Code coverage without instrumentation

Typically, to collect structural coverage results from software tests, you apply instrumentation to source code. But what if you can't apply instrumentation (because you only have access to object code), or just don't want to (to reduce instrumentation overheads and ensure that what you test is what you deploy)?

In this blog, we'll explore some methods we’ve been developing to perform instrumentationless code coverage analysis by using branch traces – traces generated from program execution that contain information on which branches were taken. The methods include one using a machine emulator (QEMU), and another using hardware (Intel Processor Trace).

Zero-instrumentation coverage on an emulator

We modified QEMU, an open source machine emulator that supports multiple popular operating systems, to collect coverage without instrumentation. To do this, we made the emulator produce a branch trace when it runs, which we can later parse to determine which elements of the object code were executed.

We compile the test program to an ELF file, so it runs “bare metal”, without an OS. If we didn’t do this, the generated trace would contain all the branches that executed in the kernel as well as in our program, and we would have to remove this data from the trace before subsequent processing.

We then run the trace through RapiCover to produce a coverage report. Figure 1 demonstrates the overall process on a snippet of code from the project.

  • Figure 1a: Excerpt from source code, written in C

  • Figure 1b: Disassembly of source code, highlighting select instructions

  • Figure 1c: Branch trace, highlighting 4 recursive calls to f5 with addresses matching those in Figure 1b

  • Figure 1d: Coverage of functions f5 and f4, showing full coverage

Zero-instrumentation coverage on hardware

Okay, so we can collect coverage data without instrumentation from a simulator we have full control over – can we do the same from physical hardware, where we don’t have that control?

To explore this, we used Intel Processor Trace (IPT), a feature built into newer Intel chipsets that lets you collect branch trace information from CPU cores.

We turn on IPT via the Linux perf tool, and then run our program. Next, we use the IPT C library to decode the output data and produce a branch trace in a format that our tools can read.

Eight top code coverage questions in embedded avionics systems

This white paper sets out eight key code coverage questions for engineers working on embedded real-time avionics systems, before introducing a software tool – RapiCover – which is designed to conduct code coverage measurement on an embedded avionics target.


IPT compresses data to reduce performance overheads, storing only whether each branch is taken or not. We can’t use the compressed data directly, as it isn't clear which branch is taken. To restore this information, we disassemble the program, generate a control flow graph (CFG) from the disassembly, and match elements in the CFG to the IPT trace.

Again, we use RapiCover to analyze the results. Figure 2 shows the overall process.

Figure 2. Process for collecting coverage via Intel Processor Trace

Closing remarks

A benefit of using branch traces to analyze structural coverage is that it means we can collect coverage from any executable written in any language, as long as we can obtain a disassembly of the object code. The programs we used while developing the Intel Processor Trace method, for example, were written in assembly language!

We’re continuing to explore new methods to collect coverage data with zero instrumentation. If you’re interested in obtaining zero-instrumentation coverage of your code, contact us to see how we can help.

Thomas Yau