QTrace: a framework for customizable full system instrumentation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work presents QTrace, an open-source instrumentation extension API for QEMU (1) that can instrument unmodified applications and OS binaries for uni- and multi-processor systems. QTrace facilitates the development of custom, full-system instrumentation tools for the X86 guest architecture enabling statistics collection and program execution studies including system-level code. This paper: illustrates QTrace's API through instrumentation examples, discusses how QEMU was modified to implement QTrace, explains the validation testing procedures, shows QTrace's usefulness in comparison to a user-level binary instrumentation tool in workloads that spend significant time in the kernel, and illustrates that QTrace does not impose a significant performance penalty. Experiments show that for an instruction count plug-in, QTrace is 12.2X slower than PIN [2], a user-level only instrumentation tool, and 4.1X faster than BOCHS [3], a full-system emulator. QTrace without instrumentation performs similarly to the un-modified QEMU.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it