Tool Changer
Reported by candidates from Salesfoece's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Salesforce's Tool Changer problem hit candidates in March 2024, and it's a simulation problem disguised as a mechanics task. You're managing state transitions, not actually building or fixing anything. The trick is tracking what changes when you swap tools and what stays locked in place. Most candidates overthink the physical analogy and miss that this is really about sequence and order of operations. StealthCoder can feed you the pattern instantly if you blank on state management during the live OA.
Pattern and pitfall
Tool Changer is fundamentally a state machine problem where each tool action produces a predictable output state. The common pitfall is treating tool changes as independent events when they're actually dependent on previous state. You need to model the current tool, available actions, and resulting state after each operation. Many candidates try to optimize prematurely or hunt for a greedy solution when the right approach is careful simulation and tracking. During your OA, if you freeze on the transition logic, StealthCoder gives you the state-by-state breakdown so you can code forward instead of getting stuck on the model.
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You can drill Tool Changer cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. If you're reading this with an OA window open, you're who this was built for.
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Salesfoece reuses patterns across OAs. If you're reading this with an OA window open, you're who this was built for. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Tool Changer FAQ
Is this a greedy problem or simulation?+
Simulation. You can't pick the 'best' tool upfront. You must trace through each operation in order and track what state you're in after each action. Greedy fails because tool availability and state constraints compound.
How much do I need to optimize for this one?+
Get it working first. The state space is small enough that a straightforward simulation will pass. Premature optimization is where candidates waste time. Solve the transitions correctly, then optimize if needed.
What's the most common mistake on Tool Changer?+
Forgetting that tool state persists between operations. Candidates model each operation independently and miss that what tool you're holding affects what you can do next. Track your current tool always.
Can I solve this without simulating every step?+
Maybe, but only after you understand the pattern fully. Start by coding the simulation cleanly. Once you see the transitions repeat or simplify, you can optimize. Don't skip straight to the trick.
How should I test my solution locally before submitting?+
Trace a few manual examples where you switch tools and verify the output state matches your code. Print intermediate states. Edge cases: starting with no tool, switching to the same tool twice, running out of valid actions.