• Assign: Monday, 9 December
• Due: By the end of finals, 4:00pm Friday, 20 December
• Policy: Pair graded synthesis assignment
• Partner search: Find a partner here.
• Code: cs240 start malloc
• Submit: git commit, cs240 sign, and git push your completed code.
• Reference:
  • dynamic memory allocation
  • programming with memory
  • reasoning about programs
  • C resources
  • debugging resources
  • Team Workflow

Instructors will add some drop-in hours during reading period and finals to support work on this assignment.

Contents

• Overview
  • Goals
  • Advice
  • Time Reports
• Setup
• Tasks
• Preparatory Exercises
  • CSAPP Review
  • Required Exercises
• Specification
  • Function Specifications
  • Programming Rules and Style
• Implementation
  • Implicit Free List Allocator
  • Explicit Free List Allocator
  • Search Strategy
  • Seglists, Alternative Policies, and Beyond
• Compiling and Testing
  • Common Testing Tasks
  • Trace Format
  • Heap Consistency Checker
  • Performance
• How To Work
  • Plan Carefully
  • Code Defensively
  • Implement and Test Incrementally
  • Debug Methodically
  • Optimize Judiciously
• Submission
• Grading
• Extra Fun Open-Ended Extensions
  • Implement realloc
  • Extended Error-Checking

Overview¹

In this assignment you will implement a dynamic memory allocator (malloc/free) for C programs!

Goals

• To understand general principles and trade-offs in dynamic memory allocation.
• To consider and empirically evaluate the effects of implementation and design choices on competing measures of performance.
• To develop defensive design, coding, and debugging skills for environments where standard structure and amenities are unavailable.
• To build a fundamental system component that you have been using (unwittingly?) since the first time you used a computer.
• To synthesize your accumulated bit-twiddling, pointer-plying, and algorithm-accelerating wisdom to build and optimize a “1-sentence” project instead of taking a final exam.

Advice

This assignment requires careful bit-level manipulation of memory using many of C’s unsafe pointer casting features without much structure. Your allocator code will not be enormous, but it will be subtle. Take planning seriously and work methodically. Ignoring this advice could cost hours or days. Also keep in mind that performance is a major component of the evaluation for this assignment.

We recommend this path for preparation and development of a successful allocator:

1. Read the specification, complete the preparatory exercises,, and review effective work strategies.
2. Implement an implicit free list allocator in C (and test it).
3. Optionally, extend your implicit free list allocator to create an explicit free list allocator.
4. Extra Fun Optionally, add open-ended extensions to the allocator.

Time Reports

According to self-reported times on this assignment from Fall 2018:

• 25% of students spent <= 6 hours.
• 50% of students spent <= 12 hours.
• 75% of students spent <= 15 hours.

This represents a range of implementation strategies.

Setup

Use a CS 240 computing environment. The allocator you build might work on similar platforms (no guarantees!), but it must work on our platforms for grading.

Get your repository with cs240 start malloc.

Your Remembrallocator Design Kit contains the following files:

• Makefile – recipes for compiling
• mdriver.c – testing driver
• memlib.h – memory/heap interface
• mm.c – memory allocator implementation
• mm.h – memory allocator interface
• traces/ – several trace files (.rep) used for simulated testing
• remaining files are testing support files you do not need to inspect

Compile the allocator and test driver with make to produce an executable called mdriver. Usage of the mdriver testing executable is described later.

Tasks

You will modify mm.c to implement a memory allocator with the interface declared in mm.h and the functionality described by the Specification section below.

int   mm_init();
void* mm_malloc(size_t payload_size);
void  mm_free(void* payload);

The provided mm.c file partially implements an allocator based on an implicit free list. It provides skeletons of several helper functions beyond the interface above and an implementation of mm_malloc that uses these helper functions. Your job is to complete the helper functions (and possibly add more of your own) as well as mm_free() to implement a memory allocator with good balance of memory utilization and throughput. You may use any implementation strategy that works (subject to programming rules), but performance of your memory allocator is a large component of the grade. There are many opportunities for extensions, whether in increasingly sophisticated allocator implementations for better performance or in analysis and error-checking tools.

Grading considers design, documentation, style, correctness, and performance.

The remainder of this document includes:

1. Preparatory exercises for designing and simulating an implicit free list allocator.
2. The allocator specification.
3. Notes on implementing various allocator strategies.
4. Documentation of the test harness for correctness checking and performance evaluation.
5. Advice for effective work strategies.
6. Grading criteria.
7. Extra Fun Ideas for open-ended extensions.

