Finding Bugs using Path-Sensitive Static Analysis Gábor Horváth Gabor.Horvath@microsoft.com @XazaxHunWelcome to CppCon 2021! Join #visual_studio channel on CppCon Discord https://aka.ms/cppcon/discord latest announcements Take our survey https://aka.ms/cppconAgenda • Intro to path-sensitive static analysis • Path-sensitive checks in MSVC • A look under the hood • Upcoming features • Lessons learned2012 -> Unknown p -> Null p -> MaybeNull p -> MaybeNull Warning Unknown Null NotNull MaybeNull Analysis state Transition semi-lattice• Some paths are infeasible: • Not taking branch 1, but taking branch

第三届中国Rust开发者大会 Rustle: the first static analyzer for smart contracts in Rust Matthew Jiang Director of Security Team @ BlockSec Motivation Background Design 1 2 3 Capability Usability Conclusion Front-end Clang Rustc Gollvm LLVM IR Back-end x86 ARM BPF WASM LLVM Pass: rich APIs to analysis the LLVM IR Background Near Blockchains with smart contracts in Rust Rust Web Assembly Workflow Design Compile Smart Contracts LLVM IR LLVM Pass Extracted Patterns Pattern Match Analysis Results Design #[private] pub fn callback_withdraw(&mut self, amount: U128) { match env::promise_result(0)

https://www.meetup.com/St-Petersburg-CPP-User- Group/ ● C++ Russia: https://cppconf.ru/en/Why Code Analysis?Software QualityReadability Maintainability tools fuzzer battery life Repeatable tests Undefined Behavior – Fun with NULL pointers, part 1: https://lwn.net/Articles/342330/Why code analysis – ● Improve software quality ● Lower developer frustration ● Avoid UBLanguageLanguage helps Built-in compiler check ○ Current LLVM implementation gives 5% overhead ○ Annotations to help analysis: gsl::SharedOwner, gsl::Owner, gsl::Pointer void sample1() { int* p = nullptr; {

1 Competitor Analysis: KubeSphere vs. Rancher and OpenShift September 2021 2 Table of Contents Competitor Analysis: KubeSphere vs. Rancher and OpenShift........................................1 integration of SonarQube for static code analysis supported and analysis results available on the UI Manual configurations required to set up SonarQube for static code analysis Manual configurations configurations required to set up SonarQube for static code analysis Application Application deployment App Store available to support Helm Chart and application repository configurations Operator Hub

Lecture Notes on Gaussian Discriminant Analysis, Naive Bayes and EM Algorithm Feng Li fli@sdu.edu.cn Shandong University, China 1 Bayes’ Theorem and Inference Bayes’ theorem is stated mathematically through parameters θ = {P(X = x | Y = y), P(Y = y)}x,y. 2 Gaussian Discriminant Analysis In Gaussian Discriminate Analysis (GDA) model, we have the following as- sumptions: • A1: Y ∼ Bernoulli(ψ): Y follows ˜y | X = ˜x) = pY |X(˜y | ˜x) = p(˜x | ˜y)p(˜y) p(˜x) where ˜y = 0, 1. 3 Gaussian Discriminant Analysis and Logistic Regression By far, we introduce two classification algorithms, Logistic Regression

pandas: powerful Python data analysis toolkit Release 0.19.0 Wes McKinney & PyData Development Team Oct 02, 2016 CONTENTS 1 What’s New 3 1.1 v0.19.0 (October 2, 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 7.4 Practical data analysis with Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 7.5 Modern . . . . . . . . . . . . . . 1888 Python Module Index 1891 xliv pandas: powerful Python data analysis toolkit, Release 0.19.0 PDF Version Zipped HTML Date: Oct 02, 2016 Version: 0.19.0 Binary Installers:

pandas: powerful Python data analysis toolkit Release 0.19.1 Wes McKinney & PyData Development Team Nov 03, 2016 CONTENTS 1 What’s New 3 1.1 v0.19.1 (November 3, 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 7.4 Practical data analysis with Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 7.5 Modern . . . . . . . . . . . . . . 1895 Python Module Index 1897 xliv pandas: powerful Python data analysis toolkit, Release 0.19.1 PDF Version Zipped HTML Date: Nov 03, 2016 Version: 0.19.1 Binary Installers:

pandas: powerful Python data analysis toolkit Release 0.20.3 Wes McKinney & PyData Development Team Jul 07, 2017 CONTENTS 1 What’s New 3 1.1 v0.20.3 (July 7, 2017) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424 6.4 Practical data analysis with Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424 6.5 Exercises . . . . . . . . . . . . . . 1995 Python Module Index 1997 xlvi pandas: powerful Python data analysis toolkit, Release 0.20.3 PDF Version Zipped HTML Date: Jul 07, 2017 Version: 0.20.3 Binary Installers:

pandas: powerful Python data analysis toolkit Release 1.4.2 Wes McKinney and the Pandas Development Team Apr 02, 2022 CONTENTS 1 Getting started 3 1.1 Installation . . . . . . . . . . . . . . . . . . . . 3720 Bibliography 3723 Python Module Index 3725 xii pandas: powerful Python data analysis toolkit, Release 1.4.2 Date: Apr 02, 2022 Version: 1.4.2 Download documentation: PDF Version | open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Getting started New to pandas? Check out the getting