Category Archives: coding

Bounds checking, leak checks and race conditions check with gcc sanitize

If you are coding since many years in C or C++ you probably hit many tools that helped in finding memory leaks in your code as well as did bounds checking to avoid buffers overrun. Those were PurifyPlus (rational), BoundsChecker (numega). Then valgrind cameout and all linux developers were happy to run valgrind on their code to find leaks and bounds overruns.

Since gcc 4.8 and llvm 3.1 Sanitize has been introduce in the compiler as a compile option which gives you the ability to check for :

  • leak and bounds overrun : -fsanitize=address
  • race conditions : -fsanitize=thread

Using sanitizer in your normal Test environment (we use c++ google test framework to test api code) will drastically change the quality of your software products (C, C++ or GO) by allowing you to spot most of the bounds overrun and leaks during the testing phase, both in your code and in the code that you include not written by you.

In my sample makefiles we build all component that we use in test in debug mode (-g3) and with sanitize settable from outside via an environment variable :

SANITIZE = -fsanitize=address

CXXFLAGS = -std=c++11 -pthread -fpermissive -isystem ../../googletest/include -isystem ../../googletest -DDEBUG -g3 $(SANITIZE)

Compiling a library with sanitize is :

$ make -f libfh.mk debugclean debuglinux
rm -rf fh.do fh.mo libfh-debug.a
cc -DDEBUG -g3 -fsanitize=address -O0 -fPIC --std=c99 -Wall -Wextra -Wcomment -pthread -I . -c fh.c -o fh.do
ar crs libfh-debug.a fh.do

Compiling tests :

$ make -f libfh-test.mk testclean testlinux
rm -rf TestMain.o TestThread.o TestFH.o CommandLineParams.o testfh *.gcda *.gcno gtest-all.o ../../*_test_results.xml
g++ -std=c++11 -pthread -fpermissive -isystem ../../googletest/include -isystem ../../googletest -DDEBUG -g3 -fsanitize=address -I.. -I ../../libutil/src -c -o TestMain.o TestMain.cpp
g++ -std=c++11 -pthread -fpermissive -isystem ../../googletest/include -isystem ../../googletest -DDEBUG -g3 -fsanitize=address -I.. -I ../../libutil/src -c -o TestThread.o TestThread.cpp
g++ -std=c++11 -pthread -fpermissive -isystem ../../googletest/include -isystem ../../googletest -DDEBUG -g3 -fsanitize=address -I.. -I ../../libutil/src -c -o TestFH.o TestFH.cpp
g++ -std=c++11 -pthread -fpermissive -isystem ../../googletest/include -isystem ../../googletest -DDEBUG -g3 -fsanitize=address -I.. -I ../../libutil/src -c -o CommandLineParams.o CommandLineParams.cpp
g++ -isystem ../../googletest/include -I ../../googletest/ -pthread -c ../../googletest/src/gtest-all.cc
g++ -o testfh -fsanitize=address TestMain.o TestThread.o TestFH.o CommandLineParams.o gtest-all.o -L ../ -lfh-debug -lpthread

Now let’s run a test (after having introduced a bug) :