Preparatory Exercises

As you read this document, complete these exercises to familiarize yourself with heap layout, block layout, and the provided starter code. These exercises will help you design your allocator implementation before diving into messy implementation details. Good planning is key when developing low-level systems software.

CSAPP Review

Read CSAPP section 9.9 to become familiar with the type of thinking and coding you will do to build the allocator. The book discusses an implicit free list allocator similar in organization to the one you will build first. The valuable part is the descriptions. The book’s code is useful, but do not get too caught up in the code details, since you will use different starter code.

We recommend the following practice problems on memory allocation, but you do not need to submit solutions. Solutions not in the textbook are available by visiting office hours. Note “word” means 4 bytes for these CSAPP problems, but 8 bytes for our assignment.

• CSAPP Practice Problem 9.6
• CSAPP Practice Problem 9.7
• CSAPP Homework Problem 9.15
• CSAPP Homework Problem 9.16

Required Exercises

These exercises will help you plan your allocator implementation and avoid wasting time writing C code before you understand what you are doing. Tips:

• Take notes on anything you learn during these exercises.
• Read instructions and comments in provided code carefully.
• Draw detailed diagrams of the heap and execute operations on the visual heap by hand to become familiar with the details or debug.
• Every line of provided code does something meaningful and necessary.

A. Heap and Block Layout

Submit answers for the following questions in A. Read mm.c to learn about the block layout. Assume words are 8 bytes and pages are 4096 bytes. Pay special attention to the early comments about block and heap layout, as well as the code in mm_init. [We made Minor updates based common questions – no need to come back to these if you already did them.]

1. What is the minimum block size (in bytes) of our allocator?
2. What is stored in the header of each block?
3. What is stored in the footer of each free block?
4. What is the largest payload that could be allocated in a minimum-size block?
5. What is stored in the last word of the heap? (We call this the heap footer; CSAPP calls this the epilogue.)
6. How much space in the heap is never part of any block?

For the following questions, draw memory as an array of words (but not to scale when using big numbers). Use the block layout rules from mm.c and especially the heap setup code in mm_init and note that they vary from the basic rules described in CSAPP. Follow the style of heap drawings used in the CSAPP book (Figures 9.36-9.38), but remember that block details will vary. (Ignore Figure 9.42 – we have no prologue block.) Always draw the heap header word, the heap footer word, and the headers (and footers as needed) for all blocks in the heap.

1. Draw a heap that contains a single allocated block with size 48. (Assume page size = total heap size = 64 bytes)
2. Draw a heap that contains a single free block with size 64. (Assume page size = total heap size = 80 bytes)
3. Draw a heap that contains an allocated block with size 48, followed by a free block of size 32. (Assume page size = total heap size = 96 bytes)
4. Draw a heap that contains a free block of size 32, followed by an allocated block of size 48. (Assume page size = total heap size = 96 bytes)

B. Simulate the Starter Allocator

Submit answers for at least one question in B.

Simulate the starter allocator code by hand starting from an heap generated by a call to mm_init. Assume words are 8 bytes and pages are 4096 bytes. Update a drawing of the heap as you go, following the drawing guidelines from part A. Show exactly what this starter allocator does, not your idea of what an allocator should do. This will force you to read and understand the provided code carefully in detail. Add comments as you go if it helps you to keep notes in addition to the provided comments.

1. Starting from a fresh initial heap, simulate the following requests and update your drawing based on what the starter code allocator does:

     p0 = mm_malloc(12);
     p1 = mm_malloc(16);
     p2 = mm_malloc(16);
     mm_free(p0);
     mm_free(p1);
     p3 = mm_malloc(24);

2. Starting from fresh initial heaps, simulate the traces short1-bal.rep and short2-bal.rep from the traces directory in the starter code. The format of trace files is described here.

C. Starter Functions

Submit brief answers for all questions in C.

1. What do the LOAD and PSTORE functions do? Why might it be preferable to use them in place of normal C pointer operations?
2. Given a block pointer bp, write an expression using helper function calls to return the allocation status of the block preceding bp in memory order.
3. What fit policy does search employ?
4. Why does extend_heap coalesce its newly added space? Consider that extend_heap is typically called only if no existing free block is large enough to satisfy the current allocation request.

