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This course is part of Software Testing and Automation Specialization
Instructors: Mike
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15,351 already enrolled
Included with
(79 reviews)
Recommended experience
Intermediate level
IDE installed (e.g., Eclipse). Familiar with testing terminology and practice (see previous courses in specialization).
(79 reviews)
Recommended experience
Intermediate level
IDE installed (e.g., Eclipse). Familiar with testing terminology and practice (see previous courses in specialization).
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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.
In this module we will learn about a range of techniques for analysis of programs and methods to automate testing. Along the way we will learn how to specify properties of interest to check about a program and capture assumptions about the environment for effective testing. To reinforce some of the important concepts learned we will practice automated testing using effective tools on a concrete example.
8 videos1 reading5 assignments1 programming assignment
The focus of this module is to understand how various techniques can help us automate the generation of useful and numerous tests. We will examine ways to specify and use properties of the system and the environment to guide the generation of test data.
8 videos4 assignments1 programming assignment
The goal of this module is to introduce the learner to the principles of statically analyzing programs, understand how analysis techniques work by looking at some example analyses, and some good practices to follow when designing programs to enable the tools to help us detect and avoid defects. The learner will gain an understanding of using static analysis tools by looking at one concrete tool.
5 videos1 reading3 assignments
This module will examine how to use effective automation techniques for a variety of purposes such as performing effective regression testing, discovering security vulnerabilities and monitoring software at run-time for critical properties.
6 videos2 readings4 assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
SkillUp EdTech
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University of Minnesota
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79 reviews
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Reviewed on Nov 12, 2020
Muy bueno!, seria interesante ver mas demostraciones con herramientas.
Reviewed on Jul 21, 2023
Please add specific tutorial on how to set up something
Reviewed on Oct 16, 2024
The course is decent, the presentations are great in most, and lots of learning. Its scope is also vast and it only gives a glimpse into what is possible.
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