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Runtime PR Review

PR review with runtime proof, not opinions about a diff

BitDive runs your pull request, diffs real execution before and after the change, and returns a merge verdict backed by traces: writes, SQL, downstream calls, and the flows that stayed stable.

0 code changes
one JVM agent
<2% overhead
safe for real envs
5 min
to first review
PR #1530 · inventory-service
SAFE TO MERGE
What changed?TRACE_VERIFIED
Invalid input is now rejected at the service layer
Where did it first diverge?TRACE_VERIFIED
StockService.updateProductQuantityInStock()
Which side effects changed?TRACE_VERIFIED
2 invalid writes removed · downstream leak sealed
What stayed stable?REPLAY_CONFIRMED
Valid adjustments: same writes, same 200, same sync
2 fixes verified · 0 regressions · stable paths intact
The blind spot

Every review signal you have stops at the source code

AI tripled your PR volume, but review capacity did not move. The signals you approve on cannot see below the code line.

What review sees
Diff looks clean
CI is green
AI bot says LGTM
Status code correct
static review stops here
What actually happens at runtime
UPDATE product_stock SET qty = -210invalid write
POST /product-service/sync { qty: -210 }payload leak
INSERT stock_history (audit trail for bad data)hidden write
location-service → 404 cascade on delete pathsilent failure
3× retry storm behind a fallbackretry noise
N+1 query introduced on the happy pathperf drift
None of this appears in a diff. All of it appears in a trace.
How it works

One PR. Two executions. One behavioral diff.

01
Baseline main
Capture full runtime traces on the target branch
02
Run the PR
Same scenarios, same input, on the PR branch
03
Diff behavior
Compare execution trees, writes, payloads
04
Verdict + proof
Safe to merge or fix first, with evidence attached
same request · same input · PR #1530: stock validation fix
main
POST /api/stock/update200 OK
StockController.updateStock()
StockService.updateProductQuantityInStock()
StockRepository.saveAll()
INSERT stock_historySQL
UPDATE product_stock SET qty = -210SQL
POST /product-service/sync { qty: -210 }REST
FIRST
DIVERGENCE
pr-branch
POST /api/stock/update400 Bad Request
StockController.updateStock()
StockService.updateProductQuantityInStock()
throws ValidationExceptionguard
no writes executed
no downstream calls
2 invalid writes removeddownstream leak sealedguard moved to service layer= valid path unchanged
No fabricated confidence

Every claim is graded by how strongly it's proven

AI review prose sounds equally confident about everything. Here, runtime proof and code-level inference are never mixed. "We couldn't verify this" is a valid answer.

runtime proofstatic inference
TRACE_VERIFIED
Before/after traces compared for method-level runtime proof
REPLAY_CONFIRMED
Deterministic replay confirmed stability or intended change
HTTP_VERIFIED
Live request observed, trace depth incomplete
CODE_VERIFIED
Code inspection only; never presented as runtime proof
BLOCKED
Could not verify; the gap is reported, not papered over
A different layer

Diff bots read the patch. This runs it.

Diff-review botreads code
public void updateStock(StockRequest req) {
- repository.saveAll(req.getItems());
+ validator.check(req);
+ repository.saveAll(req.getItems());
}
🤖Nice defensive check. LGTM 👍
Guesses behavior from the patch. Can't see writes, payloads, or what else broke.
VS
BitDive Runtime PR Reviewruns code
UPDATE product_stock qty = -210removed
POST /product-service/syncno longer called
ValidationException at service layernew guard
valid stock adjustmentunchanged
✓ SAFE TO MERGE · trace-verified
Proves behavior with before/after traces. At 50 PRs a week: 50 verdicts, not 50 comment threads.
Validated on real codebases, audited by an independent critic stage
0
trace-verified findings
0
pull requests reviewed
0%
independent-critic agreement
0
real-world codebases

Your next PR might have a hidden data leak

You won't see it in the diff. You won't catch it in tests. BitDive will show you before it reaches production.

AI-generated code you can't fully trustMicroservices with deep side effectsPRs where one wrong write corrupts data