# Previously Developed Software > Use when you must scope the reuse credit of previously developed software in a DO-178C project: classify a reused item from its origin standard, its modification state and whether its assurance level meets the target level into unchanged direct credit, modified PDS with delta qualification over the changed scope plus affected interfaces, or level upgrade needing additional verification at the higher level, compute the delta objective coverage ratio and verdict against the required objective set, and bound the regression of modified items from the changed code fraction and touched interfaces. Produces the reuse classification, the credit path, the delta objective gap and verdict, and the bounded regression scope that frame the reuse argument. Trigger: previously developed software, PDS reuse, reuse credit, delta objective coverage, modified software scope, regression scope, direct credit, level upgrade. - Skill: `ashfordeou/previously-developed-software` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add ashfordeou/previously-developed-software` - Raw SKILL.md: https://api.skillmd.com/api/skills/ashfordeou/previously-developed-software/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - License: Apache-2.0 - Author: ashfordeOU (https://skillmd.com/u/ashfordeou) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/ashfordeou/previously-developed-software --- # Previously Developed Software Reuse Scoping (avionics/do178c/previously-developed-software) Use when the task is scoping the reuse credit of previously developed software (PDS) in a DO-178C project: rating a reused item from its origin standard, its modification state and whether its assurance level meets the target level, then turning those declared facts into the delta objective assessment and the regression scope that justify taking credit. This leaf implements the reuse classification model, the delta objective coverage verdict and the modified software scope rules in pure Python, stdlib only, deterministic and offline. It pairs with avionics/do178c/verification and avionics/do178c/software-testing for the delta verification this leaf scopes, and with avionics/do178c/configuration-management and avionics/do178c/planning for the adjacent project-data and project-strategy siblings. ## Domain quick reference - Reuse classes (user-declared facts in, classes out): when the item's assurance level does not meet the target level, the class is level-upgrade, meaning additional verification at the higher level is required and the level gap is treated as the delta scope. When the level is met and the item is unmodified, the class is unchanged-direct-credit: existing data is accepted and no delta objectives apply. When the level is met and the item is modified, the class is modified-pds: delta qualification applies over the changed scope plus the affected interfaces. - Coverage: coverage_ratio = covered / required, rounded to 4 decimals; delta_objectives = required - covered. The verdict flips at equality: any covered below required gives delta-qualification-required, and covered equal to required gives full-coverage. No objective count table is reproduced: both counts are caller inputs. - Modified scope: changed_fraction = changed_loc / total_loc (rounded to 4 decimals) and interface_fraction = touched_interfaces / total_interfaces. The scope is bounded-regression when changed_fraction is at or under 0.2 and interface_fraction is at or under 0.5, and broad-regression otherwise. - DO-178C frames the reuse credit question for previously developed software; the relations above are the standard engineering method, summary-only. ## Workflow 1. Collect the declared facts for the reused item: origin standard id (for example do-178c), modified flag, level-meets flag, changed and total lines of code, touched and total interfaces, and the required and covered objective counts for the delta case. 2. Rate the item with classify_pds(origin_standard, modified, level_meets) and read reuse_class and credit_path. 3. When the class is modified-pds or level-upgrade, assess the gap with delta_objective_coverage(required_objectives, covered_objectives) and read coverage_ratio, delta_objectives and verdict. 4. When the item is modified, scope the regression with modified_scope(changed_loc, total_loc, touched_interfaces, total_interfaces) and read changed_fraction, interface_fraction and scope. 5. For a single record of the item, call pds_report with all nine inputs; it merges the classification, coverage and scope sections. 6. Hand the delta verdict and the scope to the verification and software-testing effort that performs the scoped delta verification. 