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Facundo Tuesca

dblp:251/5614 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0004-1650-1421ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Program analysis · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis
dynamic analysis
0.812024
PolyTracker: Whole-Input Dynamic Information Flow Tracing · ISSTA 2024
Program analysis › dynamic analysis
dynamic information-flow tracking
0.812024
PolyTracker: Whole-Input Dynamic Information Flow Tracing · ISSTA 2024
Program analysis › static analysis
bug detection
0.212024
PolyTracker: Whole-Input Dynamic Information Flow Tracing · ISSTA 2024

Methods — techniques the papers use, named apart from their topics

fuzzing · 0.8LLVM instrumentation · 0.8
YearPublicationVenuePosition
2024 PolyTracker: Whole-Input Dynamic Information Flow Tracing
abstract
We present PolyTracker, a whole-program, whole-input dynamic information flow tracing (DIFT) framework. Given an LLVM compatible codebase or a binary that has been lifted to LLVM intermediate representation (IR), PolyTracker compiles it, adding static instrumentation. The instrumented program will run normally with modest performance overhead, but will additionally output a runtime trace artifact in the co-designed TDAG (Tainted Directed Acyclic Graph) format. TDAGs can be post-processed for a variety of analyses, including tracing every input byte through program execution. TDAGs can be generated either by running the program over a corpus of inputs or by employing a randomized input generator such as a fuzzer. PolyTracker traces (TDAGs) are useful not only for very localized, targeted dynamic program analysis as with smaller-scale DIFT: TDAGs are primarily intended for whole-program runtime exploration and bug finding, granular information-flow diffing between program runs, and comparisons of implementations of the same input specification without any need to emulate and instrument the entire running environment. For user-friendliness and reproducibility, the software repository provides a number of examples of PolyTracker-instrumented builds of popular open-source software projects. We also provide an analysis library and REPL written in Python that are designed to assist users with operating over TDAGs.
Evan Sultanik, Marek Surovic, Henrik Brodin, Kelly Kaoudis, Facundo Tuesca, Carson Harmon, Lisa Overall, Joseph Sweeney, Bradford Larsen
ISSTA5