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        <title>Yi-Nung Tsao's Research Blog</title>
        <link>https://ytsao.github.io/blog/</link>
        <description>PhD research blog covering topics in program analysis and verification</description>
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        <lastBuildDate>Wed, 12 Feb 2025 00:00:00 GMT</lastBuildDate>
        
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            <title>SMT Solvers and Theory Extensions</title>
            <link>https://ytsao.github.io/blog/constraint-solving-smt.html</link>
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            <pubDate>Wed, 12 Feb 2025 00:00:00 GMT</pubDate>
            <category>Constraint Solving</category>
            <description>Discover how SMT solvers extend SAT with reasoning about theories like linear arithmetic.</description>
            <content:encoded><![CDATA[SMT (Satisfiability Modulo Theories) solvers extend SAT solving to handle mathematical domains like integers, reals, arrays, and bitvectors. This post covers the common theories, solver architecture, and practical applications.]]></content:encoded>
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            <title>SAT Solvers and Boolean Satisfiability</title>
            <link>https://ytsao.github.io/blog/constraint-solving-sat.html</link>
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            <pubDate>Wed, 05 Feb 2025 00:00:00 GMT</pubDate>
            <category>Constraint Solving</category>
            <description>Learn about SAT solving algorithms and their applications in software verification.</description>
            <content:encoded><![CDATA[The Boolean Satisfiability Problem (SAT) is NP-complete but practically solvable. This post covers SAT algorithms, practical solvers like MiniSat and Glucose, and real-world applications.]]></content:encoded>
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            <title>Introduction to Neural Network Verification</title>
            <link>https://ytsao.github.io/blog/neural-network-verification.html</link>
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            <pubDate>Sun, 15 Jan 2025 00:00:00 GMT</pubDate>
            <category>Neural Networks</category>
            <description>A comprehensive introduction to the fundamentals of neural network verification.</description>
            <content:encoded><![CDATA[Neural network verification aims to ensure the robustness and correctness of neural network models. This is an introduction to the field and its key challenges.]]></content:encoded>
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            <title>Lattices and Domains</title>
            <link>https://ytsao.github.io/blog/abstract-interpretation-lattices.html</link>
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            <pubDate>Fri, 25 Jan 2025 00:00:00 GMT</pubDate>
            <category>Abstract Interpretation</category>
            <description>Understanding lattice structures and how they form the mathematical foundation of abstract interpretation.</description>
            <content:encoded><![CDATA[Lattices provide the mathematical structure for abstract domains in program analysis. This post covers lattice theory and its application to abstract interpretation.]]></content:encoded>
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            <title>Introduction to Abstract Interpretation</title>
            <link>https://ytsao.github.io/blog/abstract-interpretation-intro.html</link>
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            <pubDate>Sun, 20 Jan 2025 00:00:00 GMT</pubDate>
            <category>Abstract Interpretation</category>
            <description>Learn the foundational concepts of abstract interpretation and why it's crucial for program analysis.</description>
            <content:encoded><![CDATA[Abstract interpretation is a theory of sound approximation of program behaviors. This post introduces key concepts and provides examples of abstract domains.]]></content:encoded>
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