Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Detection Software Content Failures Using Dynamic Execution Information   Modern software systems become too complex to be tested and validated.
Detecting software partial failures in complex systems at runtime assist to
handle software unintended behaviors, avoiding catastrophic software failures
and improving software runtime availability. These detection techniques aim to
find the manifestation of faults before they finally lead to unavoidable
failures, thus supporting following runtime fault tolerant techniques. We
review the state of the art articles and find that the content failures account
for the majority of all kinds of software failures, but its detection methods
are rarely studied. In this work, we propose a novel failure detection
indicator based on the software runtime dynamic execution information for
software content failures. The runtime information is recorded during software
execution, then transformed to a measure named runtime entropy and finally fed
into machine learning models. The machine learning models are built to classify
the intended and unintended behaviors of the objected software systems. A
series of controlled experiments on several open source projects are conducted
to prove the feasibility of the method. We also evaluate the accuracy of
machine learning models built in this work.

32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an