D. Add and Simulate Pseudocode Features

For each of the following features, add the feature by sketching pseudocode comments within mm.c. Then, before working on the next feature, simulate the allocator with this feature on the sample traces from the previous part, drawing heap state as you go.

1. Sketch a pseudocode implementation of mm_free as // inline comments in the body of mm_free.
2. Sketch a pseudocode implementation of splitting in allocate as // inline comments in the body of allocate.
3. Sketch a pseudocode implementation of coalesce as // inline comments in the body of coalesce.

Write pseudocode at a sufficient level of detail that you can simulate clearly, but do not get tangled up in C-level pointer work. Well-written comments at this stage can remain as documentation when you move on to implementation in C.

Submit pseudocode by committing comments in mm.c. Submit a heap drawing for the simulation of one trace after pseudocoding all 3 features.

Specification

Function Specifications

The three main memory management functions should work as follows:

• int mm_init(), provided: Initialize the heap. Return 0 on success or -1 if initialization failed. Client applications (in this case, the driver we provide) call mm_init once to initialize the system before calling mm_malloc() or mm_free().

• void* mm_malloc(size_t payload_bytes): Allocate and return a pointer to a block payload of at least payload_bytes contiguous bytes or return NULL if the requested allocation could not be completed.
  • Payload addresses must be aligned to 16 bytes.
  • Allocated blocks must be non-overlapping and within heap bounds.
  • size_t is a type for describing sizes; it is an unsigned integer large enough to represent any size within the address space.
• void mm_free(void* payload): Free the allocated block whose payload is referenced by the pointer payload. Assume that payload was returned by an earlier call to mm_malloc() and has not been passed to mm_free since its most recent return from mm_malloc.

The specifications for mm_malloc and mm_free match those for the malloc(1) and free(1) functions, respectively, in the standard C library.

Programming Rules and Style

• Do not change any of the mm_ function types in mm.c/mm.h. You may add, remove, or change helper functions in mm.c as you wish. Declare all helper functions (other than the interface above) as static (visible only within the file).

• Do not call any standard memory-management related library functions or system calls such as malloc, calloc, free, etc. You may use all functions in memlib.c, but if you use the provided starter code, you likely will not need additional uses of the memlib.c functions.

• Avoid declaring global or static variables. If you think you need them, consider how to store them within the heap region instead.

• Write function header comments for new functions (and expand the existing header comments for the main existing functions mm_malloc, mm_free, search, allocate, and coalesce) to describe what the function does, what policy it follows (if applicable), and what it assumes. Use inline comments to describe details as needed.

• Since some of the unstructured pointer manipulation inherent to allocators can be confusing, we recommend small helper functions and short inline comments on steps of the allocation algorithms.

Implementation

You may take any approach to implementing the specified allocator behavior above. Your implementation will be evaluated based on correctness, performance, documentation, and style. This section suggests an incremental implementation strategy that allows you to choose what balance of implementation sophistication and performance you prefer.

Start with an implicit free list allocator implementation. If you wish to improve the performance of your allocator once you have implemented and tested an implicit free list approach, consider an explicit free list or other search strategies as next steps, or eventually explore more sophisticated improvements.

Implicit Free List Allocator

Convert your pseudocode feature implementations to C code one at a time, testing and committing each before starting C code for the next feature.

1. Implement and test mm_free.
2. Implement and test splitting in allocate.
3. Implement and test coalesce.

Run tests on individual traces for debugging and on all traces for general testing and performance evaluation.

• Some provided traces will cause your allocator to run out of memory unless you have completed all three features.
• Any other errors or crashes indicate correctness problems you must fix.
• The traces short1-bal.rep and short2-bal.rep should work from the beginning, but they are suitable only as small debugging samples.
• Write your own small traces to help test or debug individual cases.
• Use check_heap to sanity-check each feature before implementing the next or to help debug when things go wrong.

Explicit Free List Allocator

The best way to develop an explicit free list allocator (or a more sophisticated seglist allocator) is to first develop a working implicit free list allocator and extend it to use explicit free lists.

