Departments' graduate courses
Course start and periodicity may vary. Please see details for each course for up-to-date information. The courses are managed and administered by the respective departments. For more information about the courses, how to sign up, and other practical issues, please contact the examiner or course contact to be found in the course information.
Measurement in Software Engineering
- Course code: FDAT075
- Course higher education credits: 7.5
- Department: COMPUTER SCIENCE AND ENGINEERING
- Graduate school: Computer Science and Engineering
- Course is normally given: LP2
- Language: The course will be given in English
The course is intended to provide solid foundations for working with measurement in software engineering. During the course the students learn the basis of measurement theory in general, its applications in software engineering and the relevant standards. The course is divided into the following modules:
- Measurement theory: This module introduces the students to the main concepts from the measurement theory. The students discuss the relational measurement theory and discuss their application in software engineering. Practical exercises illustrate practical problems with applying measurement theory in software engineering.
- Measurement and measurement error: This module focuses on defining measures, calculating them and working with measurement error in software engineering. Practical exercises illustrate the main concepts and their application in software engineering.
- ISO 15939 Software and Systems Engineering Measurement Processes: This module introduces the students to the main measurement standard in software engineering. The students learn differences between base and derived measures, indicators, stakeholders, measurement methods/functions and other concepts from ISO 15939 and ISO VIM (Vocabulary in Metrology).
- ISO 250xx / ISO 9126 - Software Engineering -- Software product Quality Requirements and Evaluation (SQuaRE): This module describes one of the mainstream standards describing a set of measures used to evaluate products, processes and projects in software engineering. The students learn how to choose measures and how to use basic statistical tools like cluster analysis and PCA to identify main measures.
- Measurement specific for chosen subdomain: This module provides the students with the possibility to study measures in the subdomain of their studies. The students learn how to assess the applicability of measures in their domain and how to build a measurement system based on ISO 15939 in their subdomain. The practical exercises provide the students with the ability to make judgements and assessments of quality of measures used in literature in their subdomain.
- Software engineering measurement in research: This module discusses some of the measures used in software engineering research. The module focuses on designing quantitative studies and discussing threats to construct and conclusion validity of such studies. The practical exercise in this module illustrates the difficulty in designing a good quantitative study taking into consideration all aspects of a good measure.
After completion of the course the student is expected to be able to:
- Knowledge and understanding (G):
describe the concepts and mathematical background of the relational measurement theory,
describe and discuss the concepts from ISO 15939 measurement information model,
describe the principles behind ISO 250xx and ISO 9126, including the main categories of measures.
- Skills and abilities (G):
design and develop a measurement system for a subdomain of their doctoral studies
design and develop a measure to be used in the research project of their studies,
design a quantitative study in the subdomain of their choice d,
conduct a quantitative study in the subdomain of their choice.
- Judgement and approach (VG):
assess the quality of measures given the quality of measures described in the relational measurement theory and in the standards discussed in this course,
judge the dimensionality of the data set comprising of a number of measures designed according to standards,
assess the construct and conclusion validity of the studies based on measurements.