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Silent Assumption Finder
Developers constantly write code that makes implicit assumptions — that a list will never be empty, that an API will always respond correctly, that a database field will never be null. These assumptions are rarely documented or tested, and they surface later as silent bugs: crashes, incorrect data, or security gaps that traditional linters and type checkers miss entirely, because the code is syntactically correct — it just quietly believes something that was never verified. Silent Assumption Finder is an AI-powered tool, built with IBM Bob 2.0, that scans a codebase and surfaces these hidden assumptions before they become production incidents. Rather than looking for confirmed bugs, it identifies "potential silent assumptions" — flagging exactly what the code assumes, the evidence in the source, the risk if that assumption is violated, a severity rating, and a concrete suggested test to validate it. The tool works in three stages: it reads all source files in a target folder (Python and PHP supported), runs three parallel analyzers focused on different assumption categories (input/data assumptions like null or empty values, boundary/API assumptions like unvalidated external responses, and state/auth assumptions like permissions and concurrency), then merges and deduplicates the findings into a single, severity-ranked report. Results are presented through a clean Streamlit interface so a developer can paste in a folder path and immediately see what needs attention — turning a manual, time-consuming code review task into a few seconds of analysis. Target users are software developers and teams doing code review, onboarding onto unfamiliar codebases, or auditing legacy code before a release. Instead of manually tracing every function to ask "what does this assume?", a developer runs the tool against their repository and gets an immediate, ranked list of risks with concrete next steps. What makes this creative and unique is the framing: most AI code review tools ask "is this code wrong?" This tool asks a different, more foundational question — "what does this code believe to be true, but never verifies?" That distinction surfaces an entire category of real-world bugs (unhandled empty lists, unchecked API responses, assumed non-null values) that pass every existing static check because nothing in the code is technically incorrect until the assumption is violated at runtime. The impact is direct: a developer reviewing a pull request or onboarding onto unfamiliar code can catch entire classes of bugs — the kind that only show up in production under edge-case conditions — before they ship, without having to manually trace every function for unstated assumptions. Each finding also includes a suggested test case, so the tool doesn't just detect risk, it hands the developer a concrete way to turn that assumption into a verified guarantee.
27 Sep 2026