Some suggestions as you implement explicit free lists:

1. An explicit free list allocator (or a next-fit allocator) must store a pointer to the list head node somewhere. The first word of the heap (or a single global pointer variable if necessary) is a good place to store this. Helper functions for getting and setting this pointer will keep list manipulations clean.
2. Free blocks must contain next and previous pointers. Consider how this affects MIN_BLOCK_SIZE. Choose a fixed offset within the block to store each of the pointers. Helper functions for getting and setting these pointers will keep list manipulations clean. Using block headers as the target of these pointers in all cases is the simplest, easiest, most efficient option.
3. Helper functions to insert a block into the free list and remove a block from the free list are advisable, as you will need to do these same steps in multiple places.
4. We suggest disabling coalescing, splitting and mm_free while you complete initial development of the explicit free list.
5. Update mm_init, search, allocate, and extend_heap to use your explicit free list. Test.
6. Update and test each of mm_free, splitting, and coalescing for the explicit free list.
7. Enable compiler optimizations. Add -O to the CFLAGS line in your Makefile, then make clean and make to recompile. You could also consider disabling assertions with -DNODEBUG to save work. (Both of these may make debugging a little more difficult, so use them only once your code is working.) You can also force higher levels of optimization (-O2 or -O3) to see if they help.

Search Strategy

Once you have a working allocator using a first-fit policy with freeing, splitting, and coalescing implemented, one potential performance improvement strategy is to try alternative fit policies. Consider how they are likely to affect your performance index relative to first fit and relative to the performance improvements that could result from an explicit free list. Make sure to git commit before trying this. For a next-fit policy, we suggest:

• Add a constant/macro NEXT_FIT_POLICY that is 1 if using next fit or 0 otherwise. Write code such that you can easily switch policies by switching this value. #define NEXT_FIT_POLICY 1
• Use a global variable or the first heap word to save a pointer to the block where the next search should begin. Add helper functions for getting and setting this pointer if using the latter.

Seglists, Alternative Policies, and Beyond

A clean and efficient working explicit free list allocator should achieve a respectable performance index. To achieve even better performance, you could consider implementing seglists, alternative free list representations, or alternative search policies. If you embark on this path, weigh difficulty of implementation against likely effect on performance index.

Compiling and Testing

The mdriver program tests your mm.c implementation for correctness, space utilization, and throughput. Build mdriver with make and run it with the command ./mdriver -V (the -V flag displays helpful summary information as described below).

mdriver uses trace files to simulate memory management workloads using your mm.c implementation. A trace is a sequence of allocate and free events. mdriver simulates a trace by calling mm_malloc and mm_free for each corresponding event in the trace in order.

The mdriver executable accepts the following command line arguments:

• -t <tracedir>: Look for the default trace files in directory tracedir instead of the default directory defined in config.h.
• -f <tracefile>: Use one particular tracefile for testing instead of the default set of tracefiles.
• -h: Print a summary of the command line arguments.
• -l: Run and measure libc malloc in addition to your mm.c implementation.
• -v: Verbose output. Print a performance breakdown for each tracefile in a compact table.
• -V: More verbose output. Prints additional diagnostic information as each trace file is processed. Useful during debugging for determining which trace file is causing your mm.c implementation to fail.

Common Testing Tasks

• Run mdriver on individual traces for debugging: ./mdriver -V -f traces/your-favorite-trace.rep
• Run mdriver on all traces for correctness testing and performance evaluation: ./mdriver -V
• Some traces in the traces directory will cause your allocator to run out of memory until you have completed all three implicit allocator features.
• Any other errors (other than out-of-memory) or crashes indicate correctness problems you must fix.
• The traces short1-bal.rep and short2-bal.rep should work from the beginning. You may find it useful to write additional traces for debugging.

Trace Format

When learning about the starter code, you will simulate small traces. When testing and debugging, you may find it useful to write and test your own small traces.

Traces used by mdriver summarize the execution of a program as a sequence of mm_malloc and mm_free calls in a simple format.

A trace file contains 4 header lines:

1. Suggested heap size (any number, ignored by our tests).
2. Total number of blocks allocated.
3. Total number of malloc/free events.
4. Weight (any number, ignored by our tests).

Remaining lines after the header give a sequence of memory management events, one per line. Each event is either an allocate event or a free event:

event ::= a id size
        | f id

• Event a i size indicates the ith call to malloc in the trace, requesting payload size. The ID i uniquely identifies the malloc call and the allocation it makes, starting at 0 for the first allocation in the trace.
• Event f i indicates a call to mm_free with the pointer that was returned by the ith malloc call in the trace.

The following example C code would generate the corresponding trace below it.