7. Confirm the deterministic checks with the contract test. ## Worked example Reference item: a previously certified autopilot module (DO-178C, DAL C data) reused in a DAL C project, 8000 LOC and 12 interfaces. Three cases: - Unmodified reuse at the same level: classify_pds('do-178c', False, True) returns reuse_class unchanged-direct-credit and the credit path "accepted as-is at the target assurance level from existing data; no delta objectives required". - Modified reuse at the same level (500 of 8000 LOC changed, 2 of 12 interfaces touched): classify_pds('do-178c', True, True) returns reuse_class modified-pds with the credit path "delta qualification over the changed scope plus affected interfaces". delta_objective_coverage(24, 19) returns coverage_ratio 0.7917, delta_objectives 5 and verdict delta-qualification-required. modified_scope(500, 8000, 2, 12) returns changed_fraction 0.0625, interface_fraction 0.1667 and scope bounded-regression. - Level-upgraded reuse (DAL C data reused at DAL B): classify_pds('do-178c', False, False) returns reuse_class level-upgrade with the credit path "additional verification at the higher assurance level required, treating the level gap as the delta scope". - Combined record for the modified case: pds_report('do-178c', True, True, 24, 19, 500, 8000, 2, 12) returns one dict holding reuse_class modified-pds, the modified credit path, required 24, covered 19, coverage_ratio 0.7917, delta_objectives 5, verdict delta-qualification-required, changed_fraction 0.0625, interface_fraction 0.1667 and scope bounded-regression. ## Verification - Confirm classify_pds('do-178c', False, True) gives unchanged direct credit, ('do-178c', True, True) gives modified-pds and ('do-178c', False, False) gives level-upgrade. - Confirm delta_objective_coverage(24, 19) gives ratio 0.7917 with a delta of 5 and the delta-qualification-required verdict, and that the verdict flips to full-coverage when covered reaches required. - Confirm modified_scope(500, 8000, 2, 12) gives changed_fraction 0.0625 and bounded-regression, while a 30% change with the same interfaces gives broad-regression. - Confirm every non-string or empty origin standard, required counts at or below zero, covered counts outside [0, required], changed lines outside [0, total] and touched interfaces outside [0, total] raise ValueError. - Run the contract test offline: python3 scripts/test_previously_developed_software.py (30 tests, deterministic). ## Related leaves - avionics/do178c/configuration-management: the current-data sibling; boundary between managing the accepted item's current data and rating its reuse credit. - avionics/do178c/planning: the project-strategy sibling that records the reuse approach decided here. - avionics/do178c/verification and avionics/do178c/software-testing: the delta verification this leaf scopes. ## Pitfalls - Confusing level-upgrade with modified-pds: a level gap on an unmodified item (classify_pds('do-178c', False, False)) is level-upgrade - additional verification at the higher assurance level with the gap as the delta scope - not modified-pds, which applies only when the level is met and the item is modified. - Missing the verdict flip at equality: coverage flips to full-coverage only when covered equals required; any covered below required, however close (19 of 24 is 0.7917), is delta-qualification-required with delta_objectives 5. - Inventing the objective counts: no objective count table is reproduced in this leaf - required and covered are caller inputs from the project planning data, so pull them from the plan, never from a guess at the DO-178C tables. - Reading bounded-regression from one threshold alone: the scope is bounded-regression only when changed_fraction is at or under 0.2 AND interface_fraction is at or under 0.5; a 30 percent change with untouched interfaces is still broad-regression. - Taking direct credit on a modified item or across a level gap: unchanged-direct-credit applies only to unmodified reuse at a met level; modified reuse always carries delta qualification over the changed scope plus the affected interfaces. - Scoping the delta to changed lines only: the modified case rates the changed LOC fraction and the touched interface fraction together, and pds_report merges classification, coverage, and scope into one record for the verification effort - hand over the report, not just the changed-lines count. ## Behavior contract (gate 3) Run the deterministic contract test (stdlib unittest, offline): python3 scripts/test_previously_developed_software.py The test covers the three reuse classes and their credit paths (including the level-upgrade-not-modified-pds distinction), the delta objective coverage ratio and verdict flip at full coverage, ratio preservation under input doubling, the modified scope fractions and both regression threshold boundaries, the combined pds_report record, run-to-run determinism, and ValueError rejection of empty or non-string origin standards, non-positive required counts, out-of-range covered counts, negative or oversized changed lines and out-of-range touched interfaces. ## Compliance - Standards referenced, not reproduced: DO-178C (RTCA/SAE) frames the reuse credit question; the classification and scoping rules above are standard engineering method, summary-only per standards-map.yaml, and no objective count tables are reproduced. - compliance: STANDARDS-REF, gated: false.