Analyzing the analyzers: FlowDroid/IccTA, AmanDroid, and DroidSafe
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
Numerous static analysis techniques have recently been proposed for identifying information flows in mobile applications. These techniques are compared to each other, usually on a set of syntactic benchmarks. Yet, configurations used for such comparisons are rarely described. Our experience shows that tools are often compared under different setup, rendering the comparisons irreproducible and largely inaccurate. In this paper, we provide a large, controlled, and independent comparison of the three most prominent static analysis tools: FlowDroid combined with IccTA, Amandroid, and DroidSafe. We evaluate all tools using common configuration setup and the same set of benchmark applications. We compare the results of our analysis to the results reported in previous studies, identify main reasons for inaccuracy in existing tools, and provide suggestions for future research.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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