C code:

p0 = malloc(12);
p1 = malloc(16);
p2 = malloc(16);
free(p0);
free(p1);
p3 = malloc(24);

A corresponding trace:

128
4
6
1
a 0 12
a 1 16
a 2 16
f 0
f 1
a 3 24

Heap Consistency Checker

The function check_heap implements basic heap consistency checks for an implicit free list allocator and prints out all blocks in the heap in memory order.

You may find it helpful to insert calls to check_heap to assist in testing and debugging allocator features you add. Make sure to remove all calls to check_heap before submitting your code. It will definitely affect performance evaluation.

You may also find it helpful to extend the check_heap function to check more detailed consistency properties. This becomes most interesting when considering an explicit free list (or more sophisticated) allocator. check_heap should return a nonzero value if and only if your heap is consistent according to the conditions you check.

Example checks to add:

• Are all blocks present in the (explicit) free list also marked as free?
• Are all blocks present in the (explicit) free list also valid block addresses?
• Are all blocks marked as free also present in the (explicit) free list?
• Are all free blocks surrounded by allocated blocks (i.e., are all free blocks fully coalesced)?
• Are all blocks non-overlapping (check boundary tags)?
• Are all heap words (except the heap header and heap footer) part of some block?

Feel free to rename or split check_heap into multiple static helper functions. When you submit mm.c, make sure to disable any calls to check_heap as they will impact performance.

Performance

For the most part, a correct implementation based on our provided code will yield passable performance. Two performance metrics will be used to evaluate your solution:

• Space utilization: The peak ratio between the aggregate amount of memory used by the driver (i.e., allocated via mm_malloc but not yet freed via mm_free) and the size of the heap used by your allocator. The optimal ratio is 1. Choose policies that minimize fragmentation to maximize utilization.
• Throughput: The average number of allocator operations completed per second.

The mdriver.opt program computes a performance index, which is a weighted sum of the space utilization and throughput:

P = 0.6 × U_mm.c + 0.4 × min(1, T_mm.c / T_libc)

where U_mm.c is the space utilization of your mm.c implementation, T_mm.c is the throughput of your mm.c implementation, and T_libc is the estimated throughput of the standard C library (libc) version of malloc on the default traces. The performance index values both good space utilization and good throughput, with slight preference toward space efficiency.

Your allocator must balance utilization and throughput. A performance index of 70-80 or above (out of 100) is pretty good. For reference, instructor implementations have achieved the following performance scores:

• Implicit free list with splitting and coalescing:
  • first-fit: 50/100
  • next-fit: 56/100
• Explicit free list with splitting and coalescing:
  • first-fit: 91/100

Better performance likely requires a more sophisticated free list implementation. Before haphazardly attempting to “optimize” your implementation, read these hints about performance engineering and optimization.

How To Work

Low-level unguarded memory manipulation code like this allocator is prone to subtle and frustrating bugs. There’s a reason you often use higher-level languages with more protections! The following strategies help to work effectively and responsibly to avoid frustration and confusion.

Plan Carefully

Review allocator concepts, complete the preparatory exercises, and read the provided code carefully. Never write code until you have a good idea of what you are doing and what is already there.

Code Defensively

Expect things to go wrong. Anywhere your code relies on an assumption, check it explicitly. Explain to your partner why your code should work. Write error-prone code once carefully and reuse it.

• Use assertions. Anywhere you assume a property of data to hold, assert that property explicitly. Assertions document your assumptions. They are also checked explicitly as your program runs, making it easier to localize the source of an error if one occurs.

• Use the provided helpers for memory access (LOAD, STORE, PLOAD, PSTORE.) and pointer arithmetic (PADD and PSUB). This helps avoid pointer manipulation errors or at least catch them early.

Implement and Test Incrementally

Implement, test, and commit one feature (or sub-feature!) at a time, testing and committing each before you start implementing the next. This will make it much easier to understand what code is involved in a bug.

Debug Methodically

GDB and the check_heap function are the tools of choice. Here are some strategies and other tips.