paul@paul-bigdesk:~/git/clibs/libfh/test$ ./testfh --gtest_filter=*hash_with_struct*
Running main() in file c-libraries/libfh/test/TestMain.cpp
Now running test executable: ./testfh
Note: Google Test filter = *hash_with_struct*
[==========] Running 1 test from 1 test case.
[----------] Global test environment set-up.
[----------] 1 test from FH
[ RUN ] FH.hash_with_struct
=================================================================
==23907==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x60200000eb5f at pc 0x7f37a13bc964 bp 0x7fff66eca0b0 sp 0x7fff66ec9858
WRITE of size 16 at 0x60200000eb5f thread T0
#0 0x7f37a13bc963 in __asan_memcpy (/usr/lib/x86_64-linux-gnu/libasan.so.2+0x8c963)
#1 0x466298 in fh_insert /home/paul/git/clibs/libfh/fh.c:390
#2 0x414ed5 in FH_hash_with_struct_Test::TestBody() /home/paul/git/clibs/libfh/test/TestFH.cpp:486
#3 0x45683e in void testing::internal::HandleSehExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x45683e)
#4 0x44fdf6 in void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x44fdf6)
#5 0x433737 in testing::Test::Run() (/home/paul/git/clibs/libfh/test/testfh+0x433737)
#6 0x4340cf in testing::TestInfo::Run() (/home/paul/git/clibs/libfh/test/testfh+0x4340cf)
#7 0x4347c2 in testing::TestCase::Run() (/home/paul/git/clibs/libfh/test/testfh+0x4347c2)
#8 0x43b8b5 in testing::internal::UnitTestImpl::RunAllTests() (/home/paul/git/clibs/libfh/test/testfh+0x43b8b5)
#9 0x457e16 in bool testing::internal::HandleSehExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x457e16)
#10 0x450c6e in bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x450c6e)
#11 0x43a35b in testing::UnitTest::Run() (/home/paul/git/clibs/libfh/test/testfh+0x43a35b)
#12 0x406819 in main /home/paul/git/clibs/libfh/test/TestMain.cpp:38
#13 0x7f37a07c582f in __libc_start_main (/lib/x86_64-linux-gnu/libc.so.6+0x2082f)
#14 0x406538 in _start (/home/paul/git/clibs/libfh/test/testfh+0x406538)

0x60200000eb5f is located 0 bytes to the right of 15-byte region [0x60200000eb50,0x60200000eb5f)
allocated by thread T0 here:
#0 0x7f37a13c8662 in malloc (/usr/lib/x86_64-linux-gnu/libasan.so.2+0x98662)
#1 0x466222 in fh_insert /home/paul/git/clibs/libfh/fh.c:384
#2 0x414ed5 in FH_hash_with_struct_Test::TestBody() /home/paul/git/clibs/libfh/test/TestFH.cpp:486
#3 0x45683e in void testing::internal::HandleSehExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x45683e)
#4 0x44fdf6 in void testing::internal::HandleExceptionsInMethodIfSupported<testing::Test, void>(testing::Test*, void (testing::Test::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x44fdf6)
#5 0x433737 in testing::Test::Run() (/home/paul/git/clibs/libfh/test/testfh+0x433737)
#6 0x4340cf in testing::TestInfo::Run() (/home/paul/git/clibs/libfh/test/testfh+0x4340cf)
#7 0x4347c2 in testing::TestCase::Run() (/home/paul/git/clibs/libfh/test/testfh+0x4347c2)
#8 0x43b8b5 in testing::internal::UnitTestImpl::RunAllTests() (/home/paul/git/clibs/libfh/test/testfh+0x43b8b5)
#9 0x457e16 in bool testing::internal::HandleSehExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x457e16)
#10 0x450c6e in bool testing::internal::HandleExceptionsInMethodIfSupported<testing::internal::UnitTestImpl, bool>(testing::internal::UnitTestImpl*, bool (testing::internal::UnitTestImpl::*)(), char const*) (/home/paul/git/clibs/libfh/test/testfh+0x450c6e)
#11 0x43a35b in testing::UnitTest::Run() (/home/paul/git/clibs/libfh/test/testfh+0x43a35b)
#12 0x406819 in main /home/paul/git/clibs/libfh/test/TestMain.cpp:38
#13 0x7f37a07c582f in __libc_start_main (/lib/x86_64-linux-gnu/libc.so.6+0x2082f)

SUMMARY: AddressSanitizer: heap-buffer-overflow ??:0 __asan_memcpy
Shadow bytes around the buggy address:
0x0c047fff9d10: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x0c047fff9d20: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x0c047fff9d30: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x0c047fff9d40: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
0x0c047fff9d50: fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa fa
=>0x0c047fff9d60: fa fa fa fa fa fa fa fa fa fa 00[07]fa fa 05 fa
0x0c047fff9d70: fa fa 00 00 fa fa 00 00 fa fa 00 fa fa fa 00 fa
0x0c047fff9d80: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa
0x0c047fff9d90: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa
0x0c047fff9da0: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa
0x0c047fff9db0: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa
Shadow byte legend (one shadow byte represents 8 application bytes):
Addressable: 00
Partially addressable: 01 02 03 04 05 06 07
Heap left redzone: fa
Heap right redzone: fb
Freed heap region: fd
Stack left redzone: f1
Stack mid redzone: f2
Stack right redzone: f3
Stack partial redzone: f4
Stack after return: f5
Stack use after scope: f8
Global redzone: f9
Global init order: f6
Poisoned by user: f7
Container overflow: fc
Array cookie: ac
Intra object redzone: bb
ASan internal: fe
==23907==ABORTING

