Title:

Testing and Dynamic Analysis

Code:ITS
Ac.Year:2019/2020
Sem:Summer
Curriculums:
ProgrammeField/
Specialization
YearDuty
BIT-2ndElective
IT-BC-3BIT-Elective
IT-BC-3BIT2ndElective
Language of Instruction:Czech
Public info:http://www.fit.vutbr.cz/study/courses/ITS/public/
Credits:5
Completion:credit+exam (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:2600026
 ExamsTestsExercisesLaboratoriesOther
Points:6000040
Guarantor:Smrčka Aleš, Ing., Ph.D. (DITS)
Deputy guarantor:Lengál Ondřej, Ing., Ph.D. (DITS)
Lecturer:Smrčka Aleš, Ing., Ph.D. (DITS)
Instructor:Smrčka Aleš, Ing., Ph.D. (DITS)
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
Prerequisites: 
Algorithms (IAL), DIFS
Formal Languages and Compilers (IFJ), DIFS
Operating Systems (IOS), DITS
Schedule:
DayLessonWeekRoomStartEndLect.Gr.Groups
ThulecturelecturesE112 10:0011:502BIA 2BIB 3BIT xx
 
Learning objectives:
  To provide an overview of the verification stage of development of a software system, the main focus is on dynamic analysis of software. To get practical skills with software testing required by a QA engineer. Mastering development of automatic tests of different aspects of verified programs. To get the basic knowledge of test planning and management.
Description:
  Test Specification. Coverage criteria for source code (EC, NC, EPC, PPC). Logic coverage criteria (PC, CC, MCDC). Input space partitioning. Input space coverage criteria. Black-box dynamic analysis. Tracing of shared resource usage. Testing multi-threaded applications. Testing network applications. Testing GUI. Performance testing. Test management.
Knowledge and skills required for the course:
  formal languages and compilers, algorithms, operating systems
Subject specific learning outcomes and competencies:
  The student knows fundamental techniques of software testing. The student is able to develop effective test suites of a software product. The student can analyse source codes, knows typical locations in a source code which are sensitive to be flawed. The student can analyse the behaviour of a program with finite or infinite runs with no explicit knowledge of the source code. The student can test and/or analyse program communications, program performance, usage of shared resources, manipulation with data storages, and a function of the graphical user interface. The student is able to find bugs in programs in a systematic way. The student knows the fundamentals of test planning and management. Student acquaints with English terminology in the subject.
Generic learning outcomes and competencies:
  The student will learn through project exercise on how to analyse a software product to raise its quality. The student gains a knowledge of how to create a test suite and how to find bugs in programs.
Why is the course taught:
  Software quality assurance is a necessary part of each development cycle of a software product. Software testing is the front line of quality assurance. In the age of making more complex software designs, more emphasis is given to automation of all development stages, software testing including. Students will be acquainted with problems of systematic software testing and learn basic approaches to its automation. Graduates of the course will have main competences of a quality engineer.
Syllabus of lectures:
 
  1. Role of testing and dynamic analysis in the development of a computer-based system. Introduction to terms in testing. Models of the testing process. Test requirements, test specification, and test plan. Test-driven development.
  2. Subsystem testing. Coverage criteria for source code. Control flow graph. Graph coverage criteria. Data flow coverage criteria.
  3. Relation of a graph coverage and the source code. Relation of a data flow coverage and the source code.
  4. Logic coverage criteria.
  5. Input domain modelling. Input space coverage criteria.
  6. Syntax-based testing.
  7. Test case development based on specification requirements of a system. Testing according to V-model.
  8. Combining test cases. Test-based bug localization. Bug-reporting.
  9. Black-box dynamic program analysis. Analysis based on tracing library and system calls. Constructing data and control flow graph. Constraints of the event sequence.
  10. Virtualization in dynamic analysis. Analysis of shared resource usage. Coverage criteria based on shared resource usage.
  11. Testing multi-threaded applications.
  12. Testing network applications. Testing the graphical user interface and its automation. Testing non-functional requirements.
  13. Performance testing. Test planning and management. A brief introduction to static analysis.
Syllabus - others, projects and individual work of students:
 
  1. Design of a test suite satisfying specified test criteria for a given software project.
  2. Implementation of an automated test suite.
Fundamental literature:
 
  • P. Ammann, J. Offutt. Introduction to Software Testing. Cambridge University Press, 2008, 322 p. ISBN 978-0-511-39330-3.
Study literature:
 
  • G. J. Myers, C. Sandler, T. Badgett. The Art of Software Testing, 2nd edition. John Wiley & Sons, 2011, 256 p., ISBN 978-1118031964.
  • A. Spillner, T. Linz, H. Schaefer. Software Testing Foundations : A Study Guide for the Certified Tester Exam. Rocky Nook Computing. 2014. p. 296. ISBN 9781937538422.
  • C. Kaner, J. Bach, B. Pettichord. Lessons Learned in Software Testing: A Context-Driven Approach. Wiley Computer Publishing, 2002, 286 p., ISBN 0-471-08112-4.
  • B. Marick. The Craft Of Software Testing, Subsystem Testing, Prentice Hall PTR, 1995, ISBN 0-13-177411-5.
  • A. Spillner, T. Linz, H. Schaefer. Software Testing Foundations, 2nd ed., 2007, 296 p., ISBN 978-1-9339-5278-9.
  • P. Farrell-Vinay. Manage Software Testing. Auerbach Publications, 2008, 537 p., ISBN 978-0-8493-9383-9.
Controlled instruction:
  Realization and defence of projects in due dates.
Progress assessment:
  Students can obtain up to 40 points from 2 projects and up to 60 points from the final exam.
Exam prerequisites:
  For receiving the credit and thus for entering the exam, students have to earn at least 15 points from all projects.
 

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