Challenges of Sonarqube Plug-In Maintenance
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Command Line Interface
Command Line Interface Squore 21.0.2 Last updated 2021-08-19 Table of Contents Preface. 1 Foreword. 1 Licence. 1 Warranty . 1 Responsabilities . 2 Contacting Vector Informatik GmbH Product Support. 2 Getting the Latest Version of this Manual . 2 1. Introduction . 3 2. Installing Squore Agent . 4 Prerequisites . 4 Download . 4 Upgrade . 4 Uninstall . 5 3. Using Squore Agent . 6 Command Line Structure . 6 Command Line Reference . 6 Squore Agent Options. 6 Project Build Parameters . 7 Exit Codes. 13 4. Managing Credentials . 14 Saving Credentials . 14 Encrypting Credentials . 15 Migrating Old Credentials Format . 16 5. Advanced Configuration . 17 Defining Server Dependencies . 17 Adding config.xml File . 17 Using Java System Properties. 18 Setting up HTTPS . 18 Appendix A: Repository Connectors . 19 ClearCase . 19 CVS . 19 Folder Path . 20 Folder (use GNATHub). 21 Git. 21 Perforce . 23 PTC Integrity . 25 SVN . 26 Synergy. 28 TFS . 30 Zip Upload . 32 Using Multiple Nodes . 32 Appendix B: Data Providers . 34 AntiC . 34 Automotive Coverage Import . 34 Automotive Tag Import. 35 Axivion. 35 BullseyeCoverage Code Coverage Analyzer. 36 CANoe. 36 Cantata . 38 CheckStyle. .. -
Avatud Lähtekoodiga Vahendite Kohandamine Microsoft Visual C++ Tarkvaralahenduste Kvaliteedi Analüüsiks Sonarqube Serveris
TALLINNA TEHNIKAÜLIKOOL Infotehnoloogia teaduskond Tarkvarateaduse instituut Anton Ašot Roolaid 980774IAPB AVATUD LÄHTEKOODIGA VAHENDITE KOHANDAMINE MICROSOFT VISUAL C++ TARKVARALAHENDUSTE KVALITEEDI ANALÜÜSIKS SONARQUBE SERVERIS Bakalaureusetöö Juhendaja: Juhan-Peep Ernits PhD Tallinn 2019 Autorideklaratsioon Kinnitan, et olen koostanud antud lõputöö iseseisvalt ning seda ei ole kellegi teise poolt varem kaitsmisele esitatud. Kõik töö koostamisel kasutatud teiste autorite tööd, olulised seisukohad, kirjandusallikatest ja mujalt pärinevad andmed on töös viidatud. Autor: Anton Ašot Roolaid 21.05.2019 2 Annotatsioon Käesolevas bakalaureusetöös uuritakse, kuidas on võimalik saavutada suure hulga C++ lähtekoodi kvaliteedi paranemist, kui ettevõttes kasutatakse arenduseks Microsoft Visual Studiot ning koodikaetuse ja staatilise analüüsi ülevaate saamiseks SonarQube serverit (Community Edition). Seejuures SonarSource'i poolt pakutava tasulise SonarCFamily for C/C++ analüsaatori (mille eelduseks on SonarQube serveri Developer Edition) asemel kasutatakse tasuta ja vaba alternatiivi: SonarQube C++ Community pluginat. Analüüsivahenditena eelistatakse avatud lähtekoodiga vabu tarkvaravahendeid. Valituks osutuvad koodi kaetuse analüüsi utiliit OpenCppCoverage ja staatilise analüüsi utiliit Cppcheck. Siiski selgub, et nende utiliitide töö korraldamiseks ja väljundi sobitamiseks SonarQube Scanneri vajadustega tuleb kirjutada paar skripti: üks PowerShellis ja teine Windowsi pakkfailina. Regulaarselt ajastatud analüüside käivitamist tagab QuickBuild, -
Write Your Own Rules and Enforce Them Continuously
Ultimate Architecture Enforcement Write Your Own Rules and Enforce Them Continuously SATURN May 2017 Paulo Merson Brazilian Federal Court of Accounts Agenda Architecture conformance Custom checks lab Sonarqube Custom checks at TCU Lessons learned 2 Exercise 0 – setup Open www.dontpad.com/saturn17 Follow the steps for “Exercise 0” Pre-requisites for all exercises: • JDK 1.7+ • Java IDE of your choice • maven 3 Consequences of lack of conformance Lower maintainability, mainly because of undesired dependencies • Code becomes brittle, hard to understand and change Possible negative effect • on reliability, portability, performance, interoperability, security, and other qualities • caused by deviation from design decisions that addressed these quality requirements 4 Factors that influence architecture conformance How effective the architecture documentation is Turnover among developers Haste to fix bugs or implement features Size of the system Distributed teams (outsourcing, offshoring) Accountability for violating design constraints 5 How to avoid code and architecture disparity? 1) Communicate the architecture to developers • Create multiple views • Structural diagrams + behavior diagrams • Capture rationale Not the focus of this tutorial 6 How to avoid code and architecture disparity? 2) Automate architecture conformance analysis • Often done with static analysis tools 7 Built-in checks and custom checks Static analysis tools come with many built-in checks • They are useful to spot bugs and improve your overall code quality • But they’re -
