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UID:pretalx-eu-summit-2026-NTCH3P@cfp.riscv-europe.org
DTSTART;TZID=CET:20260610T134000
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DESCRIPTION:We present a coverage-driven framework that optimizes RISC-V sm
 oke regressions by decomposing VCS coverage into feature-specific subsets 
 via tag-based pattern matching\, ranking tests via greedy set cover\, and 
 flagging runtime outliers. Applied to a 978-test production suite drawn fr
 om a larger regression pool of 10\,000 tests\, the framework cut smoke tes
 ts by 40% and peak test runtime by 63%\, while improving coverage on key a
 rchitectural features-including +64% (SMRNMI)\, +53% (timer)\, and +25% (c
 ounters)-with modest regressions on a few features (median <3%)\, all with
 in project thresholds.
DTSTAMP:20260522T162439Z
LOCATION:Poster Island A
SUMMARY:Coverage-Directed Smoke Regression Optimization via Greedy Set Cove
 r for RISC-V Verification - Anish Jaltare\, Abhishek Rajgadia\, Shubham Si
 ngla\, Radha Govindaradjou
URL:https://cfp.riscv-europe.org/eu-summit-2026/talk/NTCH3P/
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