Kernel Korner: The Linux Test Project

Finding 500 bugs in 50 different kernel versions is the fruit of this thorough Linux testing and code coverage project.
Automation Tools

Although not required to run the test suite, the LTP has a number of related tools and projects that facilitate test automation. Two of these projects are the Software Testing Automation Framework (STAF/STAX) and the Open Source Development Lab (OSDL) Test Platform.

LTC uses STAF/STAX to manage a pool of test machines. Using the STAF/STAX Web interface you can find and configure test machines, then run and monitor any set of test programs and return the results. STAF is an open-source, multiplatform, multilanguage testing framework. It is based on the concept of reusable services, such as process control, logging and event handling that automate testing activities. At its core, STAF is a message routing dæmon that maintains a network of local and remote services and routes requests to those services. A network of STAF-enabled machines is built by running STAF clients on dedicated networked hosts. STAX is a GUI-based execution engine built on STAF, XML and Python. It provides an interface for testers to distribute, execute and process test results.

The OSDL Scalable Test Platform provides a framework for developers to execute tests against specific kernels and kernel patches through a Web-based interface. LTP is one of the tests that OSDL executes. Using the Web interface, you also can search for historic test results. The LTP Web site has detailed information regarding this framework.

Expanding the Test Suite with Coverage Analysis

The often unspoken assumption with software testing is that the test cases cover a majority of the software source code written. A test covers a line of code if running the test executes the line. Coverage analysis measures how much of the target code is run during a test and is a useful mechanism for evaluating the effectiveness of the LTP test suite. Given two test cases that run successfully, the test with the higher code coverage provides somewhat more assurance that the code is bug-free. Of course, bugs still may exist in the untested code, and even 100% coverage does not guarantee bug-free code.

Cornett's paper provides a good introduction to the many types of coverage. We've based the LTP coverage on the GCC compiler that provides statement and branch coverage. As stated earlier, statement coverage reports which lines of the source code are executed. Branch-conditional coverage reports which Boolean conditions in a control statement, such as “if” or “while”, are tested and taken. In the code below, branch-conditional coverage would tell us when the branch was taken, statement1 executed, and when it was due to condition1 or condition2 being true:

if ( condition1 || condition2 )

GCC coverage works by passing the options -fprofile-arcs -ftest-coverage to the compiler and the GCOV program that processes coverage data. GCOV produces a source file annotated with the number of times each line of code and branch condition was executed. GCC coverage was intended originally for user-space programs and needed to be adapted for the kernel because coverage data is produced only when a program terminates, which the kernel never does.

Also, because the kernel is not linked with standard C libraries, many of the GCOV structures are not present in the kernel. The LTP has published a GCOV-kernel patch to the Linux kernel that addresses these issues and allows developers to use the existing GCOV tools to gather coverage data from a running kernel. Installation instructions as well as a detailed description of the functionality provided by the patch can be found at the LTP Web site and in an Ottawa Linux Symposium paper by Paul Larson and others.

The GCOV-kernel patch is published on the LTP Web site as a separate package, but it is included in the LTP development tree. In addition to kernel code changes, when installed, the patch configures the Makefiles to pass the coverage options to GCC when the kernel is compiled. The coverage options instruct the compiler to generate code and data structures to capture information that is used to determine which lines of kernel code were executed. The user-space tool GCOV combines the source files and the files generated by running a GCOV-enabled program—in our case this is the kernel—to produce a new source code file with the count for each line of C code, representing the number of times the line was executed. Because the program output needed for GCOV is not created until the program ends, and the kernel does not terminate, the patch also creates a /proc/gcov/... tree that GCOV can use at any time to get counter data from the kernel.

To facilitate coverage analysis further, the LTP has developed a utility, LCOV, to create more useful graphic GCOV output. LCOV can be downloaded from the GCOV-kernel Web site. LCOV automates the process of extracting the coverage data from the kernel, running GCOV and producing HTML. Once the GCOV-kernel patch is applied and compiled, the coverage system can be used as follows.

First, load the gcov-proc kernel module:

insmod gcov-proc.o

Clear the GCOV counters:

lcov --reset

Run the LTP test suite or your favorite test program next, then capture GCOV data:

lcov -c -o

Create the HTML coverage tree:


genhtml is one of the LCOV tools and generates HTML output at both the directory and file level, as illustrated in Figures 1 and 2. Figure 1 is a partial screenshot of the Linux kernel source subdirectory. In this example, the total amount of code covered for the directory is 47.3%. Each line shows a filename. A color-coded meter is used to represent the amount of coverage for the file: green for files with 50% coverage or greater, yellow for files with coverage between 10% and 50% and red for files with less than 10% coverage. The last two columns show the percent coverage for the file and number of lines executed over the total number of lines instrumented. Both figures are displayed on a color-coded background. Figure 2 is a partial view of a printk.c file. This is a graphical view of the original GCOV output. A similar color coding is used to allow you to identify under-utilized code quickly. At this time, LCOV output shows only statement coverage and not branch coverage.

Figure 1. genhtml produces a code coverage report from GCOV data.

Figure 2. Color codes show under-utilized code in the source file.