Course co-ordinator(s): Dr Idris Skloul Ibrahim (Edinburgh).
Aims:
- To develop a critical appreciation of the importance and benefits of software quality in industry
- To enable students to gain competence and practice in software testing at their workplaces
- To enable industry to provide learning opportunities in software testing and software quality assurance
- To enable students to put into practice software quality knowledge and skills, applicable to and contextualised for the host company
Detailed Information
Pre-requisites: none.
Location: Edinburgh.
Semester: 3.
Syllabus:
Work-based learning:
- rigorous and organised software testing
- combinatorial models in software testing
- software testing life cycle and levels of testing
- rapid prototyping and software quality
- OO testing and procedural testing
- test-driven design, implementation and critical evaluation of software at the workplace
- using data analytics to support software quality and business expectations
- data-flow analysis
- techniques, tools and strategies used in industry
Work-based practice:
- Industrial project embedded in and contextualised for the host company, focusing on the practical aspects software testing
Learning Outcomes: Subject Mastery
- Understanding of established techniques, models and strategies underlying software testing.
- Become knowledgeable with the techniques and tools of software quality used in the students' workplace
- Practical ability in using rapid prototyping and data analytics to support software quality
- Ability to design and develop robust, secure and reliable software applications
- Ability to critically evaluate the software quality practices used in industry
- Understand software testing principles and can practice them independently in an industrial context
Learning Outcomes: Personal Abilities
- Skills in selecting, applying and evaluating technologies used to enhance software quality
- Ability to analyse complex software and carry out its testing an evaluation
- Ability to relate and apply learned knowledge to work based scenarios
- Reflection, constructive criticism and learning from peers (PDP)
- Showing autonomy, creativity, problem solving (PDP) and communication (PDP) skills
Assessment Methods: Due to covid, assessment methods for Academic Year 2021-22 may vary from those noted on the official course descriptor. Please see the Computer Science Course Weightings and the Maths Course Weightings for 2020-21 Semester 1 assessment methods.
SCQF Level: 9.
Credits: 15.