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Dynamic Memory Allocation: Advanced Concepts
15-213/18-213/14-513/15-513/18-613: Introduction to Computer Systems
16th Lecture, October 22, 2020
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Review: Dynamic Memory Allocation
Memory invisible to user code
%rsp
(stack pointer)
Kernel virtual memory
User stack (created at runtime)
Memory-mapped region for shared libraries
Run-time heap (created by malloc)
Read/write segment (.data, .bss)
Read-only segment (.init, .text, .rodata)
Unused
Application
Dynamic Memory Allocator
Heap
 Programmers use dynamic memory allocators (such as malloc) to acquire virtual memory (VM) at run time.
▪ for data structures whose size is only known at runtime
 Dynamic memory allocators manage an area of process VM known as the heap.
0x400000
brk
Loaded from
the executable file
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Review: Keeping Track of Free Blocks
 Method 1: Implicit list using length—links all blocks Unused
32
48
32
16
 Method 2: Explicit list among the free blocks using pointers Need space
 Method 3: Segregated free list
▪ Different free lists for different size classes
 Method 4: Blocks sorted by size
▪ Can use a balanced tree (e.g. Red-Black tree) with pointers within each
free block, and the length used as a key Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Need to tag each block as allocated/free
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48
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for pointers

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Review: Implicit Lists Summary
 Implementation: very simple
 Allocate cost:
▪ linear time worst case
 Free cost:
▪ constant time worst case ▪ even with coalescing
 Memory Overhead:
▪ Depends on placement policy
▪ Strategies include first fit, next fit, and best fit
 Not used in practice for malloc/free because of linear- time allocation
▪ used in many special purpose applications
 However, the concepts of splitting and boundary tag
coalescing are general to all allocators Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Today
 Explicit free lists
 Segregated free lists
 Memory-related perils and pitfalls
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Keeping Track of Free Blocks
 Method 1: Implicit list using length—links all blocks
Unused
 Method 2: Explicit list among the free blocks using pointers
32
48
32
16
32
48
32
16
 Method 3: Segregated free list
▪ Different free lists for different size classes
 Method 4: Blocks sorted by size
▪ Can use a balanced tree (e.g. Red-Black tree) with pointers within each
free block, and the length used as a key Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Explicit Free Lists
Allocated (as before) Free
Size
a
Payload and padding
Size
a
Size
a
Next
Prev
Size
a
Optional
 Maintain list(s) of free blocks, not all blocks
▪ Luckily we track only free blocks, so we can use payload area ▪ The “next” free block could be anywhere
▪ So we need to store forward/back pointers, not just sizes ▪ Still need boundary tags for coalescing
▪ To find adjacent blocks according to memory order Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Explicit Free Lists  Logically:
ABC
 Physically: blocks can be in any order
AB
Forward (next) links
32
32
32
32
48
48
32
32
32
32
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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C
Back (prev) links

