Unroll hot-path loops in U256 (mulWide, sqrWide, addTo, subTo) to
eliminate loop control overhead and array bounds checks that ART JIT
on Android does not optimize as aggressively as HotSpot. These functions
are called ~1,900× per signature verification.
Optimize unsignedMultiplyHighFallback to compute the unsigned 128-bit
product directly from 32-bit sub-products, avoiding the signed
multiplyHigh + correction path. Saves ~8 instructions per call on
Android < API 31 (~30,000 calls per verify).
Unroll FieldP.reduceWide carry propagation and inline the reduceSelf
subtraction (avoiding P array access and U256.subTo call). Unroll
FieldP.half with P[1..3]=-1 inlined as mask.
Replace copyFrom pattern in mul, mulG, and mulDoubleG with ping-pong
point buffers — alternate between two MutablePoints via reference swap
instead of copying 12 Longs after every addition. Eliminates ~170
copyFrom calls per verify and avoids the internal copy buffer in
doublePoint's out===inp path (~130 per verify). Also removes the
MutablePoint() allocation in mulG (3 LongArrays per sign/pubCreate).
https://claude.ai/code/session_017UbWduFi1sLUsgVUMUH2nx
All three annotated methods (toggleAudioMute, toggleVideo, cleanup)
are only ever called from the main thread, so the blocking lock was
never contended. Remove it to avoid misleading future readers and to
prevent accidental main-thread blocking if a call site changes.
The Mutex in CallManager is kept because it uses suspending withLock
which never blocks the thread, and it correctly serializes the
GlobalScope.launch(Dispatchers.Default) hangup/reject paths in
CallActivity against the viewModelScope state-collector path.
https://claude.ai/code/session_01TTPrYjcz1eYEzdSV5N6rHi
- Clear discoveredCalleePeers on transitionToEnded to prevent stale
peers from triggering mesh setup in subsequent calls
- Cap processedEventIds and completedCallIds with LRU eviction to
prevent unbounded memory growth over long app sessions
- Store and release SurfaceTextureHelper in startCamera/stopCamera
to prevent GL thread and texture leaks
- Wrap stopCamera's stopCapture in try-catch for InterruptedException
to ensure camera resources are always released
- Add Mutex to CallManager to serialize state mutations, preventing
races when signaling events arrive concurrently from multiple relays
- Add @Synchronized to CallController's toggleAudioMute, toggleVideo,
and cleanup to prevent races with WebRTC callbacks
https://claude.ai/code/session_01TTPrYjcz1eYEzdSV5N6rHi
- H11: Cache skipped message keys in SecretTree for out-of-order decryption
- L1: Prune sentKeys map when exceeding 10000 entries
- L2: Prune consumed generations below current minimum
- H17: Call markAsRead when chat view is opened
- Key zeroing: Zero old private keys in KeyPackageRotationManager
https://claude.ai/code/session_018gVkmmYgMFtBH7G31pCk9N
ThreadLocal.withInitial is a JVM-only API that doesn't compile on
Kotlin/Native or iOS targets. Replace all usages in commonMain
(FieldP.kt, Point.kt) with a new ScratchLocal expect/actual:
- jvmMain/androidMain: delegates to java.lang.ThreadLocal (same behavior)
- nativeMain: holds value directly (Kotlin/Native coroutines are
cooperative, scratch buffers don't need thread isolation)
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
When the app restarts and reconnects to relays, old call offer events
from completed calls could be replayed, causing the phone to ring for
calls that already ended. This was especially noticeable when the user
killed and restarted the app shortly after a call.
Three protections added to CallManager:
1. Track completed call IDs: hangup/reject events mark their call-id as
completed. Subsequent offer events for the same call-id are ignored.
2. Init timestamp guard: events created before the CallManager was
initialized (minus a grace period) are rejected, preventing stale
events from a previous app session from triggering ringing.
3. Completed call IDs survive reset(): the set is intentionally not
cleared when the call state machine resets to Idle, ensuring that
stale offers remain blocked for the lifetime of the CallManager.
https://claude.ai/code/session_0145VKiG8yZMqcMsaBEjNPxv
Three Android-specific optimizations:
1. Use Math.unsignedMultiplyHigh on API 35+ (Android 15): single UMULH
instruction, eliminates the 4-insn signed→unsigned correction that
the fallback path requires. Same optimization as our JVM 18+ path.
2. Use Math.multiplyHigh + correction on API 31-34 (Android 12-14):
avoids the pure-Kotlin 4×32-bit sub-product fallback entirely.
