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How Code Coverage Analysis Can Improve Software Testing (Wie Codeabdeckungsanalyse Den Softwaretest Verbessern Kann) Ingo Nickles Sr

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How Code Coverage Analysis Can Improve Software Testing (Wie Codeabdeckungsanalyse Den Softwaretest Verbessern Kann) Ingo Nickles Sr How Code Coverage Analysis can Improve Software Testing (Wie Codeabdeckungsanalyse den Softwaretest verbessern kann) Ingo Nickles Sr. Field Application Engineer Vector Software © Vector Software Agenda . Vector Software – Who we are . Basics of code coverage analysis . Unit-, integration, and system tests . Change-based test selection . White-box tests with the Vector toolchain . Live Demo © Vector Software Vector Software – Who we are © Vector Software Vector Software . Founded in 1990 • First product released for Lockheed Martin’s C-130J Super Hercules . Corporate headquarters in Rhode Island, USA • US HQ – Providence, Europe HQ – London, Asia HQ – Yokohama • Worldwide Presales, Sales, and Technical Support – Direct and Indirect • Development in US, UK, and India • 90+ Employees • 100+ Partners TÜV SÜD Certified • 900+ Customers Software Tool for Safety Related . Global Services Development • On-site training, best practice workshops, project delivery . Since 2017 part of Vector Informatik, Stuttgart © Vector Software Where does VectorCAST Fit in Your Environment? VectorCAST Requirements Gateway • Dassault Systèmes® Reqtify® • IBM Rational DOORS® Requirements System • IBM Rational RequisitePro® Specification Testing • Jama Software® Compiler Integrations • Microsoft Excel® • Analog Devices V-DSP • Microsoft Word® • ARM RealView • Polarion® REQUIREMENTS™ • Cosmic Software • PTC Integrity® • FreeScale Code Warrior • Siemens ® Teamcenter™ • Fujitsu Software • Standard XML Integration • GNU / GNU Cross • Visure IRQA Architecture Testing • Green Hills MULTI • Hightec • IAR • Intel VectorCAST Integrations • Keil uVision • Atego Artisan Studio • Metaware • IBM Rational Rhapsody® System Unit • Microchip • MathWorks Simulink® • Microsoft VisualStudio Design Testing • NEC • Paradigm C++ Pro. • Renesas • STMicroelectronics • TASKING Compatible Static Analysis Tools • Texas Instruments CCS • Coverity® Test Advisor™ • Wind River • Gimpel Lint™ • Klocwork Insight™ Coding • MathWorks Polyspace® • PRQA™ QA·C|QA·C++ © Vector Software Testing: Early, Plenty, Thoroughly and Continuously Integration Static Analyis Unit Testing System Testing Testing Requirements Based Testing Code Coverage Based Testing Robustness Testing New Release: Regression Testing Continuous Integration: „Clean base“ Testing of each code change Parallel Testing Change Based Testing © Vector Software Basics of Code Coverage Analysis © Vector Software Why measure Code Coverage? . An important metric for certification . An important metric in testing • Testing (In-)Completeness • Quality/Adequacy of test cases • Requirements Traceability . An important metric for change based testing © Vector Software Code Coverage Level . Function coverage • Each function should be called . Function call coverage • Each function call should be executed . Statement coverage • Each line of code should be executed . Decision (Branch) coverage • Each decision should be executed with outcome True and False . Condition coverage • Each condition in each decision should be executed with outcome True and False . Condition/Decision coverage • Combination of Condition and Decision Coverage . Modified condition/decision coverage (MC/DC) • Condition/Decision Coverage with verification that conditions are independant © Vector Software Code Coverage and Certification High Software Quality DAL/SIL/Level/Class Code Coverage Level Code Coverage Low Software Quality © Vector Software Why achieve 100% Code Coverage? . 100% Code Coverage means • Each part of the code was executed without crashing • There is no unreachable code • We tested thoroughly and archieved a minimum number of test cases • “Program elements […] covered by any test case see about half as many bug-fixes as those not covered” * . 100% Code Covearge does not mean • The code is correct • The code is complete • The test is complete *Source: Can Testedness be Effectively Measured? Rahul Gopinath; Oregon State University; based on 250 real world programs © Vector Software Unit Test Integration Test System Test Coding © Vector Software How often should we test the software? Phase of the S/W Dev Relative cost to fix a bug* Testing Phase ~Cost/Bug** Maintenance 100x System Test $5000 Testing 15x Integration Test $500 Implementation 6.5x Full Build $50 Design 1 Unit Test $5 . As soon and as often as possible! . Find any bug in early stage => reduce the cost of fixing the bug Cost of fixing a bug depending of time passed since introduction. * DevOps: Shift left with continuous testing by using automation and virtualization (IBM; Dibbe Edwards) ** How Google Tests Software (James A. Whittaker, Jason Arbon, and Jeff Carollo) © Vector Software Functional Testing needs Requirements Customer Request Requirements System Analysis Testing . Basis for SW Development System Link Test Cases Requirements . Basis for SW Tests (functional) High Level Integration . Allows Traceability Design Testing • Requirement <-> Test Case High-Level Link Test Cases • Requirement <-> Source Code Requirements . Allows Change Impact- Analysis Detailed Unit • When source code changes: Design Testing • -> what requirement might be affected Low-Level Link Test Cases • When a requirement changes: Requirements • -> what source code might be affected • -> what test case might be affected Coding © Vector Software Change-based Test Selection Test Less, Fail Faster © Vector Software Test Cases in a Project Test Cases System System Requirements Test Cases High-Level Integration Requirements Test Cases Low-Level Unit Requirements Test Cases Coding Source Code © Vector Software Change-based Test case selection . What can change? • Requirement • Invalidate Test Cases linked to that Requirement • Source Code Traceability can give a clue what code needs to be changed • Test Case • Re-run the changed Test Case • Source Code • A real challenge • Do we need to execute all test cases? • Tools can help reducing the test execution times with an intelligent Test Case Selection © Vector Software Continuous Testing of Code Changes Test Cases System System Requirements Test Cases High-Level Integration Requirements Test Cases Low-Level Unit Requirements Test Cases Coding Source Code Code Change © Vector Software White-box tests with the Vector toolchain © Vector Software vTESTstudio Demo Setup VectorCAST VectorCAST Source Code Instrumented Source Code Execute Test-Add Coverage CANoe Instrument Execute Test-Multiply Coverage Execute Test-Subtract Coverage Reporting © Vector Software Live Demo © Vector Software © Vector Software .
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