CallerCalleeProcessor
CallerCalleeProcessor is a class that extends the functionality of
GraphProcessor. The core role of this class is to add edges to a
MultiDiGraph based on the caller-callee relationships between
Symbol nodes. One symbol is considered a caller of another if it
performs a call to the latter.
Overview
The CallerCalleeProcessor class requires a MultiDiGraph and a
document during initialization. It uses these inputs to process and
generate edges based on caller-callee relationships. It catches any
exceptions during parsing or data retrieval, thus ensuring that
processing continues despite minor errors.
Example
Below is a simple example of how to get started with
CallerCalleeProcessor.
import networkx as nx
from automata.symbol.graph.symbol_caller_callees import CallerCalleeProcessor
from automata.symbol.document import Document
# Create a random MultiDiGraph and document
graph = nx.MultiDiGraph()
document = Document()
# Initialize and use the CallerCalleeProcessor
processor = CallerCalleeProcessor(graph, document)
processor.process()
This script will add edges to the input graph according to the caller-callee relationships found in the document’s symbols.
Limitations
The CallerCalleeProcessor has a few limitations to be aware of:
Constructing the
CallerCalleeProcessoris an expensive operation. Hence, its instantiation should be used sparingly.The
processmethod is marked with a TODO to be split into smaller methods. This indicates that theprocessmethod may perform more operations than one might expect from a single function, and could potentially be improved for readability, maintainability and testing.Exceptions are caught and logged, but the exact nature of various errors are not rethrown or handled further. This might lead to circumstances where the execution continues despite critical errors.
Follow-up Questions:
How can we optimize the construction of CallerCalleeProcessor?
What would a suitable strategy be for splitting the
processmethod into smaller functions?How could we handle exceptions in a more granular manner?