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Predictive Analysis - Seminar SS2019

The first session of the PA Seminar will start at 9 April at 10:15 in Room 1.047.

General Information

Predictive Analytics - Seminar SS2019 (MA-INF 4227)

Time Tuesdays, 10:15 - 11:45
Date Weekly, from April 9 according to the Schedule of the Lecture (will be announced)
Place Seminarraum 1.047 (Address: Endenicher Allee 19a, 53115 Bonn)
Language English
Lecturer Dr. Hamed Shariat Yazdi, Prof. Jens Lehmann

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Seminar Schedule

Time What? Who?
07.05.2019 Sketch Presentations All Students
21.05.2019 (We Start at 9:30) Middle Presentations All Students
04.06.2019 (We Start at 9:30) Final Presentations Sharmana, Rishi, Srinivas, Subbulakshashimi
18.06.2019 (We Start at 9:30) Final Presentations Nikhil, Pinkal, Deepansh


This contents will be provided in the classroom.

Teaching Staff

Who E-mail Tel Office
Dr. Hamed Shariat Yazdi shariat -at- cs uni-bonn de (0228) 73-4506 1.066


  • Course title: Seminar Predictive Analytics
  • Course number in module handbook: MA 4220
  • Course number in Basis: 612014220
  • Hours per week: 2
  • Credit points: 4.
  • Prerequisites:

The seminar is part of the ICM track of the M.Sc. curriculum. It is are aimed at students who want to become familiar with predictive analytics. As the target domain, we also consider the domain of software engineering.

In this year there will be no subsequent lab related to the seminar topics.

Predictive Analytics

Increasing complexity of modern software systems and rapid advancements in data science and analytical techniques has lead to a new paradigm which aims at using predictive techniques and analysis in the development and maintenance of software systems. Predictive Analytics (PA) covers different range of analytical, statistical and mining techniques that are used to extract data from existing data sets in software systems with different goals in mind. To name a few, PA techniques are used to predict software development cost/effort, estimate the quality of software systems, finding bugs and defected components etc. PA is also used in quantification and prediction of intermediate or final properties of interest in the software development process such as social, collaborative and teamwork activities and related patterns which typically occur in large software projects. Modeling the software project evolution based on historical repository data, characterization, classification, and prediction of software defects based on analysis of software repositories, finding suitable components and code fragments for reuse, and analysis of change patterns and trends to assist in future development are other typical activities in this regard.

Interested in further details? Then attend the info meeting. It will introduce necessary background on predictive analytics in software engineering, present a catalogue of topics for the seminar and clarify organizational issues. You will then be able to choose the seminar topic you want to pursue.

teaching/seminars/pa/2019/start.txt · Last modified: 2019/05/03 08:01 by Hamed Shariat Yazdi

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