these-ammii/thesis
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages 1 Wiki Activity Actions

rasta

Browse source
This commit is contained in:
Jean-Marie Mineau 2025-08-17 00:10:58 +02:00
parent fe6dbb1d22
commit e794c037e8
Signed by: histausse
GPG key ID: B66AEEDA9B645AD2
10 changed files with 377 additions and 52 deletions
Download patch file Download diff file Expand all files Collapse all files

10
papers/3_rasta/3_experiments.typ
View file

@ -1,4 +1,4 @@
#import "../lib.typ": todo, highlight, num, paragraph
#import "../lib.typ": todo, highlight-block, num, paragraph
#import "X_var.typ": *
#import "X_lib.typ": *
@ -48,7 +48,7 @@ As a summary, the final ratio of successful analysis for the tools that we could
// and applications of Rasta dataset
is #mypercent(54.9, 100). When including the two defective tools, this ratio drops to #mypercent(49.9, 100).
#highlight()[
#highlight-block()[
*RQ1 answer:*
On a recent dataset we consider that #resultunusable of the tools are unusable.
For the tools that we could run, #resultratio of analysis are finishing successfully.
@ -120,7 +120,7 @@ sqlite> SELECT apk1.first_seen_year, (COUNT(*) * 100) / (SELECT 20 * COUNT(*)
```
*/
#highlight()[
#highlight-block()[
*RQ2 answer:* For the #nbtoolsselected tools that can be used partially, a global decrease of the success rate of tools' analysis is observed over time.
Starting at 78% of success rate, after five years, tools have 61% of success; after ten years, 45% of success.
]
@ -216,7 +216,7 @@ We performed similar experiments by variating the min SDK and target SDK version
We found that contrary to the target SDK, the min SDK version has an impact on the finishing rate of Java based tools: 8 tools over 12 are below 50% after SDK 16.
It is not surprising, as the min SDK is highly correlated to the year.
#highlight()[
#highlight-block()[
*RQ2 answer:*
The success rate varies based on the size of bytecode and SDK version.
The date is also correlated with the success rate for Java based tools only.
@ -388,7 +388,7 @@ We observe that the ratio for the finishing rate decreases from 1.04 to 0.73, wh
We conclude from this table that analyzing malware triggers less errors than for goodware.
#highlight()[
#highlight-block()[
*RQ3 answer:*
Analyzing malware applications triggers less errors for static analysis tools than analyzing goodware for comparable bytecode size.
]