Floating-Point TVPI Abstract Domain
Proceedings of the ACM on Programming Languages, ISSN: 2475-1421, Vol: 8, Issue: PLDI, Page: 442-466
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Floating-point arithmetic is natively supported in hardware and the preferred choice when implementing numerical software in scientific or engineering applications. However, such programs are notoriously hard to analyze due to round-off errors and the frequent use of elementary functions such as log, arctan, or sqrt. In this work, we present the Two Variables per Inequality Floating-Point (TVPI-FP) domain, a numerical and constraint-based abstract domain designed for the analysis of floating-point programs. TVPI-FP supports all features of real-world floating-point programs including conditional branches, loops, and elementary functions and it is efficient asymptotically and in practice. Thus it overcomes limitations of prior tools that often are restricted to straight-line programs or require the use of expensive solvers. The key idea is the consistent use of interval arithmetic in inequalities and an associated redesign of all operators. Our extensive experiments show that TVPI-FP is often orders of magnitudes faster than more expressive tools at competitive, or better precision while also providing broader support for realistic programs with loops and conditionals.
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