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Allocating From Explicit Free Lists
conceptual graphic
Before
After
(with splitting)
= malloc(…)
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Freeing With Explicit Free Lists
 Insertion policy: Where in the free list do you put a newly freed block?
 Unordered
▪ LIFO (last-in-first-out) policy
▪ Insert freed block at the beginning of the free list ▪ FIFO (first-in-first-out) policy
▪ Insert freed block at the end of the free list
▪ Pro: simple and constant time
▪ Con: studies suggest fragmentation is worse than address ordered
 Address-ordered policy
▪ Insert freed blocks so that free list blocks are always in address order:
addr(prev) < addr(curr) < addr(next) ▪ Con: requires search ▪ Pro: studies suggest fragmentation is lower than LIFO/FIFO Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 12 Carnegie Mellon Freeing With a LIFO Policy (Case 1) Allocated Allocated conceptual graphic Before Root free( )  Insert the freed block at the root of the list After Root Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 13 Carnegie Mellon Freeing With a LIFO Policy (Case 2) conceptual graphic Allocated Free Before Root free( )  Splice out adjacent successor block, coalesce both memory blocks, and insert the new block at the root of the list After Root Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 14 Carnegie Mellon Freeing With a LIFO Policy (Case 3) conceptual graphic Free Allocated Before Root free( )  Splice out adjacent predecessor block, coalesce both memory blocks, and insert the new block at the root of the list After Root Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 15 Carnegie Mellon Freeing With a LIFO Policy (Case 4) conceptual graphic Free Free Before Root free( )  Splice out adjacent predecessor and successor blocks, coalesce all 3 blocks, and insert the new block at the root of the list After Root Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 16 Carnegie Mellon Some Advice: An Implementation Trick FIFO Insertion Point LIFO Insertion Point ABCD Free Pointer Next fit  Use circular, doubly-linked list  Support multiple approaches with single data structure  First-fit vs. next-fit ▪ Either keep free pointer fixed or move as search list  LIFO vs. FIFO ▪ Insert as next block (LIFO), or previous block (FIFO) Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 17 Carnegie Mellon Explicit List Summary  Comparison to implicit list: ▪ Allocate is linear time in number of free blocks instead of all blocks ▪ Much faster when most of the memory is full ▪ Slightly more complicated allocate and free because need to splice blocks in and out of the list ▪ Some extra space for the links (2 extra words needed for each block) ▪ Does this increase internal fragmentation? Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 18 Carnegie Mellon Today  Explicit free lists  Segregated free lists  Memory-related perils and pitfalls Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 19 Carnegie Mellon Segregated List (Seglist) Allocators  Each size class of blocks has its own free list 16 32-48 64–inf  Often have separate classes for each small size  For larger sizes: One class for each size [𝟐𝒊 + 𝟏, 𝟐𝒊+𝟏] Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 20 Carnegie Mellon Seglist Allocator  Given an array of free lists, each one for some size class  To allocate a block of size n: ▪ Search appropriate free list for block of size m > n (i.e., first fit) ▪ If an appropriate block is found:
▪ Split block and place fragment on appropriate list
▪ If no block is found, try next larger class ▪ Repeat until block is found
 If no block is found:
▪ Request additional heap memory from OS (using sbrk())
▪ Allocate block of n bytes from this new memory
▪ Place remainder as a single free block in appropriate size class.
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Seglist Allocator (cont.)  To free a block:
▪ Coalesce and place on appropriate list
 Advantages of seglist allocators vs. non-seglist allocators
(both with first-fit)
▪ Higher throughput
▪ log time for power-of-two size classes vs. linear time
▪ Better memory utilization
▪ First-fit search of segregated free list approximates a best-fit
search of entire heap.
▪ Extreme case: Giving each block its own size class is equivalent to best-fit.
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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More Info on Allocators
 D. Knuth, The Art of Computer Programming, vol 1, 3rd edition, Addison Wesley, 1997
▪ The classic reference on dynamic storage allocation
 Wilson et al, “Dynamic Storage Allocation: A Survey and Critical Review”, Proc. 1995 Int’l Workshop on Memory Management, Kinross, Scotland, Sept, 1995.
▪ Comprehensive survey
▪ Available from CS:APP student site (csapp.cs.cmu.edu)
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Quiz Time!
Check out:
https://canvas.cmu.edu/courses/17808
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Today
 Explicit free lists
 Segregated free lists
 Memory-related perils and pitfalls
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Memory-Related Perils and Pitfalls
 Dereferencing bad pointers
 Reading uninitialized memory
 Overwriting memory
 Referencing nonexistent variables  Freeing blocks multiple times
 Referencing freed blocks
 Failing to free blocks
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Dereferencing Bad Pointers  The classic scanf bug
int val;
…
scanf(“%d”, val);
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Reading Uninitialized Memory
 Assuming that heap data is initialized to zero
/* return y = Ax */
int *matvec(int **A, int *x) {
int *y = malloc(N*sizeof(int));
int i, j;
for (i=0; i .++–
! ~ ++– + – * &(type)sizeof
left to right
right to left
left to right left to right left to right left to right left to right left to right left to right left to right left to right left to right right to left right to left left to right
* / % + –
<< >> Binary
< <= > >= == !=
&
^
Unary Unary
Prefix
Binary
|
&&
||
?:
= += -= *= /= %= &= ^= != <<= >>= ,
 ->, (), and [] have high precedence, with * and & just below  Unary +, -, and * have higher precedence than binary forms
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
Source: K&R page 53, updated
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Overwriting Memory
 Referencing a pointer instead of the object it points to
int *BinheapDelete(int **binheap, int *size) { int *packet;
packet = binheap[0];
binheap[0] = binheap[*size – 1];
*size–;
Heapify(binheap, *size, 0);
return(packet);
}
 Same effect as ▪ size–;
 Rewrite as
▪ (*size)–;
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Referencing Nonexistent Variables
 Forgetting that local variables disappear when a function returns
int *foo () { int val;
return &val;
}
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Freeing Blocks Multiple Times  Nasty!
x = malloc(N*sizeof(int));

free(x);
y = malloc(M*sizeof(int));

free(x);
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Referencing Freed Blocks  Evil!
x = malloc(N*sizeof(int));

free(x); …
y = malloc(M*sizeof(int));
for (i=0; ival = 0;
head->next = NULL;