3. Resolve API level check ONCE at class load via static final fields
(HAS_MULTIPLY_HIGH, HAS_UNSIGNED_MULTIPLY_HIGH) instead of checking
Build.VERSION.SDK_INT on every call. These functions are called 16×
per field multiply (~12,000× per signature verify), so eliminating
the per-call branch matters.
Performance tiers on Android:
API 35+ (Android 15): ~same as JVM 18+ (UMULH intrinsic)
API 31-34 (Android 12-14): SMULH + 3 correction insns per product
API 26-30 (Android 8-11): pure-Kotlin fallback (4 sub-products)
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
Add precise per-operation cost analysis from comparing our Kotlin
implementation with bitcoin-core/secp256k1's C source:
- doublePoint: 1,516 insns (Kotlin) vs 530 insns (C) = 2.9×
- mul/sqr accounts for 76% of gap (UMULH+MUL+carry vs single MUL)
- add/neg/half accounts for 24% (reduceSelf vs lazy magnitude tracking)
- Update performance numbers to Java 21 results (verify 3.4×, sign 1.1×)
- Document all optimizations implemented during this session
- Note that lazy reduction penalty (4.2× on cheap ops) is the main
remaining algorithmic opportunity, but requires 5×52-bit limb change
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
- Add `inline` to hot-path tiny functions: U256.isZero, U256.testBit,
FieldP.reduceSelf, FieldP.neg, MutablePoint.isInfinity. These are
called thousands of times per EC operation; inline eliminates virtual
call overhead (mostly helps Kotlin/Native; JVM JIT already inlines).
- Fix stale comment: G_TABLE_SIZE is 1024 for w=12 (was "64 for w=8")
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
Move transitionToEnded() before the signing + relay publish in hangup()
so the UI stops ringing/ringback immediately, matching the pattern
already used by rejectCall(). Add onDestroy safety net in CallActivity
to hang up if the Activity is destroyed while a call is active. Wrap
audio stop methods in try-catch to prevent one failure from blocking
the others.
https://claude.ai/code/session_01Rip2HPCbF48PPFDiB2X5ik
inv() and sqrt() each allocated 11 LongArray(4) (plus 2 for sqrt
verification) on every call. These are now served from a thread-local
Array(11) { LongArray(4) } cache, eliminating 22-24 allocations per
ECDH operation (inv called in toAffine, sqrt called in liftX).
Also reuses chain scratch slots for sqrt's verification step instead
of allocating separate check/ar arrays.
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
Eliminates ~80 LongArray allocations per mul/mulDoubleG call by
pre-allocating the P-side Jacobian and affine tables, the doubling
temp, and the batch inversion scratch buffers in PointScratch
(thread-local, allocated once per thread, reused across calls).
Before: mul() allocated 8 MutablePoint (24 LongArray) + 8 MutablePoint
(24 LongArray) + 16 AffinePoint (32 LongArray) + batch temps = ~92
LongArray per call. After: 0 allocations in the table construction path.
Also fixes minor allocation in addMixed degenerate case (use t[5]
scratch instead of new LongArray(4)).
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
The JVM target is Java 21, so Math.unsignedMultiplyHigh (Java 18+) can
be called directly without MethodHandle reflection. The previous approach
used MethodHandle.invokeExact which Kotlin compiles with Object return
type, causing Long boxing on every call (3 box/unbox per invocation ×
16 calls per field multiply = 48 boxed objects per mul).
Direct call compiles to a single UMULH instruction with zero overhead.
This is the most performance-critical function: called ~12,000× per
signature verification.
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
Two microoptimizations:
1. reduceSelf: exploit P's structure (P[1..3] = 0xFFFFFFFFFFFFFFFF).
a >= P only if all top 3 limbs are max AND a[0] >= P[0]. The first
check (a[3] == -1) fails >99.99% of the time, making this a single
branch miss prediction instead of a 4-limb comparison loop.
Called ~1,300× per verify, ~500× per ECDH.
2. Pre-allocate wNAF IntArrays and scratch MutablePoint/LongArray in
PointScratch. Eliminates 8-12 IntArray(145) + 8-12 LongArray(4)
allocations per mul/mulDoubleG call. Adds wnafInto() to Glv that
writes into caller-provided arrays.
https://claude.ai/code/session_01BhU63WUe9AhikZxRdw3Lpg
After swapping with an adjacent item, the dragOffset adjustment can
flip its sign (e.g. negative becomes positive), which immediately
triggers the second if-block to swap back in the opposite direction
within the same onDrag call. This causes the dragged item to jump
and the user to end up dragging a different item. Fix by returning
after each successful swap so only one swap occurs per drag event.
https://claude.ai/code/session_01RVM5kEJGrCaJTaP3GmVHDd
Vitor Pamplona