You easily get to were the bug is fh.c line 390; we decremented the allocated size by 1:

new_opaque_obj = malloc(fh->h_datalen-1);

Easily you can switch to race conditions checking my using

$ make SANITIZE=-fsanitize=thread -f libfh-test.mk testclean testlinux

Design for simplicity : software options

xkcd.com

(I was highly inspired by Evan Martin post before trying to recap in this post)
Think twice before adding an option to a software; options are :

  • bad user experience : good software just works without asking to many things to the user.
  •  a maintenance cost : an option is a feature you have to maintain/test for the lifetime of the software
  • documentation cost : every option, even the most cryptical, should be documented to the user, explained and you should provide some examples of use. When you normally try to do this you end up removing the option from documentation
  • normally options are a way to delegate to user a decision that the designer failed to take : “shall we open on the last opened document or shall put an options ‘always open on blank document’ ?
  • remember the paradox of choice
  • options setting generates bad GUIs : they are hard to present, group or organize.

On the other hand consider that any change you make will probably break someone’s workflow, no doubt, so the temptation to create an option to enable the previous operational mode is high.

The old windows search wizard, awesome, read this : https://www.joelonsoftware.com/2000/04/12/choices/

WTF/Minute : code quality measure unit

 Some day your code will be reviewed, modified or even just read to understand the underlying algorithm by someone else that is not you that wrote the code….

My point here is that readability/maintainability of code is by far the biggest quality of a piece of software. Being able to read the code and understand it rapidly makes everything easier, either bugfixing or modifying/enhancing the code. Think that the next one that might be reading the code might not be as experienced as you with that language so

  • avoid using  unnecessarily complicated constructs that feed you coder ego but slow down the maintenance activity. You are a good coder, no doubt, but if your code is not readable by the average coder that will have to then you are not making a good service to your colleagues
  • Make clear what your code is doing and, if necessary use a comment to clarify what is not evident from the code (I’m not a huge fan of comments because most of them don’t tell anything more than the code). Use comments to refer to a requirement/user-story that is being implemented.
  • Stick to the language style guidelines that were set for your team/company
  • Tests are code too and often are read/reviewed more than real code : don’t fuck up in tests code just because “this is just a test, this code will not run in production”

Discussion on code quality is huge of course and these are simple rules that will impact on maintainability of your code (since a reviewer is doing the same activity of the next coder which will have to work on your code : read it). If you want to dig deeper into code quality measurement I’ll suggest this work from Idan Amit and Dror G. Feitelson really interesting : https://arxiv.org/pdf/2007.10912.pdf

Comic comes from here

Milan skies after fires in the alps, 2018

Hash functions – efficency and speed

A hash function is any function that can be used to map data of arbitrary size to data of a fixed size. The values returned by a hash function are called hash values, hash codes, digests, or simply hashes. Hash functions are often used in combination with a hash table, a common data structure used in computer software for rapid data lookup.

If you happen to need a non cryptographic hash function (and you might need it even if your are using languages that have builtin hashtables like java or c++ ) here are some references taken from various parts:

Interesting comparison of different hash tables :

http://www.eternallyconfuzzled.com/tuts/algorithms/jsw_tut_hashing.aspx

Some more hash functions here :

http://www.cse.yorku.ca/~oz/hash.html

Some really interesting benchmarks strchr.com/hash_functions by Peter Kankowsky.

And again hash benchmarks sanmayce.com/Fastest_Hash/.