A Machine Learning Approach Towards Automatic Software Design Pattern Recognition Across Multiple Programming Languages
ICSEA 2020 : The Fifteenth International Conference on Software Engineering Advances A Machine Learning Approach Towards Automatic Software Design Pattern Recognition Across Multiple Programming Languages Roy Oberhauser[0000-0002-7606-8226] Computer Science Dept. Aalen University Aalen, Germany e-mail: [email protected] Abstract—As the amount of software source code increases, languages of programmers that affect naming, tribal manual approaches for documentation or detection of software community effects, the programmer's (lack of) knowledge of design patterns in source code become inefficient relative to the these patterns and use of (proper) naming and notation or value. Furthermore, typical automatic pattern detection tools markers, make it difficult to identify pattern usage by experts are limited to a single programming language. To address this, or tooling. While many code repositories are accessible to our Design Pattern Detection using Machine Learning the public on the web, many more repositories are hidden (DPDML) offers a generalized and programming language within companies or other organizations and are not agnostic approach for automated design pattern detection necessarily accessible for analysis. While determining actual based on Machine Learning (ML). The focus of our evaluation pattern usage is beneficial for identifying which patterns are was on ensuring DPDML can reasonably detect one design used where and can help avoid unintended pattern pattern in the structural, creational, and behavioral category for two popular programming languages (Java and C#). 60 degradation and associated technical debt and quality issues, unique Java and C# code projects were used to train the the investment necessary for manual pattern extraction, artificial neural network (ANN) and 15 projects were then recovery, and archeology is not economically viable. -
Ics-Fd-Qa Project • Objective • Present Scope • QA Calling Sequence • Present Status & Tools • Integration Into Projects & Kobe • Some Issues • Conclusion
ics-fd-qa project • Objective • Present scope • QA calling sequence • Present status & tools • Integration into projects & kobe • Some issues • Conclusion • Your input, discussion Objective • Provide integrated code quality assessment • Standard analysis method, but ignore coding styles a.f.a.p. • High quality code scans, try to find “fishy” pieces automatically • Report only false-true, keep noise down • Graphical output with sonarqube, fancy, motivating • Support and encourage easy documentation writing (sphinx, …) • Provide clear code fix proposals if available • Provide q.a. history • Have minimal impact on projects • Existing build chains are sacred • Be able to digest lots of legacy code and give orientation for “hot spots” Present Scope • ICS-FD section internal • C/C++ code, no java, no control+ • Cmake build chain ( qmake/Qt/bear come later ) • Static code analysis: clang-tidy, cppcheck (more tools can be easily added, but clang-tidy is the upshot) • Push results to tmp-sonarqube, will have own fd instance later (dixit ics- in) • Integrated with docker, gitlab-CI and uses a bit of nexus • Therefore is kobe-compatible , see later • Can update existing sphinx-doc “almost for free”: tools are included in the docker image QA Sonarqube Ics-fd-qa (gitlab, nexus) Ics-fd qa webpage Sonar-scanner transmission Docker: clang 7.0.1 Calling • Code issues Python 3, Sphinx, • Proposed corrections Doxygen, Breathe, sequence • Statistics Trigger with payload Sonar-scanner, break, • Graphs • Artifact URL cmake 3, … • Project name stages: Push new sources • Control flags 1. Fetch sources URL & unpack 2. analysis: clang-tidy, cppcheck, aux results, output & logs artifacts C/C++ 3. Push to sonarqube Trigger project using sonar-scanner Pipeline Build: ADDED stage: • gitlab • all sources • Pull qa scripts from nexus • cmake are available • Analyze json-db for full • Produce a source dependencies build • Pack sources into artifact Nexus command (URL) Temp json-db • Trigger with payload repo QA calling sequence • works mostly blind. -