… free(head); return;
}
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Dealing With Memory Bugs
 Debugger:gdb
▪ Good for finding bad pointer dereferences ▪ Hard to detect the other memory bugs
 Data structure consistency checker
▪ Runs silently, prints message only on error ▪ Use as a probe to zero in on error
 Binary translator: valgrind
▪ Powerful debugging and analysis technique
▪ Rewrites text section of executable object file ▪ Checks each individual reference at runtime
▪ Bad pointers, overwrites, refs outside of allocated block  glibc malloc contains checking code
▪ setenv MALLOC_CHECK_ 3 Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Supplemental slides
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Implicit Memory Management: Garbage Collection
 Garbage collection: automatic reclamation of heap-allocated storage—application never has to explicitly free memory
void foo() {
int *p = malloc(128);
return; /* p block is now garbage */
}
 Common in many dynamic languages:
▪ Python, Ruby, Java, Perl, ML, Lisp, Mathematica
 Variants (“conservative” garbage collectors) exist for C and C++ ▪ However, cannot necessarily collect all garbage
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Garbage Collection
 How does the memory manager know when memory can be freed?
▪ In general we cannot know what is going to be used in the future since it depends on conditionals
▪ But we can tell that certain blocks cannot be used if there are no pointers to them
 Must make certain assumptions about pointers
▪ Memory manager can distinguish pointers from non-pointers
▪ All pointers point to the start of a block
▪ Cannot hide pointers
(e.g., by coercing them to an int, and then back again)
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Classical GC Algorithms
 Mark-and-sweep collection (McCarthy, 1960)
▪ Does not move blocks (unless you also “compact”)
 Reference counting (Collins, 1960)
▪ Does not move blocks (not discussed)
 Copying collection (Minsky, 1963)
▪ Moves blocks (not discussed)
 Generational Collectors (Lieberman and Hewitt, 1983) ▪ Collection based on lifetimes
▪ Most allocations become garbage very soon
▪ So focus reclamation work on zones of memory recently allocated
 For more information:
Jones and Lin, “Garbage Collection: Algorithms for Automatic Dynamic Memory”, John Wiley & Sons, 1996.
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Memory as a Graph
 We view memory as a directed graph
▪ Each block is a node in the graph
▪ Each pointer is an edge in the graph
▪ Locations not in the heap that contain pointers into the heap are called root nodes (e.g. registers, locations on the stack, global variables)
Root nodes
Heap nodes
reachable
Not-reachable (garbage)
A node (block) is reachable if there is a path from any root to that node.
Non-reachable nodes are garbage (cannot be needed by the application) Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
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Mark and Sweep Collecting  Can build on top of malloc/free package
▪ Allocate using malloc until you “run out of space”
 When out of space:
▪ Use extra mark bit in the head of each block
▪ Mark: Start at roots and set mark bit on each reachable block ▪ Sweep: Scan all blocks and free blocks that are not marked
root
Note: arrows here denote memory refs, not free list ptrs.
Mark bit set
Before mark
After mark
After sweep
free
free
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Assumptions For a Simple Implementation
 Application
▪ new(n): returns pointer to new block with all locations cleared ▪ read(b,i): read location i of block b into register
▪ write(b,i,v): write v into location i of block b
 Each block will have a header word
▪ addressed as b[-1], for a block b
▪ Used for different purposes in different collectors
 Instructions used by the Garbage Collector
▪ is_ptr(p): determines whether p is a pointer
▪ length(b): returns the length of block b, not including the header ▪ get_roots(): returns all the roots
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Mark and Sweep Pseudocode Mark using depth-first traversal of the memory graph
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
50
ptr mark(ptr p) {
if (!is_ptr(p)) return;
if (markBitSet(p)) return; setMarkBit(p);
for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// recursively call mark on all words // in the block
mark(p[i]);
return;
}

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Mark and Sweep Pseudocode Mark using depth-first traversal of the memory graph
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
51
ptr mark(ptr p) {
if (!is_ptr(p)) return;
if (markBitSet(p)) return; setMarkBit(p);
for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// recursively call mark on all words // in the block
mark(p[i]);
return;
}

