0282e7ebb7
Implements priority-aware pair-upgrade queue with starvation prevention: - PairUpgradeQueue: enqueue/dequeue/getActive sorted by priority (step 879) - UpgradePriorityPolicy: critical/revenue/coverage/experimental classes (step 880) - ParallelDispatchOptimizer: schedule N pairs with blocked-pair constraints (step 881) - StarvationPrevention: detect and promote starved pairs (step 882) - QueueHealthScorer: stall-rate-based health scoring (step 883) - RetryBackoffStrategy: exponential backoff with max-attempts guard (step 884) - whetstone_enqueue_pair_upgrade MCP tool (step 885) - whetstone_get_upgrade_queue MCP tool with priority sorting (step 886) - UpgradeQueueObservabilityPanel: snapshot model for queue visibility (step 887) - Sprint65IntegrationSummary (step 888) All 10 steps passing (94 tests). Routing rule: critical-tier regressions preempt all experimental upgrades. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
51 lines
2.2 KiB
C++
51 lines
2.2 KiB
C++
// Step 881: Parallel dispatch optimizer (10 tests)
|
|
#include "graduation/ParallelDispatchOptimizer.h"
|
|
#include <iostream>
|
|
static int p=0,f=0;
|
|
#define T(n) { std::cout << " " << #n << "... "; }
|
|
#define P() { std::cout << "PASS\n"; ++p; }
|
|
#define F(m) { std::cout << "FAIL: " << m << "\n"; ++f; }
|
|
#define C(c,m) if(!(c)){F(m);return;}
|
|
|
|
void t1(){T(schedules_up_to_max);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b","c"},2);
|
|
C(plan.scheduledCount==2,"count");P();}
|
|
void t2(){T(max_parallelism_stored);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b"},3);
|
|
C(plan.maxParallelism==3,"max");P();}
|
|
void t3(){T(slot_count_equals_pairs);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b","c"},3);
|
|
C(plan.slots.size()==3,"slots");P();}
|
|
void t4(){T(blocked_pairs_not_scheduled);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b","c"},3,{"b"});
|
|
bool b_scheduled=false;
|
|
for(auto& s:plan.slots) if(s.pairId=="b"&&s.scheduled) b_scheduled=true;
|
|
C(!b_scheduled,"not sched");P();}
|
|
void t5(){T(slot_ids_sequential);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b"},2);
|
|
C(plan.slots[0].slotId=="slot-1"&&plan.slots[1].slotId=="slot-2","ids");P();}
|
|
void t6(){T(empty_pairs_zero_scheduled);
|
|
auto plan=ParallelDispatchOptimizer::optimize({},2);
|
|
C(plan.scheduledCount==0,"zero");P();}
|
|
void t7(){T(more_pairs_than_max);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b","c","d"},2);
|
|
C(plan.scheduledCount==2,"capped");P();}
|
|
void t8(){T(all_pairs_if_within_max);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b"},5);
|
|
C(plan.scheduledCount==2,"all");P();}
|
|
void t9(){T(to_json_has_scheduled_count);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a","b"},2);
|
|
auto j=ParallelDispatchOptimizer::toJson(plan);
|
|
C(j.contains("scheduled_count"),"json");P();}
|
|
void t10(){T(to_json_slots_array);
|
|
auto plan=ParallelDispatchOptimizer::optimize({"a"},1);
|
|
auto j=ParallelDispatchOptimizer::toJson(plan);
|
|
C(j["slots"].is_array(),"slots");P();}
|
|
|
|
int main(){
|
|
std::cout<<"Step 881: Parallel dispatch optimizer\n";
|
|
t1();t2();t3();t4();t5();t6();t7();t8();t9();t10();
|
|
std::cout<<"\nResults: "<<p<<"/"<<(p+f)<<" passed\n";
|
|
return f?1:0;
|
|
}
|