Applications of Machine Learning in Software Engineering Seminar 2012

Applications of Machine Learning in Software Engineering

Master Seminar (IN2107, IN8901)

Beschreibung

Thema des Seminars sind Ansätze aus den Bereichen Maschinelles Lernen und Data Mining und deren Einsatz in der Softwareentwicklung. Es wird diskutiert, wie solche Ansätze eingesetzt werden können, um Programme besser zu verstehen, große Mengen an Benutzerinput zu analysieren und wie Wissen und Zusammenhänge aus unstrukturierten Daten gewonnen werden kann.

Jeder Teilnehmer präsentiert dabei eine Ansatz des Maschinellen Lernens und eine Anwendung in der Software Entwicklung.

Summary

This seminar focuses on techniques from machine learning and data mining, and surveys their application in software engineering.
In particular, the seminar investigates how such techniques aid program comprehension, help to analyze and interpret large amounts of user input, and facilitate the extraction of relevant knowledge from unstructured data.

During the seminar each participant will present a machine learning technique including a particular application in software engineering.

Organizational Issues

NEW NEW NEW The kickoff meeting will be on 6.11, 14-15 h, room 01.07.58. We will discuss research methods and seminar topics in that session. NEW NEW NEW
Report and presentation can be in German or English.
For signing up in the seminar write an email to emitza.guzman(at)mytum.de.
In case of any questions please write an e-mail to emitza.guzman(at)mytum.de.

Modalities

Grades will be based on the following criteria:

Ability to do independent research
Oral presentation
Written term paper
Active participation in all the other presentations (compulsory attendance)

Lecturers

Prof. Bernd Brügge, Ph.D.

Teaching Assistants

Topics

Paper	Conf.	ML Technique	Presenter	Advisor
Henß et al.: Semi-automatically extracting FAQs to improve accessibility of software development knowledge	ICSE 2012	Latent Dirichlet Allocation	Aleksandar Stoimenov	Emitzá Guzmán
Bacchelli et al.: Content classification of development emails	ICSE 2012	Naive Bayes	Martin Stoll	Emitzá Guzmán
McMillan et al: Detecting Similar Software Applications	ICSE 2012	Latent Semantic Indexing	Hao Ji	Emitzá Guzmán
Murphy-Hill et al.: Improving Software Developers’ Fluency by Recommending Development Environment Commands	FSE 2012	Collaborative Filtering	Burak Söhmelioglu	Emitzá Guzmán
Zhong et al.: Inferring Resource Specifications from Natural Language API Documentation	ASE 2009	Hidden Markov Chains	Viktor Bogishef	Emitzá Guzmán
Kim et al.: Towards an Intelligent Code Search Engine	AAAI 2010	K-means	Pei Li	Emitzá Guzmán
Di Fatta et al.: Discriminative Pattern Mining in Software Fault Detection	SOQUA 2006	Frequent subtree mining	Mads Esholdt Wiemann	Tobias Röhm
Lo et al.: Classification of Software Behaviors for Failure Detection: A Discriminative Pattern Mining Approach	KDD 2009	Frequent iterative pattern mining, classification	Vesko Georgiev	Tobias Röhm
Ghazarian, Noorhosseini: Automatic detection of users' skill levels using high-frequency user interface events	User Modeling and User-Adapted Interaction, 2010	Decision Trees	Rui Yuan	Tobias Röhm
Tseng, Lin: Efficient mining and prediction of user behavior patterns in mobile web systems	Information and Software Technology 2006	SPAM mine (own algo)	Serge Krauze	Tobias Röhm
Saito et al.: Understanding user behavior through summarization of window transition logs	Databases in Networked Information Systems, 2011	HMM (task summary) PCA (comparison of users)	Zdravko Georgiev	Tobias Röhm
Romero et al.: Design pattern mining enhanced by machine learning	ICSM, 2005	Machine Learning techniques	Mehdi Foudhaili	Tobias Röhm