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Mark and Sweep Pseudocode Mark using depth-first traversal of the memory graph
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
52
ptr mark(ptr p) {
if (!is_ptr(p)) return;
if (markBitSet(p)) return; setMarkBit(p);
for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// recursively call mark on all words // in the block
mark(p[i]);
return;
}

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Mark and Sweep Pseudocode Mark using depth-first traversal of the memory graph
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
53
ptr mark(ptr p) {
if (!is_ptr(p)) return;
if (markBitSet(p)) return; setMarkBit(p);
for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// recursively call mark on all words // in the block
mark(p[i]);
return;
}

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Mark and Sweep Pseudocode
Mark using depth-first traversal of the memory graph
ptr mark(ptr p) {
if (!is_ptr(p)) return;
if (markBitSet(p)) return;
setMarkBit(p);
for (i=0; i < length(p); i++) // for each word in p’s block } mark(p[i]); return; Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 54 // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit

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Mark and Sweep Pseudocode
Mark using depth-first traversal of the memory graph
ptr mark(ptr p) {
if (!is_ptr(p)) return;
if (markBitSet(p)) return; setMarkBit(p);
for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// for each word in p’s block
// make recursive call
mark(p[i]);
return;
}
Sweep using lengths to find next block
ptr sweep(ptr p, ptr end) {
while (p < end) { // for entire heap } if markBitSet(p) clearMarkBit(); else if (allocateBitSet(p)) free(p); p += length(p+1); Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 56 Carnegie Mellon Mark and Sweep Pseudocode Mark using depth-first traversal of the memory graph ptr mark(ptr p) { if (!is_ptr(p)) return; if (markBitSet(p)) return; setMarkBit(p); for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// for each word in p’s block
// make recursive call
mark(p[i]);
return;
}
Sweep using lengths to find next block
ptr sweep(ptr p, ptr end) {
while (p < end) { // for entire heap // did we reach this block? } if markBitSet(p) clearMarkBit(); else if (allocateBitSet(p)) free(p); p += length(p+1); Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition 57 Carnegie Mellon Mark and Sweep Pseudocode Mark using depth-first traversal of the memory graph ptr mark(ptr p) { if (!is_ptr(p)) return; if (markBitSet(p)) return; setMarkBit(p); for (i=0; i < length(p); i++) // if not pointer -> do nothing
// if already marked -> do nothing // set the mark bit
// for each word in p’s block
// make recursive call
mark(p[i]);
return;
}
Sweep using lengths to find next block
ptr sweep(ptr p, ptr end) {
while (p < end) { // for entire heap // did we reach this block? // yes -> so just clear mark bit
}
if markBitSet(p)
clearMarkBit();
else if (allocateBitSet(p)) free(p);
p += length(p+1);
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C Pointer Declarations: Test Yourself!
int *p
int *p[13]
int *(p[13])
int **p
int (*p)[13]
int *f()
int (*f)()
int (*(*x[3])())[5]
p is a pointer to int
p is an array[13] of pointer to int p is an array[13] of pointer to int p is a pointer to a pointer to an int
p is a pointer to an array[13] of int
f is a function returning a pointer to int
f is a pointer to a function returning int
x is an array[3] of pointers to functions returning pointers to array[5] of ints
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
Source: K&R Sec 5.12
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C Pointer Declarations: Test Yourself!
int *p
int *p[13]
int *(p[13])
int **p
int (*p)[13]
int *f()
int (*f)()
int (*(*x[3])())[5]
int (*(*f())[13])()
p is a pointer to int
p is an array[13] of pointer to int p is an array[13] of pointer to int p is a pointer to a pointer to an int
p is a pointer to an array[13] of int
f is a function returning a pointer to int
f is a pointer to a function returning int
x is an array[3] of pointers to functions returning pointers to array[5] of ints
f is a function returning ptr to an array[13] of pointers to functions returning int
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
Source: K&R Sec 5.12
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Parsing: int (*(*f())[13])()
int (*(*f())[13])()
int (*(*f())[13])()
int (*(*f())[13])()
int (*(*f())[13])()
int (*(*f())[13])()
f
f is a function
f is a function
that returns a ptr
f is a function
that returns a ptr to an array of 13
f is a function that returns a ptr to an array of 13 ptrs
int (*(*f())[13])()
Bryant and O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition
f is a function that returns a ptr to an array of 13 ptrs to functions returning an int
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