484d9e3f8c
Adds cost modeling and budget enforcement for transpilation runs: - PortingCostModel: LOC + ambiguity → compute/review/total cost + tier (step 869) - ReviewEffortEstimator: ambiguity/risk → minutes + complexity label (step 870) - ComputeCostEstimator: prior run history → avg duration/tokens (step 871) - MultiPlanAlternativeGenerator: cheap/balanced/rigorous profiles (step 872) - BudgetPolicyEnforcer: approve/requires_token/rejected decisions (step 873) - CostQualityTradeoffReport: efficiency-based plan recommendation (step 874) - whetstone_plan_transpilation_run MCP tool (step 875) - whetstone_estimate_porting_cost MCP tool (step 876) - CostTelemetryIntegration: cost error tracking + over-budget count (step 877) - Sprint64IntegrationSummary (step 878) All 10 steps passing (94 tests). Policy: over-budget plans require explicit reviewer approval token. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
52 lines
2.2 KiB
C++
52 lines
2.2 KiB
C++
// Step 871: Compute/runtime cost estimator from prior runs (10 tests)
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#include "graduation/ComputeCostEstimator.h"
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#include <iostream>
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static int p=0,f=0;
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#define T(n) { std::cout << " " << #n << "... "; }
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#define P() { std::cout << "PASS\n"; ++p; }
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#define F(m) { std::cout << "FAIL: " << m << "\n"; ++f; }
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#define C(c,m) if(!(c)){F(m);return;}
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void t1(){T(no_history_no_data);
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auto e=ComputeCostEstimator::estimate("py->cpp",{});
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C(!e.hasHistory,"no history");P();}
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void t2(){T(with_history_has_data);
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auto e=ComputeCostEstimator::estimate("py->cpp",{{"py->cpp",100,500}});
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C(e.hasHistory,"history");P();}
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void t3(){T(pair_id_set);
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auto e=ComputeCostEstimator::estimate("rust->go",{});
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C(e.pairId=="rust->go","pairId");P();}
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void t4(){T(sample_count_correct);
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std::vector<PriorRunRecord> h={{"py->cpp",100,500},{"py->cpp",200,600}};
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auto e=ComputeCostEstimator::estimate("py->cpp",h);
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C(e.sampleCount==2,"count");P();}
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void t5(){T(average_duration);
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std::vector<PriorRunRecord> h={{"py->cpp",100,500},{"py->cpp",200,600}};
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auto e=ComputeCostEstimator::estimate("py->cpp",h);
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C(e.estimatedDurationMs==150.0f,"avg");P();}
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void t6(){T(average_tokens);
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std::vector<PriorRunRecord> h={{"py->cpp",100,500},{"py->cpp",200,600}};
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auto e=ComputeCostEstimator::estimate("py->cpp",h);
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C(e.estimatedTokens==550.0f,"tokens");P();}
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void t7(){T(single_run);
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auto e=ComputeCostEstimator::estimate("py->cpp",{{"py->cpp",300,900}});
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C(e.estimatedDurationMs==300.0f,"single");P();}
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void t8(){T(zero_history_zero_estimate);
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auto e=ComputeCostEstimator::estimate("py->cpp",{});
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C(e.estimatedDurationMs==0.0f,"zero");P();}
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void t9(){T(to_json_has_history);
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auto e=ComputeCostEstimator::estimate("py->cpp",{{"py->cpp",100,500}});
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auto j=ComputeCostEstimator::toJson(e);
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C(j.contains("has_history"),"json");P();}
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void t10(){T(to_json_has_sample_count);
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auto e=ComputeCostEstimator::estimate("py->cpp",{{"py->cpp",100,500}});
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auto j=ComputeCostEstimator::toJson(e);
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C(j.contains("sample_count"),"count");P();}
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int main(){
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std::cout<<"Step 871: Compute cost estimator\n";
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t1();t2();t3();t4();t5();t6();t7();t8();t9();t10();
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std::cout<<"\nResults: "<<p<<"/"<<(p+f)<<" passed\n";
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return f?1:0;
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}
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