• Did your program hit an explicit error? An assertion failure? A segfault?
  • Localize the crash. Exactly what line of code, what operation in this line, what value(s) used by this operation manifested what error and crashed? This symptom rarely indicates the cause, but it marks where to begin the search.
    • Use gdb to run the code until it crashes, then find the line that crashed (and the context in which it executed) with bt, backtrace, or where.
    • Inspect the most relevant line of code and the error report to determine what the error means. Was it a segfault? If it was an assertion failure, what was the assertion checking?
    • Inspect the arguments shown in the backtrace or print variables to determine what ill-formed pointer was dereferenced to cause a segmentation fault or what illegal values failed an assertion.
  • Trace backward through the dependences of this broken operation to the original logic error.
    • Invalid values: Did any of this operation’s arguments hold invalid values? Did this operation load any invalid values from memory?
      • What operations produced these invalid values?
        • This is easy to answer for invalid arguments.
        • For invalid memory values, consider what earlier operations (perhaps in completely separate function calls) may have saved (or failed to save) this value. Look ahead to the memory tips.
      • Continue tracing backwards treating these producer operations as broken operations.
    • Invalid choices: Was it invalid to apply this operation here given correct arguments (or regardless of the arguments)?
      • What control flow decision led to execution of this operation?
      • Is the logic of the decision correct?
      • If so, continue tracing backwards treating the control flow decision as a broken operation.
    • Callers: You may need to trace back beyond the function where the crash happened.
      • Get a backtrace to see where the current function was called. (Don’t just assume you know which function called this one. Get the truth.)
      • If you want to inspect local variables in functions that called this one, use up and down in gdb to step up and down the call stack, then print what you want to see.
    • Memory: Remember, mm_malloc and mm_free are called many times during a single execution. They depend on their arguments, but also the entire contents of the heap as it exists when they are called, so changes made by earlier calls to mm_malloc and mm_free affect data used by this one.
      • Use the check_heap function to scan the heap.
      • Run it at arbitrary times in gdb with call check_heap().
      • Or hard-code calls to it in your code so you see how the heap evolves with each mm_malloc or mm_free call.
  • Minimize the input. Try to write a small trace that captures the essence of the large trace on which your allocator has an error. A smaller trace is easier to reason about in full.

• valgrind will be less useful since you are doing very low-level work, implementing the memory allocator itself. valgrind excels in analyzing programs that use the memory allocator.

• If resorting to printing (try gdb first), use fprintf(stderr, "...", ...) instead of printf("...", ...) and be sure to remember newline for clarity. Disable any printing in final version.

• Use the mdriver -f option. During initial development, using tiny trace files will simplify debugging and testing. We have included two such trace files (short1-bal.rep and short2-bal.rep) that you can use for initial debugging. You can also write your own for targeted debugging/testing.

• Use the mdriver -V option. The -V will option will give a detailed summary for each trace file and indicate when each trace file is read, which will help you isolate errors.

• Does your code seem to be running forever?
  • That might be because it is no longer broken! Comment out those calls to check_heap. Printing the full contents of the heap on every memory management event costs orders of magnitude more than the allocations or frees themselves.
  • Or it might be because you have a size 0 block somewhere other than the heap footer word.

Optimize Judiciously

“… avoid premature optimization…” – Donald Knuth (or Tony Hoare?) and countless others.

When your program is not as efficient as you wish, it is easy to jump in and start hacking on the first part that comes to mind as a potential reason for poor performance. It is also generally useless to do this unless the program is tiny and you completely understand it. A much better approach is to first:

1. Make sure you have enabled all available automatic optimizations, such as compiler optimizations.
2. If this does not yield sufficient gains, then:
   • Gather and analyze empirical data about where your program is spending its time or other resources.
   • Use this data to form a hypothesis about what particular implementation features are “bottlenecks” contributing to poor performance.
   • Now you are ready to attempt some modifications and use this same measurement process to evaluate their impact.
     • Think first in Big-O terms. Consider lower level implementation optimizations only once you have exhausted opportunities for algorithmic optimizations.

Using a Profiler for More Detailed Time Measurement

Your performance index measures the efficiency of your implementation, but gives no hints about why or where it is (in)efficient. Using a profiler can help answer these questions and support more informed choices about performance engineering.

A profiler essentially measures (via some approximation) where your code spends most of its execution time. Presented with a report of this information, it is hopefully intuitive that:

• Functions that account for the largest chunk of execution time are the functions where you should focus your optimization efforts: In an ideal world, doubling the speed of a function that accounts for 50% of overall execution time should cut 25% off the execution time.
• Functions that account for only small fractions of execution time are not worth optimizing: even if you could eliminate the cost of a function that accounts for 0.5% of execution time, this would make overall execution only 0.5% faster.

