CppCon 2023

Large language models like GPT-4 are achieving state of the art results in a wide variety of well-studied areas, eclipsing past work in well-studied areas like auto-completion. I argue that they should also presage a "Cambrian explosion" – a wave of radically new kinds of software development tools, all powered by AI, that will make all our lives easier. This talk will focus on several tools of particular interest to C++ developers. First, as any C++ developer knows, C++ compiler errors are notoriously verbose and can be hard to decode even for experts. To address this challenge, we created CWhy, a compiler wrapper that translates C or C++ compiler errors into readable explanations, and even proposes potential fixes. Beyond compile-time errors, C++ developers must also spend considerable time in debuggers (like `gdb` or `lldb`) trying to track down the root cause of runtime errors. To simplify this task, we created ChatDBG, a system that augments debuggers with a new command you can run for post-mortem debugging: `why`. This command performs a root cause analysis of the issue leading to the error (e.g., a segfault) and proposes a fix. For both of these projects, we share some details about their internal workings, describe how they can effectively leverage large language models, and present examples of them in action.