Hi everyone,
I’ve been building a DeFi arbitrage engine on Arbitrum One called TitanArb, and I’d really like to get feedback from people who understand the Arbitrum ecosystem, DEX infrastructure, MEV, and execution systems.
TitanArb is written primarily in Go and is designed around real-time market state, cross-DEX opportunity discovery, bounded multi-hop routing, executable quotes, trade-size optimization, simulation, and atomic execution using Aave V3 Flash Loans.
The current system works with Uniswap V3 and Camelot V3 / Algebra, evaluates 2/3/4-hop routes, and includes:
real-time WSS market updates
dirty-pool based state refresh
pair intelligence and dynamic market selection
route scoring and route memory
cross-venue opportunity detection
bounded quote and optimizer budgets
gas, DEX fees, price impact, slippage, and flash-loan premium in profitability calculations
multi-provider RPC routing and latency-aware failover
pre-execution simulation
live atomic execution with on-chain safety checks
One of the most interesting challenges has been avoiding both extremes: evaluating everything and overwhelming the RPC/runtime, or filtering so aggressively that potentially useful opportunities never reach the economics stage.
I’m currently spending a lot of time on opportunity discovery quality, particularly understanding exactly where routes are rejected throughout the pipeline and whether the system is being too conservative before an opportunity reaches executable pricing.
The repository is public:
I’d especially appreciate feedback on:
route discovery and candidate selection
market/pair universe design
cross-DEX arbitrage on Arbitrum
RPC/state freshness architecture
MEV and execution assumptions
areas where the system may be filtering opportunities too early
additional DEXs or market structures worth supporting
Critical feedback is very welcome. I’m much more interested in finding weaknesses in the architecture than simply promoting the project.