Hash benchmarks in Rust by https://medium.com/@tprodanov/benchmarking-non-cryptographic-hash-functions-in-rust-2e6091077d11

And more benchmarks : https://medium.com/logos-network/benchmarking-hash-and-signature-algorithms-6079735ce05

Some (a mininum set) benchmarks ran using random keys of random len, 1.5 multiply factor on hash size, next power of 2 hash sizes :

Tests are run on random keys
--- hash_function speed on random long (100-350) keys
Keys    HashFunc         HashSize AvgTime(ns) Collisions LongestChain DimFactor
1000000 djb_hash         4194304    191.03      110620    6            1.500000
1000000 murmur64a_hash   4194304    60.87       110830    7            1.500000
1000000 wyhash_hash      4194304    36.69       110170    5            1.500000
1000000 elf_hash         4194304    444.25      110488    5            1.500000
1000000 jen_hash         4194304    143.90      110471    5            1.500000
1000000 djb2_hash        4194304    189.63      111048    6            1.500000
1000000 sdbm_hash        4194304    247.92      110087    6            1.500000
1000000 fnv_hash         4194304    247.87      110170    6            1.500000
1000000 oat_hash         4194304    309.55      110538    6            1.500000

--- hash_function speed on short keys (10 to 45 char len)
Keys    HashFunc        HashSize AvgTime(ns) Collisions LongestChain DimFactor
1000000 djb_hash         4194304    31.14       110363    6            1.500000
1000000 murmur64a_hash   4194304    28.24       110264    6            1.500000
1000000 wyhash_hash      4194304    21.84       109798    5            1.500000
1000000 elf_hash         4194304    49.88       110845    5            1.500000
1000000 jen_hash         4194304    33.28       110541    5            1.500000
1000000 djb2_hash        4194304    31.21       110664    6            1.500000
1000000 sdbm_hash        4194304    35.60       109906    6            1.500000
1000000 fnv_hash         4194304    35.59       109940    6            1.500000
1000000 oat_hash         4194304    43.28       110123    6            1.500000

Tests done with the hash table code you can find github.com/paulborile/clibs

And last a research study for SIMD optimized hash functions : arxiv.org/pdf/1612.06257.pdf  some theory and code github.com/google/highwayhash/blob/master/c/highwayhash.c. The all use the vector extensions present in gcc.

Photo by Luca Campioni on Unsplash

Code benchmarks : how can I measure how fast my software is (and make it faster) ?

You probably heard many times a coder say “this way is faster” : nothing can be more wrong nowadays unless you prove your statement by measuring the same piece of code running with algorithm A and algorithm B (the faster one). And there were times when you could measure the speed of the execution time of a program 1, 2 or 10 times without noticeable variability : those times are gone. Measuring how fast a piece of software runs is about getting a set of results with the lowest possible variability.

Variability in computing time in modern computer architectures is just unavoidable; while we can guarantee the results of a computation we cannot guarantee how fast this computation will be :

“Computer can reproduce anwsers, not performance” : Bryce Adelstein Lellback, https://youtu.be/zWxSZcpeS8Q?t=6m45s

Reasons for variance in computation time can be recap in :

  • Hardware jitter : instruction pipelines, cpu frequency scaling and power management, shared caches and many other things
  • OS activities : a huge list of things the kernel can do to screw up your benchmark performance
  • Observer effect : every time we instruments code to measure performance we introduce variance.

Also warming up the cpu seems to have become necessary to get meaningful results. Running hot instead of cold on a single piece of code is well described here :

https://youtu.be/zWxSZcpeS8Q?t=18m51s

This said the process for benchmarking an piece of code is :

  • Write some benchmark code : define a subset of execution (let’s call it op1) in your code and measure how many op1/sec. Do the same for other parts (op2, op3) but be sure that all parts can be run indipendently from each other   
  • Assure that samples population that we get is “normal” distributed

In details I use C code to measure and :

  • Use GNU Scientific Library (gsl) for mean, median, variance, stdev, skew running stats
  • Use CLOCK_MONOTONE clock_gettime() mode. An example code here.
  • Check if the set returned has ‘normal’ distribution : find the algorithm you like here (I use mean-median/max(mean,median) < 1%, not really correct but ok for my purposes).
  • Narrow down as much as possible the size of the code you are measuring
  • Warm up the cpu before taking samples to avoid having too much variability. You do this by running the code you want to measure many times before actually taking samples. Ideally you should run it until you have normal distributed results. If you don’t then probably the piece of code you are measuring is too big and you are experiencing the effects of other perturbations (os ? io ?).
  • Consider using a benchmark framework : google benchmark (c++) is great for this but I’m afraid you will have to measure C++ code.
  • Lock the cpu clock (if you can) on the host you are using for benchmarks.

Prepare to see strange results 🙂