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 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 required 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 and Helm

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

pandas: powerful Python data analysis toolkit Release 0.13.1 Wes McKinney & PyData Development Team February 03, 2014 CONTENTS 1 What’s New 3 1.1 v0.13.1 (February 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . 1209 Python Module Index 1211 vi pandas: powerful Python data analysis toolkit, Release 0.13.1 PDF Version Zipped HTML Date: February 03, 2014 Version: 0.13.1 Binary for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any

pandas: powerful Python data analysis toolkit Release 0.15.2 Wes McKinney & PyData Development Team December 11, 2014 CONTENTS 1 What’s New 3 1.1 v0.15.2 (December 12, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 6.4 Practical data analysis with Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 6.5 Excel . . . . . . . . . . . . 1567 Python Module Index 1569 vii viii pandas: powerful Python data analysis toolkit, Release 0.15.2 PDF Version Zipped HTML Date: December 11, 2014 Version: 0.15.2 Binary