🎯 Objective
Modify the core execution loop in signal_processor.py to aggregate Function-level risks into their parent Classes before normalizing them into File-level scores.
🛠️ Implementation
prism.py already successfully links functions to classes (func["parent_class_name"] = cls["name"]).- Update the
_calc_* methods (e.g., _calc_algorithmic_dos, _calc_cognitive_load) to iterate through classes first.
- Sum the function impacts within the class boundary, generate a Class-level risk score, and then pass those Class aggregates up to the File-level Sigmoid normalizer.
🎯 Objective
Modify the core execution loop in
signal_processor.pyto aggregate Function-level risks into their parent Classes before normalizing them into File-level scores.🛠️ Implementation
prism.pyalready successfully links functions to classes (func["parent_class_name"] = cls["name"])._calc_*methods (e.g.,_calc_algorithmic_dos,_calc_cognitive_load) to iterate throughclassesfirst.