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feat: add all applied controls during mapping #2666

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feat: add all applied controls during mapping #2666

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c2e3d87
feat: Add all applied controls during mapping
monsieurswag Oct 8, 2025
787354f
Fix conflicts
monsieurswag Oct 8, 2025
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9 changes: 7 additions & 2 deletions backend/core/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5161,8 +5161,9 @@ def quality_check(self) -> dict:

def compute_requirement_assessments_results(
self, mapping_set: RequirementMappingSet, source_assessment: Self
) -> list["RequirementAssessment"]:
) -> tuple[list["RequirementAssessment"], dict["RequirementAssessment", list[str]]]:
requirement_assessments: list[RequirementAssessment] = []
assessment_source_dict: dict[RequirementAssessment, list[str]] = {}
result_order = (
RequirementAssessment.Result.NOT_ASSESSED,
RequirementAssessment.Result.NOT_APPLICABLE,
Expand Down Expand Up @@ -5227,6 +5228,10 @@ def assign_attributes(target, attributes):
)
ref = refs[inferences.index(selected_inference)]

assessment_source_dict[requirement_assessment] = [
str(ref.id) for ref in refs
]

assign_attributes(requirement_assessment, selected_inference)
requirement_assessment.mapping_inference = {
"result": requirement_assessment.result,
Expand All @@ -5253,7 +5258,7 @@ def assign_attributes(target, attributes):
],
batch_size=1000,
)
return requirement_assessments
return requirement_assessments, assessment_source_dict

def get_progress(self) -> int:
requirement_assessments = list(
Expand Down
34 changes: 23 additions & 11 deletions backend/core/views.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
import regex
import os
import uuid
import itertools
import zipfile
import tempfile
from datetime import date, datetime, timedelta
Expand Down Expand Up @@ -5943,15 +5944,16 @@ def perform_create(self, serializer):
)

# Compute results and get all affected requirement assessments
computed_assessments = instance.compute_requirement_assessments_results(
mapping_set, baseline
computed_assessments, assessment_source_dict = (
instance.compute_requirement_assessments_results(
mapping_set, baseline
)
)

# Collect all source requirement assessment IDs
source_assessment_ids = [
assessment.mapping_inference["source_requirement_assessment"]["id"]
for assessment in computed_assessments
]
source_assessment_ids = itertools.chain.from_iterable(
assessment_source_dict.values()
)

# Fetch all baseline requirement assessments in one query
baseline_assessments = {
Expand All @@ -5966,21 +5968,31 @@ def perform_create(self, serializer):
m2m_operations = []

for requirement_assessment in computed_assessments:
source_id = requirement_assessment.mapping_inference[
selected_source_id = requirement_assessment.mapping_inference[
"source_requirement_assessment"
]["id"]
baseline_ra = baseline_assessments[source_id]
selected_baseline_ra = baseline_assessments[selected_source_id]

# Update observation
requirement_assessment.observation = baseline_ra.observation
requirement_assessment.observation = (
selected_baseline_ra.observation
)
updates.append(requirement_assessment)

source_ids = assessment_source_dict[requirement_assessment]
baseline_requirement_assessments = [
baseline_assessments[source_id] for source_id in source_ids
]

# Store M2M operations for later
m2m_operations.append(
(
requirement_assessment,
baseline_ra.evidences.all(),
baseline_ra.applied_controls.all(),
selected_baseline_ra.evidences.all(),
itertools.chain.from_iterable(
requirement_assessment.applied_controls.all()
for requirement_assessment in baseline_requirement_assessments
),
)
)
Comment on lines 5989 to 5997
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⚠️ Potential issue | 🔴 Critical

Fix generator capturing the wrong applied controls

itertools.chain.from_iterable(...) captures baseline_requirement_assessments by reference. Because you append that generator to m2m_operations and only iterate it after the outer loop finishes, every stored generator runs with baseline_requirement_assessments set to whatever the last iteration assigned. Earlier requirement assessments therefore end up copying the applied controls of the final baseline mapping, which is a regression. Materialize the union while you’re still inside the loop (e.g. build a list or set of control IDs) and store that concrete collection instead of the lazy generator.

Suggested fix:

-                    m2m_operations.append(
-                        (
-                            requirement_assessment,
-                            selected_baseline_ra.evidences.all(),
-                            itertools.chain.from_iterable(
-                                requirement_assessment.applied_controls.all()
-                                for requirement_assessment in baseline_requirement_assessments
-                            ),
-                        )
-                    )
+                    baseline_control_ids = {
+                        ac.id
+                        for baseline_ra in baseline_requirement_assessments
+                        for ac in baseline_ra.applied_controls.all()
+                    }
+                    m2m_operations.append(
+                        (
+                            requirement_assessment,
+                            selected_baseline_ra.evidences.all(),
+                            baseline_control_ids,
+                        )
+                    )
@@
-                for assessment, evidences, controls in m2m_operations:
-                    assessment.evidences.add(*[ev.id for ev in evidences])
-                    assessment.applied_controls.add(*[ac.id for ac in controls])
+                for assessment, evidences, control_ids in m2m_operations:
+                    assessment.evidences.add(*[ev.id for ev in evidences])
+                    if control_ids:
+                        assessment.applied_controls.add(*control_ids)
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
(
requirement_assessment,
baseline_ra.evidences.all(),
baseline_ra.applied_controls.all(),
selected_baseline_ra.evidences.all(),
itertools.chain.from_iterable(
requirement_assessment.applied_controls.all()
for requirement_assessment in baseline_requirement_assessments
),
)
)
baseline_control_ids = {
ac.id
for baseline_ra in baseline_requirement_assessments
for ac in baseline_ra.applied_controls.all()
}
m2m_operations.append(
(
requirement_assessment,
selected_baseline_ra.evidences.all(),
baseline_control_ids,
)
)
🤖 Prompt for AI Agents 
In backend/core/views.py around lines 5989 to 5997 the code appends an
itertools.chain.from_iterable(...) generator that closes over
baseline_requirement_assessments, causing all stored generators to reflect the
final loop value; instead, inside the loop materialize the applied-controls
collection (e.g., build a list or set of control IDs or control instances from
requirement_assessment.applied_controls.all() or from the baseline mapping) and
append that concrete collection to m2m_operations so later iteration uses the
correct, per-iteration controls rather than a late-bound generator.


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