Things are not quite this clear-cut, since there can be complex interactions between the choices made in one function and the efficiency of another. However, to a first approximation, this is a useful way of thinking about profiling results.

gprof is a great place to start. Enable it by passing the -pg option to the compiler. (See comments in Makefile.) Now, when run, the compiled executable will generate a file gmon.out that can be interpreted by running the gprof command. Read about gprof for more on how to use the profiler and its results. Be sure to turn off -pg for your performance evaluation, because it will slow things down.

Submission

Submit: The course staff will collect your work directly from your hosted repository as of the deadline. To submit your work:

1. Make sure you have committed your latest changes.

   $ git add ...
   $ git commit ...

2. Run the command cs240 sign to sign your work and respond to any assignment survey questions.

   $ cs240 sign

3. Push your signature and your latest local commits to the hosted repository.

   $ git push

Confirm: After pushing, all local changes have been submitted if the output of git status shows both:

• Your branch is up to date with 'origin/master', meaning all local commits have been pushed
• nothing to commit, meaning all local changes have been committed

Resubmit: If you realize you need to change something later, just repeat this process.

Grading

Your grade will be calculated from 100 points as follows:

• Preparatory Exercises (10 points):
  • Keep your completed exercises to show to tutors/instructors if asking code questions. Submit them before the due date by either:
    • Adding, committing, and pushing a PDF in your repository; or
    • Submitting a paper copy in person or under the door.
• Documentation and Style (10 points):
  • Document your code clearly.
  • Follow the programming rules.
• Correctness (40 points): based on passing mdriver tests
  • 2 points each for short1-bal.rep and short2-bal.rep.
  • 4 points each for all remaining traces.
  • The realloc*.rep traces are excluded.
• Performance (40 points): 40 × P
  • P is the mdriver performance index.
• Extra Fun Successful open-ended extensions may earn additional points.

You may use any implementation strategy that works (subject to programming rules). Allocator performance is a large component of the grade for this assignment. Do the arithmetic: a high-quality implicit free list allocator can achieve a reasonable grade.

Extra Fun Open-Ended Extensions

There are a number of interesting allocator features you could add if looking for more fun or extra credit. Each is annotated with a possible extra credit award for a thorough, well-designed, well-implemented extension. Other improvements to allocator performance on the standard test suite will naturally be reflected in your grade independent of extra credit. Talk to your instructor if you are curious about any of these extensions or if you have ideas for others. Some larger extensions would be larger than the original assignment. In general, the amount of work required per extra point is far larger than the amount of work required per standard point.

Implement realloc

(Up to +10) Implement a final memory allocation-related function: mm_realloc. The signature for this function, which you will find in your mm.h file, is:

extern void* mm_realloc(void* ptr, size_t size);

Similarly, you should add the following in your mm.c file:

void* mm_realloc(void* ptr, size_t size) {
  // ... implementation here ...
}

Follow the contract of the standard C library’s realloc exactly (pretending that malloc and free are mm_malloc and mm_free, etc.). The man page entry for realloc says:

   The realloc() function changes the size of the memory block pointed to by
   ptr to size bytes.  The contents will be unchanged in the range from the
   start of the region up to the minimum of the old and new sizes.  If the
   new size is larger than the old size, the added memory will not be
   initialized.  If ptr is NULL, then the call is equivalent to
   malloc(size), for all values of size; if size is equal to zero, and ptr
   is not NULL, then the call is equivalent to free(ptr).  Unless ptr is
   NULL, it must have been returned by an earlier call to malloc(), calloc()
   or realloc().  If the area pointed to was moved, a free(ptr) is done.

A good test would be to compare the behavior of your mm_realloc to that of realloc, checking each of the above cases. Your implementation of mm_realloc should also be performant. Avoid copying memory if possible, making use of nearby free blocks. You may not use standard library functions such as memcpy to copy memory. Instead, copy WORD_SIZE bytes at a time to the new destination while iterating over the existing data.

To run tracefiles that test mm_realloc, compile using make mdriver-realloc. Then, run mdriver-realloc with the -f flag to specify a tracefile, or first edit config.h to include additional realloc tracefiles in the default list.

Extended Error-Checking

(Up to +100) Augment the allocator to do additional error-checking on the fly to help detect common memory errors such as invalid frees (bad address), double-free, use-after-free, out-of-bounds access on heap objects corrupting heap metadata, etc. You could insert extra padding, use canary values, place recently freed blocks in a waiting area, track additional information about earlier allocations and frees to detect errors, or more. Come chat if you have ideas or interest here.