Institute of Computer Science
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  3. Software Analytics (LTAT.05.008)
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Software Analytics 2017/18 spring

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Software Analytics

Lecturers: Dietmar Pfahl & Ezequiel Scott

Course Responsible and Lecturer (Part 1): Dietmar Pfahl (dietmar dot pfahl at ut dot ee) - room: 302
Lecturer (Part 2): Ezequiel Scott (ezequiel dot scott at ut dot ee) - room: 309

This course provides an introduction to data-driven techniques supporting software engineers and managers in decision-making. The course is suitable for 1st year MSc students who successfully completed the pre-requisite course "Data Mining".

Note that this course will not explain the basics of the techniques taught in the "Data Mining" course. We expect that these techniques are already known to students participating in the "Software Analytics" course. The "Software Analytics" course differs from the "Data Mining" course by:
* Focusing on software engineering related applications
* Giving a broader overview on the role of data science in the field of software engineering
* Explaining how to collect/retrieve software engineering related data

Upon completion of this course, a student will:
1. Understand the role of data science in software engineering
2. Know the basic approaches to empirical software engineering
3. Know how to apply data mining in the context of software engineering knowledge discovery and decision-support

On successful completion, students will receive 3 ECTS point.

As background reading (even before the course starts), recommend this article: "The ABC of Software Engineering Research" by Klaas-Jan Stol and Brian Fitzgerald: DOI:10.1145/3241743

  • Institute of Computer Science
  • Faculty of Science and Technology
  • University of Tartu
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