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    Advanced Software Testing, Maintenance And Evolution

    Posted By: ELK1nG
    Advanced Software Testing, Maintenance And Evolution

    Advanced Software Testing, Maintenance And Evolution
    Published 7/2025
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.95 GB | Duration: 2h 30m

    Automated Software Testing and Maintenance for Traditional (object-oriented) and modern (Cyber-physical) systems

    What you'll learn

    Foundations of software testing and software maintenance and evolution for traditional (object-oriented) and modern (Cyber-physical) systems

    Motivation, challenges and definitions in the field of software testing and software maintenance and evolution

    Techniques and technologies of software testing and software maintenance and evolution

    Variants of software maintenance, relations to software development life-cycle

    Quantitative analyses, empirical analyses, qualitative analyses of software. Evolution dynamics

    Leverage platforms and Digital Twins tools for test case generation, DevOps technologies in the context of Java and autonomous systems

    14 Remote Lectures in total (Max 2 hours each ) - 1 Lecture per week

    Some exercises are optional for the course, but they provide a better understanding of how the theory (published in research works) can be applied in practice

    This course offers a combination of lectures and (optional) exercises, plus a research (usually group) project

    Mix of learning technologies and research use projects

    Requirements

    Computer Science (and/or software engineering background) and programming skills in Python and/or Java

    Creative mindset and interest in new technologies and research

    Interested to discuss ideas and develop them during the project courses

    Description

    Software maintenance and testing are critical aspects of the software life cycle, often consuming more than two-thirds of the total effort invested in a software system. These efforts focus on modifications after delivery to correct faults, enhance performance, and adapt to evolving requirements such as platform updates or business changes. To manage these challenges effectively, it is essential to employ advanced techniques and tools that reduce costs and optimize resource utilization during development and testing.This course provides an in-depth exploration of the foundations of software evolution, maintenance, and testing. Students will examine key topics, including the management of successful but aging software systems (i.e., legacy software), object-oriented reengineering, refactoring, change patterns, defect prediction models, software quality analysis, and software evolution visualization.In the testing module, students will delve into software testing methodologies in the context of object-oriented systems (e.g., Java systems) and cyber-physical systems, such as autonomous drones and self-driving cars. The course also introduces cutting-edge analysis platforms and simulation tools, including PX4, BeamNG, Carla, and SDC-scissor. Students will learn about test case generation and continuous delivery technologies, gaining hands-on experience in applying these techniques to Java systems and autonomous systems.By the end of the course, students will have a strong foundation in advanced techniques for software maintenance, evolution, and testing, equipping them with the skills needed to address real-world challenges in these critical domains.Course mode:The lecture is done regularly:The lecture is done regularly over Microsoft Teams. After each lecture, a video of the live lecture is made available to students (even the ones who were not able to participate). If requested the course can be done fully in offline mode, with the videos of the lectures shared weekly. However, the exercises and projects will be discussed with the lecturer on a regular basis.The slides and material of each lecture are shared upfront on the webpage of the course. Questions can be made during the lectures.Projects and exercise meetings are in general done on a weekly basis via MS Teams. The time slots for them are discussed between the lecturer and the students. On request, other channels (e.g., Slack) can be created for running the projects, but the default way is to use sub-channels of the MS teams dedicated to the course.“We encourage all students to contact the lecturer(s) via MS teams and/or email for any doubt about the projects and exercisesFormat:This course offers a combination of lectures and exercises. The exercises are required for the course as they will provide a better understanding of how the theory (published in research works) can be applied in practice.This way the students actively learn during the lecture and through preparation before and after the lecture based on concrete examples.There will be exercises for the students to do individually and a project. The project will be done in groups of students formed by max 3-4 people. The group project will be about one of the main topics of the course itself with presentations from the students. In specific cases, individual projects are accepted. Sometimes, successful projects lead to the publication of relevant conferences or journals.Grading will be based on:(i) the practical exercise (not too complicated) performed during the course (35% of the grade);(iii) the (bigger) project (65% of the grade).You gain skills and competencies covered in central modules:- Foundations of software testing and software maintenance and evolution for traditional (object-oriented) and modern (Cyber-physical) systems- Motivation, challenges, and definitions in the field of software testing and software maintenance and evolution- Techniques and technologies of software testing and software maintenance and evolution- Variants of software maintenance, relations to software development life-cycle- Quantitative analyses, empirical analyses, and qualitative analyses of software. Evolution dynamics- The participants will also leverage platforms and Digital Twins (i.e., Simulation environments) tools (e.g., PX4, BeamNG, Carla, SDC-scissor, etc.), test case generation and continuous delivery technologies in the context of Java and autonomous systems (e.g., drones and self-driving cars).