A Graduate Certificate
ADUS Technologies s.r.o. Fraňa Kráľa 2049 058 01 Poprad, Slovakia T: +421 (0) 949 407 310 | E: [email protected] www.adus-technologies.com Mykhailo Riabets [email protected] EDUCATION 2005 to The Torun secondary school (engineering) 2012 A graduate certificate 2015 to Uzhgorod National University – Faculty of Information Technologies 2019 Bachelor PROFESSIONAL EXPERIENCE 12/2018 to ADUS Technologies s.r.o., Poprad, Slovakia present ELVIS – a software product for a Swiss Customer that allows you to create powerful online applications, design services and systems for any kind of business. Utilized technologies: TypeScript, Angular 11, Sass, Git, IntelliJ IDEA, Sonarqube, JWT authentication, Rest Api, YouTrack Denta5 – an administrative system for managing clients and their orders, which allows clients to create orders containing a large number of attachments such as dental scans and dental aids. Utilized technologies: TypeScript, Angular 11, Sass, Git, IntelliJ IDEA, YouTrack Treves – internal system for organizing and synchronizing work in the company, planning the production of products and reporting on the products produced. Utilized technologies: TypeScript, Angular 11, Sass, Git, IntelliJ IDEA, YouTrack Reactoo Node.js backend – Node.js platfrom developer for UK Customer specializing in live streaming. Custom solution based on AWS Lambdas and heavy use of customized JavaScript solutions o Successful refactoring of code to use CI and Lambda layers o Backend and front-end tasks node.js + React Utilized technologies: JavaScript, AWS Lamda, Lambda Layers, ffmpeg Utimate solution – React & Angular Developer Developing internal platfrom system for corporate purposes Utilized technologies: TypeScript, Angular9, NgRx, Git, IntelliJ IDEA, React. Angular Common – Angular Developer It is an internal core library based on Angular 9 and Prime NG UI components. -
Canarys Automations Private Limited
Canarys Automations Private Limited Sheshadri Srinivas [email protected] https://www.ecanarys.com About Canarys Over 25+ years in the industry, having offices in Bangalore, India and USA, Canarys is a comprehensive solution provider specializing in DevOps, Mobile Apps, MS Dynamics, TFS Consulting, Staffing and Application Development across a broad spectrum of domains. About Canarys Canarys is a DevOps and Azure (Cloud Platform) Gold Partner. Canarys is also Azure CSP-Cloud Solutions Provider. Canarys has been providing ALM and DevOps Consulting services for Professional services for Consulting services consulting services in Microsoft customers in Microsoft Corp-USA through MCS from 2+ India from last 10+ years APAC region from last 3 from 3+ years years on Microsoft TFS, VSTS, years on TFS, VSTS and Azure and Xamarin Azure Canarys was alsoawarded as Our Services DevOps-VSTS Microsoft Mobile MS Azure Software Staffing Consulting Dynamics Solutions Solutions Services Solutions Canarys has adopted best practices and optimized processes to improve overall service delivery to its customers. Our business model has been refined by the experience gained, partnering with leading organizations for end-to-end solutions. Business Region USA INDIA EUROPE Asia Pacific VSTS/TFS DevOps Consulting Version DevOps/ALM 02 Upgrades 03 01 Migration Best Practises Release Process Deployment & 04 Automation 05 Tech Support VSTS/TFS DevOps Consulting Assess the customer about their current DevOps methodologies, release cycles, goals and understand their pain points Propose Microsoft DevOps solution using existing tooling and Microsoft Platform Evangelize the customer about Microsoft DevOps tools through a workshop or an event and demonstrate the features and usage Migration of TFS work loads to Visual Studio Team Services (VSTS). -
Comparison of Static Analysis Tools for Quality Measurement of RPG Programs
