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PLDI 2020
Mon 15 - Fri 19 June 2020

Almost all modern production software is compiled with optimization.
Debugging optimized code is a desirable functionality.
For example,
developers usually perform post-mortem debugging on the coredumps produced by
software crashes.
Designing reliable debugging techniques for optimized code
has been well-studied in the past.
However, little is known about the correctness of the debug information generated by optimizing compilers when debugging optimized code.

Optimizing compilers emit debug information (e.g., DWARF information) to support
source code debuggers.
Wrong debug information causes debuggers to either
crash or to display
wrong variable values.
Existing debugger validation techniques only focus on testing the interactive aspect of
debuggers for dynamic languages (i.e., with unoptimized code).
Validating debug information for optimized code raises some unique
many breakpoints cannot be reached by debuggers due to
code optimization; and (2)
inspecting some arbitrary variables such as uninitialized variables introduces undefined

This paper presents the first generic framework for systematically testing debug information with
optimized code.
We introduce a novel concept called \emph{actionable program}.
An actionable program $P_{\langle s,
v\rangle}$ contains a program location $s$ and a
variable $v$ to inspect.
Our key insight is that
in both the unoptimized program $P_{\langle s,v\rangle}$ and the optimized program $P^\prime_{\langle s,v\rangle}$,
debuggers should be able to stop at the program location $s$ and inspect the value of the variable $v$ without any undefined behaviors.
Our framework generates actionable programs and does systematic testing by comparing the
debugger output of $P^\prime_{\langle s,
v\rangle}$ and the actual value of $v$ at line $s$ in $P_{\langle s, v\rangle}$.
We have applied our framework to two mainstream optimizing C
compilers (i.e., GCC and LLVM).
Our framework
has led to 47 confirmed bug reports, 11 of which have already been fixed.
Moreover, in three days, our technique has found 2 confirmed bugs in the Rust
compiler. The results have demonstrated the effectiveness and generality of our framework.

Fri 19 Jun

Displayed time zone: Pacific Time (US & Canada) change

06:20 - 07:40
Parsing, Debugging, and Code SearchPLDI Research Papers at PLDI Research Papers live stream
Chair(s): Dan Barowy Williams College

YouTube lightning session video

Faster General Parsing through Context-Free Memoization
PLDI Research Papers
Grzegorz Herman Jagiellonian University, Poland
Zippy LL(1) Parsing with Derivatives
PLDI Research Papers
Romain Edelmann EPFL, Switzerland, Jad Hamza EPFL, Switzerland, Viktor KunĨak EPFL, Switzerland
Debug Information Validation for Optimized Code
PLDI Research Papers
Yuanbo Li Georgia Institute of Technology, USA, Shuo Ding Georgia Institute of Technology, USA, Qirun Zhang Georgia Institute of Technology, USA, Davide Italiano Apple, USA
Semantic Code Search via Equational Reasoning
PLDI Research Papers
Varot Premtoon Massachusetts Institute of Technology, USA, James Koppel Massachusetts Institute of Technology, USA, Armando Solar-Lezama Massachusetts Institute of Technology, USA