|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)|
|Lecturer||Dr. Hamed Shariat Yazdi, Prof. Jens Lehmann|
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|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.
|Dr. Hamed Shariat Yazdi||shariat -at- cs uni-bonn de||(0228) 73-4506||1.066|
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.
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.