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by SZTE Publicatio Repozitórium - SZTE - Repository of Publications Comparison of Static Analysis Tools for Quality Measurement of RPG Programs Zolt´anT´oth1, L´aszl´oVid´acs2, and Rudolf Ferenc1 1 Department of Software Engineering, University of Szeged, Hungary [email protected], [email protected] 2 MTA-SZTE Research Group on Artificial Intelligence, Hungary [email protected] Abstract. The RPG programming language is a popular language em- ployed widely in IBM i mainframes nowadays. Legacy mainframe systems that evolved and survived the past decades usually data intensive and even business critical applications. Recent, state of the art quality assur- ance tools are mostly focused on popular languages like Java, C++ or Python. In this work we compare two source code based quality man- agement tools for the RPG language. The study is focused on the data obtained using static analysis, which is then aggregated to higher level quality attributes. SourceMeter is a command line tool-chain capable to measure various source attributes like metrics and coding rule viola- tions. SonarQube is a quality management platform with RPG language support. To facilitate the objective comparison, we used the SourceMe- ter for RPG plugin for SonarQube, which seamlessly integrates into the framework extending its capabilities. The evaluation is built on analysis success and depth, source code metrics, coding rules and code duplica- tions. We found that SourceMeter is more advanced in analysis depth, product metrics and finding duplications, while their performance of cod- ing rules and analysis success is rather balanced. -
Setup Development Environment for the Openmdm(R) Application Eclipse Mdmbl Project
Setup Development Environment for the openMDM(R) Application Eclipse mdmbl project Document history: Author Date Affects Version Description Angelika Wittek 9.6.2017 0.6 initial version Angelika Wittek 12.6.2017 0.6 User Preference Service added Alexander Nehmer 22.6.2017 0.6 Review and additions Angelika Wittek 30.6.2017 0.6 Mailing Lists and ECA infos added Angelika Wittek 18.7.2017 0.7 Comments from Ganesh inserted, Glassfish Bugs added Angelika Wittek 31.07.2017 0.7 Elasticsearch version added, exported to pdf for mdmbl page Alexander Nehmer 4.8.2017 0.7 Added Eclipse Hot Deploy section Ganesh Deshvini 14.8.2017 0.7 Parameter to skip npm install Angelika Wittek 13.9.2017 0.8 additions for new version exported to pdf for download pages Alexander Nehmer 19.9.2017 0.8 Added SonarQube setup in Eclipse Angelika Wittek 07.11.2017 0.9 Extending the introduction chapter 21.11.2017 Angelika Wittek 23.11.2017 0.9 changes in service.xml, restructuring chapters, exported for V0.9 Angelika Wittek 26.02.2018 0.10 changes for version V0.10 Angelika Wittek 20.03.2018 0.11 IP Management Chapter added Angelika Wittek 02.05.2018 0.11 Chapter 6 extended Angelika Wittek 14.05.2018 5.0.0M1 Updates for new version Angelika Wittek 10.9.2018 5.0.0M2 / 5.0.0M3 Updates for new version Angelika Wittek 25.09.2018 5.0.0M4 Realm configuration changes added. Angelika Wittek 10.10.2018 5.0.0 Switch to EPL 2.0 Copyright(c) 2017-2018, A. -
Incremental Static Analysis of Large Source Code Repositories
Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Measurement and Information Systems Incremental Static Analysis of Large Source Code Repositories Bachelor’s Thesis Author Advisors Dániel Stein Gábor Szárnyas, PhD Student Dr. István Ráth, Research Fellow 2014 Contents Kivonat i Abstract ii 1 Introduction 1 1.1 Context ..................................... 1 1.2 Problem Statement and Requirements .................... 2 1.3 Objectives and Contributions ......................... 2 1.4 Structure of the Thesis ............................. 3 2 Background and Related Work 4 2.1 Big Data and the NoSQL Movement ..................... 4 2.1.1 Sharding ................................ 5 2.1.2 High Availability ............................ 5 2.1.3 4store .................................. 6 2.1.4 Query Languages and Evaluation Strategies ............. 6 2.2 Modeling .................................... 7 2.2.1 Metamodels and Instance Models ................... 8 2.2.2 The Eclipse Modeling Framework .................. 8 2.2.3 JaMoPP ................................. 9 2.2.4 Graph Data Models ........................... 10 2.2.5 Model Queries over EMF and RDF .................. 13 2.3 Static Analysis in Practice ........................... 14 2.3.1 Checkstyle ............................... 14 2.3.2 FindBugs ................................ 15 2.3.3 PMD ................................... 15 2.4 Well-formedness Checking over Code Models ................ 16 3 Overview of the Approach 18 -