    Overview

    Section 1: Introduction

    Lecture 1 Introduction to the Course

    Section 2: Lecture on "Foundations of Advanced Software Testing, Maintenance and Evolution"

    Lecture 2 Lecture on "Foundations of Advanced Software Testing, Maintenance and Evolution"

    Section 3: (Optional) Project definition

    Lecture 3 (Optional) Project definition

    Section 4: Lecture on "Empirical Software Engineering"

    Lecture 4 Lecture on "Empirical Software Engineering"

    Section 5: Lecture on "Change Type Analysis and Defect Prediction for Software Systems"

    Lecture 5 Lecture on "Change Type Analysis and Defect Prediction for Software Systems"

    Section 6: Lecture on Mining (Un-)Structured Data-1

    Lecture 6 Lecture on Mining (Un-)Structured Data-1

    Section 7: Lecture on Mining (Un-)Structured Data-2

    Lecture 7 Lecture on Mining (Un-)Structured Data-2

    Section 8: Lecture on "Peer/Modern Code Review: Theory and Practical Insights"

    Lecture 8 Lecture on "Peer/Modern Code Review: Theory and Practical Insights"

    Section 9: Lecture on "Automated Software Testing - Part 1 - Traditional Systems"

    Lecture 9 Lecture on "Automated Software Testing - Part 1 - Traditional Systems"

    Section 10: Lecture on "Summarization Techniques for Code, Changes, and Testing"

    Lecture 10 Lecture on "Summarization Techniques for Code, Changes, and Testing"

    Section 11: Lecture on "Bugs, Issues, and Faults affecting Cyber-physical systems (CPSs)"

    Lecture 11 Lecture on "Bugs, Issues, and Faults affecting Cyber-physical systems (CPSs)"

    Section 12: Lecture on "Automated Software Testing - Part 2 - Cyber-physical Systems - UAVs"

    Lecture 12 Lecture on "Automated Software Testing - Part 2 - Cyber-physical Systems - UAVs"

    Section 13: Lecture on "Automated Software Testing - Part 3 - Self-Driving Cars"

    Lecture 13 Lecture on "Automated Software Testing - Part 3 - Self-Driving Cars"

    Section 14: (Optional) Project Presentations

    Lecture 14 (Optional) Project Presentations

    Software maintenance and testing are critical aspects of the software life cycle, often consuming more than two-thirds of the total effort invested in a software system. These efforts focus on modifications after delivery to correct faults, enhance performance, and adapt to evolving requirements such as platform updates or business changes. To manage these challenges effectively, it is essential to employ advanced techniques and tools that reduce costs and optimize resource utilization during development and testing. This course provides an in-depth exploration of the foundations of software evolution, maintenance, and testing. Students will examine key topics, including the management of successful but aging software systems (i.e., legacy software), object-oriented reengineering, refactoring, change patterns, defect prediction models, software quality analysis, and software evolution visualization. In the testing module, students will delve into software testing methodologies in the context of object-oriented systems (e.g., Java systems) and cyber-physical systems, such as autonomous drones and self-driving cars. The course also introduces cutting-edge analysis platforms and simulation tools, including PX4, BeamNG, Carla, and SDC-scissor. Students will learn about test case generation and continuous delivery technologies, gaining hands-on experience in applying these techniques to Java systems and autonomous systems. By the end of the course, students will have a strong foundation in advanced techniques for software maintenance, evolution, and testing, equipping them with the skills needed to address real-world challenges in these critical domains.,This course address both academic and industrial researchers (both senior and junior) interested to be exposed to top notch and recent technological and researcher oriented approaches and tools/frameworks in both programming and robotics systems