tensorflow / quantum
Features of Interest
Aspects in the source code identified through RegEx patterns.
Intro
Features of interest are any aspects of a software system that can be identified through patterns in code.
Features of interest provide you with a way to focus your attention on relevant parts of the codebase.
Typical examples include, security, TODOs, logging.
A feature of interest may be present in multiple files. Any source code file may be in zero or multiple features of interest.
Overview
GENERAL
TODOs
4,648 LOC (41%)
22 files
|
found text
|
found text per file
1 GENERAL Concerns
The "general" group contains
2
concerns.
TODOs
Unclassified
general
1.1 TODOs
4,648 LOC (41%)
22 files
|
found text
|
found text per file
The following criteria are used to filter files:
files with any line of content like "
.*(TODO|FIXME)( |:| ).*
".
22
files match defined criteria (
4,648
lines of code,
41.1%
vs. main code):
15
*.cc files (
3,516
lines of code)
7
*.py files (
1,132
lines of code)
29
lines match the content pattern.
details...
per component - primary logical decomposition
tensorflow_quantum/core/ops
in 17 files, 3,848 LOC (73%)
tensorflow_quantum/python/layers
in 1 file 11 LOC (1%)
tensorflow_quantum/python
in 1 file 438 LOC (91%)
tensorflow_quantum/python/differentiators
in 1 file 166 LOC (41%)
benchmarks/scripts
in 2 files, 185 LOC (47%)