Efficient Feature Selection for Static Analysis Vulnerability Prediction
sensors Article Efficient Feature Selection for Static Analysis Vulnerability Prediction Katarzyna Filus 1 , Paweł Boryszko 1 , Joanna Doma ´nska 1,* , Miltiadis Siavvas 2 and Erol Gelenbe 1 1 Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Baltycka 5, 44-100 Gliwice, Poland; kfi[email protected] (K.F.); [email protected] (P.B.); [email protected] (E.G.) 2 Information Technologies Institute, Centre for Research & Technology Hellas, 6th km Harilaou-Thermi, 57001 Thessaloniki, Greece; [email protected] * Correspondence: [email protected] Abstract: Common software vulnerabilities can result in severe security breaches, financial losses, and reputation deterioration and require research effort to improve software security. The acceleration of the software production cycle, limited testing resources, and the lack of security expertise among programmers require the identification of efficient software vulnerability predictors to highlight the system components on which testing should be focused. Although static code analyzers are often used to improve software quality together with machine learning and data mining for software vulnerability prediction, the work regarding the selection and evaluation of different types of relevant vulnerability features is still limited. Thus, in this paper, we examine features generated by SonarQube and CCCC tools, to identify those that can be used for software vulnerability prediction. We investigate the suitability of thirty-three different features to train thirteen distinct machine learning algorithms to design vulnerability predictors and identify the most relevant features that should be used for training. Our evaluation is based on a comprehensive feature selection process based on the correlation analysis of the features, together with four well-known feature selection techniques. -
Multi-Language Software Metrics
FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Multi-Language Software Metrics Gil Dinis Magalhães Teixeira Mestrado Integrado em Engenharia Informática e Computação Supervisor: João Bispo, PhD Second Supervisor: Filipe Figueiredo Correia, PhD February 12, 2021 © Gil Teixeira, 2021 Multi-Language Software Metrics Gil Dinis Magalhães Teixeira Mestrado Integrado em Engenharia Informática e Computação Approved in oral examination by the committee: President: Prof. João Carlos Pascoal Faria, PhD External Examiner: Dr. José Gabriel de Figueiredo Coutinho, PhD Supervisor: Prof. João Carlos Viegas Martins Bispo, PhD Second Supervisor: Prof. Filipe Alexandre Pais de Figueiredo Correia, PhD February 12, 2021 Abstract Software metrics are of utmost significance in software engineering. They attempt to capture the properties of programs, which developers can use to gain objective, reproducible and quantifiable measurements. These measurements can be applied in quality assurance, code debugging, and performance optimization. The relevance of their use is continuously increasing with software systems growing in complexity, size, and importance. Implementing metrics is a tiring and challenging task that most companies ought to surpass as part of their development process. Also, this task usually must be repeated for every language used. However, suppose we can decompose the implementation of software metrics into a sequence of basic queries to the source code that can be implemented in a language-independent way. In that case, these metrics can be applied to any language. Many programming languages share similar concepts (e.g., functions, loops, branches), which has led certain approaches to raise the abstraction level of source-code analysis and support mul- tiple languages. LARA is a framework developed in FEUP (Faculty of Engineering of the Univer- sity of Porto) for code analysis and transformation that is agnostic to the language being analyzed.