# 2.1. Cross Translation Unit (CTU) Analysis¶

Normally, static analysis works in the boundary of one translation unit (TU). However, with additional steps and configuration we can enable the analysis to inline the definition of a function from another TU.

## 2.1.1. Manual CTU Analysis¶

Let’s consider these source files in our minimal example:

// main.cpp
int foo();

int main() {
return 3 / foo();
}

// foo.cpp
int foo() {
return 0;
}


And a compilation database:

[
{
"directory": "/path/to/your/project",
"command": "clang++ -c foo.cpp -o foo.o",
"file": "foo.cpp"
},
{
"directory": "/path/to/your/project",
"command": "clang++ -c main.cpp -o main.o",
"file": "main.cpp"
}
]


We’d like to analyze main.cpp and discover the division by zero bug. In order to be able to inline the definition of foo from foo.cpp first we have to generate the AST (or PCH) file of foo.cpp:

$pwd$ /path/to/your/project
$clang++ -emit-ast -o foo.cpp.ast foo.cpp$ # Check that the .ast file is generated:
$ls compile_commands.json foo.cpp.ast foo.cpp main.cpp$


The next step is to create a CTU index file which holds the USR name and location of external definitions in the source files:

$clang-extdef-mapping -p . foo.cpp c:@F@foo# /path/to/your/project/foo.cpp$ clang-extdef-mapping -p . foo.cpp > externalDefMap.txt


We have to modify externalDefMap.txt to contain the name of the .ast files instead of the source files:

$sed -i -e "s/.cpp/.cpp.ast/g" externalDefMap.txt  We still have to further modify the externalDefMap.txt file to contain relative paths: $ sed -i -e "s|$(pwd)/||g" externalDefMap.txt  Now everything is available for the CTU analysis. We have to feed Clang with CTU specific extra arguments: $ pwd
/path/to/your/project
$clang++ --analyze -Xclang -analyzer-config -Xclang experimental-enable-naive-ctu-analysis=true -Xclang -analyzer-config -Xclang ctu-dir=. -Xclang -analyzer-output=plist-multi-file main.cpp main.cpp:5:12: warning: Division by zero return 3 / foo(); ~~^~~~~~~ 1 warning generated.$ # The plist file with the result is generated.
$ls compile_commands.json externalDefMap.txt foo.ast foo.cpp foo.cpp.ast main.cpp main.plist$


This manual procedure is error-prone and not scalable, therefore to analyze real projects it is recommended to use CodeChecker or scan-build-py.

## 2.1.2. Automated CTU Analysis with CodeChecker¶

The CodeChecker project fully supports automated CTU analysis with Clang. Once we have set up the PATH environment variable and we activated the python venv then it is all it takes:

$CodeChecker analyze --ctu compile_commands.json -o reports [INFO 2019-07-16 17:21] - Pre-analysis started. [INFO 2019-07-16 17:21] - Collecting data for ctu analysis. [INFO 2019-07-16 17:21] - [1/2] foo.cpp [INFO 2019-07-16 17:21] - [2/2] main.cpp [INFO 2019-07-16 17:21] - Pre-analysis finished. [INFO 2019-07-16 17:21] - Starting static analysis ... [INFO 2019-07-16 17:21] - [1/2] clangsa analyzed foo.cpp successfully. [INFO 2019-07-16 17:21] - [2/2] clangsa analyzed main.cpp successfully. [INFO 2019-07-16 17:21] - ----==== Summary ====---- [INFO 2019-07-16 17:21] - Successfully analyzed [INFO 2019-07-16 17:21] - clangsa: 2 [INFO 2019-07-16 17:21] - Total analyzed compilation commands: 2 [INFO 2019-07-16 17:21] - ----=================---- [INFO 2019-07-16 17:21] - Analysis finished. [INFO 2019-07-16 17:21] - To view results in the terminal use the "CodeChecker parse" command. [INFO 2019-07-16 17:21] - To store results use the "CodeChecker store" command. [INFO 2019-07-16 17:21] - See --help and the user guide for further options about parsing and storing the reports. [INFO 2019-07-16 17:21] - ----=================---- [INFO 2019-07-16 17:21] - Analysis length: 0.659618854523 sec.$ ls
compile_commands.json  foo.cpp  foo.cpp.ast  main.cpp  reports
$tree reports reports ├── compile_cmd.json ├── compiler_info.json ├── foo.cpp_53f6fbf7ab7ec9931301524b551959e2.plist ├── main.cpp_23db3d8df52ff0812e6e5a03071c8337.plist ├── metadata.json └── unique_compile_commands.json 0 directories, 6 files$


The plist files contain the results of the analysis, which may be viewed with the regular analysis tools. E.g. one may use CodeChecker parse to view the results in command line:

$CodeChecker parse reports [HIGH] /home/egbomrt/ctu_mini_raw_project/main.cpp:5:12: Division by zero [core.DivideZero] return 3 / foo(); ^ Found 1 defect(s) in main.cpp ----==== Summary ====---- ----------------------- Filename | Report count ----------------------- main.cpp | 1 ----------------------- ----------------------- Severity | Report count ----------------------- HIGH | 1 ----------------------- ----=================---- Total number of reports: 1 ----=================----  Or we can use CodeChecker parse -e html to export the results into HTML format: $ CodeChecker parse -e html -o html_out reports
$firefox html_out/index.html  ## 2.1.3. Automated CTU Analysis with scan-build-py (don’t do it)¶ We actively develop CTU with CodeChecker as a “runner” script, scan-build-py is not actively developed for CTU. scan-build-py has various errors and issues, expect it to work with the very basic projects only. Example usage of scan-build-py: $ /your/path/to/llvm-project/clang/tools/scan-build-py/bin/analyze-build --ctu
analyze-build: Run 'scan-view /tmp/scan-build-2019-07-17-17-53-33-810365-7fqgWk' to examine bug reports.
$/your/path/to/llvm-project/clang/tools/scan-view/bin/scan-view /tmp/scan-build-2019-07-17-17-53-33-810365-7fqgWk Starting scan-view at: http://127.0.0.1:8181 Use Ctrl-C to exit. [6336:6431:0717/175357.633914:ERROR:browser_process_sub_thread.cc(209)] Waited 5 ms for network service Opening in existing browser session. ^C$