGet(Node* head, size_t index) {
Node* curNode = head;
while(curNode && index) {
index--;
curNode = curNode->next;
}
return curNode;
}
Q: How many times is memory accessed relative to the requested index?
Removing… on the other, other hand!
• One nice thing about linked lists
is their flexibility to changing
shape.
• I used to be able to bend a lot
better, too, when I was in my 20s.
Alas.
• Since we don’t have a way to go
“backward”
• We first find the node we want to
delete (curNode)
• Keeping track of the node of index
– 1 (lastNode)
• Rewire lastNode to cut out
curNode.
22
Node* linkedListDelete(Node* head, size_t index) {
Node* lastNode = NULL;
Node* curNode = head;
while(curNode && index) {
index--;
lastNode = curNode;
curNode = curNode->next;
}
if (!curNode)
return head;
if (!lastNode)
head = curNode->next; // New head is next item
else
lastNode->next = curNode->next; // Orphans item
free(curNode->data);
free(curNode);
return head;
} Returns new head (or old head if unchanged).
Can’t find item at index.
We are deleting the head.
Removing… on the other, other hand!
• This looks complex, but it really is
a simple traversal.
• So it takes to find the item.
• And it performs a simple update
and deallocation. (quick to do)
• A big array, on the other hand.
• It can find the element to remove
immediately.
• However, removing it means
shifting over every item after it left.
• That can be an expensive update!
(Memory is slow!!)
23
Node* linkedListDelete(Node* head, size_t index) {
Node* lastNode = NULL;
Node* curNode = head;
while(curNode && index) {
index--;
lastNode = curNode;
curNode = curNode->next;
}
if (!curNode)
return head;
if (!lastNode)
head = curNode->next; // New head is next item
else
lastNode->next = curNode->next; // Orphans item
free(curNode->data);
free(curNode);
return head;
}
On your own!
Think about the code you would need to do any of the following:
• Delete/free the entire linked list.
• Sort a linked list.
• Append a linked list to an existing one.
• Copy a subset of a linked list to a new list.
Often, operations can be abstracted in such a way that all of these can be written relatively
simply.
Consider the performance of these operations compared to an Array.
24
Linked lists … link you … to the world!
• Consider how much cleaner you can make certain operations if you tracked the
previous node as well.
• This is a doubly linked list.
• This is typically “double-ended” as well: keeping track of both head and tail.
25
Node
Node* next
char* data
Node* prev
Node
Node* next
char* data
Node* prev
Node
Node* next
char* data
Node* prevNode*head
Node*
tail
Seeing the trees through the forest
• A binary tree can be represented by the same nodes as a linked list.
• In this case, you have a left and right child node instead of next and prev.
• The operations are
very different, though.
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COMP2013 IB9X60 INVP001 EMATM0051 COMP220 BLAW1002 E20 TCP8001 ECON61001 EART40005 ECONM1022 MATH 365 MATH 367 ELEC6218 COMP 5812M EDUC 5061M ELEC ENG 1101 equation MATH6174 ST334 C4 EC9570 A33648 EBUS603 ECON47815 stata WFMS0001 PEM102 INF6060 ionically ELECTRICAL MATH 375 MMW 12 MKTG860 ECON60401 ALY6010 SOST20131 Introduction COM3524 MME2 GGR305 JNB 538 EECS101 COMM5030 IEOR E4601 2B CSC336 EN2315 LAW 432 CSC263 MATH2001 OLET1143 CSCB63 SIT772 COMM1170 STAT 441 MS930 INFT3050 GLBH0030 Stat 120B MAST10007 MGEC61 Machine GGR 252H1S ECON7030 Financial Marketing MGMT30019 ECON5120 SDSC 8009 CSC165H1S DSCI 551 3081W ACM41000 ECA 5304 MATH 1064 ECSE444 DATA 604 COMP7105 MIE1615 ECON4004 ENV200H1S EC481 MKT 306 EC1B1 MATH08051 ALY6140 CS260C CSE30 MSIN0226 CS4103 CSC3064 AM16 COMP11212 CSE4101 PSTAT 174 Math 380W CNT 5106C STAT 310 FIN2028 CS5014 STAT 425 COMP 4102A ELEC2140 MANF9544 QRM 9 QRM 8 ECON 457 COMPSCI 4091 MATH 523 DNSC-4211 PEAS 6000 MSIN0180 COMP2119 A2A HT 2022 IB93F0 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