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Introduction to Automated Analysis
Coursera
Course
Unknown

Introduction to Automated Analysis

University of Minnesota

This course introduces advanced automated analysis techniques to verify software correctness and detect common defects effectively.

Unknown4 weeksEnglish18,571 enrolled

About this Course

This course introduces state-of-the-art techniques for automated analysis. Automated analysis encompasses both approaches to automatically generate a very large number of tests to check whether programs meet requirements, and also means by which it is possible to prove that software meets requirements and that it is free from certain commonly-occurring defects, such as divide-by-zero, overflow/underflow, deadlock, race-condition freedom, buffer/array overflow, uncaught exceptions, and several other commonly-occurring bugs that can lead to program failures or security problems. The learner will become familiar with the fundamental theory and applications of such approaches, and apply a variety of automated analysis techniques on example programs. After completing this course, a learner will be able to: - Understand the foundations of automated verification: randomization and symbolic representations - Distinguish the strengths and weaknesses of random testing, symbolic analysis, static analysis, and model checking - Use a variety of state-of-the-art static analysis and automated testing tools for automated verification - Create executable requirements as an oracle suitable for automated testing and symbolic analysis - Understand how the choice of oracle affects fault-finding for automated analysis strategies. - Use automated testing to achieve full mutation coverage - Create a test plan that utilizes both manually-written tests and automated tests towards maximizing rigor, minimizing effort and time, and minimizing test costs. This course is intended for learners interested in understanding the principles of automation and the application of tools for analysis and testing of software This knowledge would benefit several typical roles: Software Engineer, Software Engineer in Test, Test Automation Engineer, DevOps Engineer, Software Developer, Programmer, Computer Enthusiast. We expect that you have some familiarity with the Software development Life-Cycle, an understanding of the fundamentals of software testing, similar to what is covered in the Introduction to Software Testing and Black-box and White-Box Testing Courses. Familiarity with an object-oriented language such as Java or ability to pick-up Java syntax quickly to write and modify code, and willingness to use tools and IDEs are assumed

What You'll Learn

  • Understand foundations of automated verification through randomization and symbolic methods
  • Distinguish strengths and weaknesses of random testing, symbolic analysis, static analysis, and model checking
  • Use advanced static analysis and automated testing tools for verification
  • Create executable requirements as oracles for automated testing and symbolic analysis
  • Understand how oracle selection affects fault detection in automated analysis
  • Apply automated testing to achieve full mutation coverage

Prerequisites

  • IDE installed (e.g., Eclipse)
  • Familiarity with testing terminology and practices

Instructors

M

Mike

Whalen

K

Kevin Wendt

Director of Graduate Studies, Software Engineering

Topics

Software Development
Computer Science
Computer Security and Networks
Software Development Tools
White-Box Testing
Security Testing
Test Data
Test Case
Test Automation
Unit Testing

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

تطوير البرمجيات
علوم الحاسوب
أمن الحاسوب والشبكات
أدوات تطوير البرمجيات
الاختبار الأبيض
اختبار الأمان
بيانات الاختبار
حالات الاختبار
Test Automation
Unit Testing

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