Eliminate vulnerabilities with source code analysis tool

CodePeer is a source code analysis tool that detects run-time and logic errors in Ada programs. Serving as an efficient and accurate code reviewer, CodePeer identifies constructs that are likely to lead to run-time errors such as buffer overflows, and it flags legal but suspect code typical of logic errors.

Going well beyond the capabilities of typical static analysis tools, CodePeer also produces a detailed analysis of each subprogram, including pre- and postconditions. Such an analysis makes it easier to find potential bugs and vulnerabilities early: if the implicit specification deduced by CodePeer does not match the component’s requirements, a reviewer is alerted immediately to a likely logic error.

CodePeer can be used both during system development – to prevent errors from being introduced or as part of a systematic code review process to dramatically increase the efficiency of human review – and retrospectively on existing code, to detect and remove latent bugs.

CodePeer can be used either as a standalone tool or fully integrated into the GNAT Pro Ada development environment. It can be tuned based on the memory and speed available on the developer’s machine, and can efficiently exploit multi-core CPUs. CodePeer can be run on partially complete programs; it does not require stubs or drivers.

CodePeer analyzes programs for a wide range of flaws including use of uninitialized data, pointer misuse, buffer overflow, numeric overflow, division by zero, dead code, and concurrency faults (race conditions). These sorts of errors can be difficult and expensive to detect and correct with conventional debugging, but CodePeer identifies them statically, without running the program, and determines not only where the failure could occur, but identifies where the bad values originate, be it within the current subprogram or from some distant subprogram that reached the point of failure through a series of calls.

CodePeer also looks for code that, although syntactically and semantically correct, is performing a suspect computation, such as an assignment to a variable that is never subsequently referenced, or a conditional test that always evaluates to the same true or false value.