Sebastiano Panichella, Dr.

  Senior Research Associate
Address:
University of Zurich
Department of Informatics
Binzmühlestrasse 14
CH-8050 Zurich, Switzerland
Contact Information:
Email panichella@ifi.uzh.ch
Tel: +41 44 63 545 83
Office BIN 2.D.03

Biographical Sketch

Sebastiano Panichella was born in Isernia (Italy), he received (cum laude) the Laurea in Computer Science from the University of Salerno (Italy) in 2010 defending a thesis on IR-based Traceability Recovery, advised by Prof. Andrea De Lucia.

He received the PhD in Computer Science from the University of Sannio (Department of Engineering) in 2014 defending the thesis entitled ''Supporting Newcomers in Open Source Software Development Projects'' (PDF) .

Currently he is a Research Associate at University of Zurich working in the Software Evolution and Architecture Lab of Prof. Harald Gall. He is a member of IEEE. His research interests include Mining Software Repositories, Code Review, IR-based Traceability Recovery, Machine Learning (applied to SE problems), Textual Analysis, Software maintenance and evolution and Empirical Software Engineering. For more information have a look on his CV (PDF, 154 KB).

His research is funded by two Swiss National Science Foundation Grants

Students

He mainly works with
- Carol V. Alexandru (University of Zurich, PhD student, Whiteboard)
- Adelina Ciurumelea (University of Zurich, PhD student, SURF-MobileAppsData)
- Andrea Di Sorbo (University of Sannio, PhD student)

Open Bachelor and Master's Theses

He mainly advises theses in the area of Mining Software Repositories. There are theses available (for both bachelor and master degree) on topics related to his research activities. It is suggested to contact him directly (by e-mail), or, if you want, to have a look at his recent publications on the various topics. In particular, there are available theses on the following topics:

Mining software repositories

- Define Feedback a Mechanisms able for mining user reviews of mobile App: designing and developing tools to help developers digest the huge amount of feedback they receive from users on a daily basis, transforming user reviews into maintenance tasks (fixing issues or building features). For more information read the recent papers accepted "How Can I Improve My App? Classifying User Reviews for Software Maintenance and Evolution", "What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes" and the related tools called ARdoc and SURF.

- Develop recommender systems able to (better) support developers during the code review process. For more information read the recent paper accepted "Would Static Analysis Tools Help Developers with Code Reviews?".

- Development recommender systems based on Source Code Summarization and Code Change Summarization techniques able to support developers during development or maintenance activities. For more information read the recent paper accepted at ICSE 2016 entitled "The impact of test case summaries on bug fixing performance: An empirical investigation". The slides of my lecture of the course Software Maintenance and Evolution describe the concepts of Source Code Summarization and Code Change Summarization.

- Develop search-based approaches to better predict change and defect prone classes. For more information read the recent paper accepted at GECCO 2016 entitled "A Search-based Training Algorithm for Cost-aware Defect Prediction".

- Automatic redocumentation of existing systems by mining software repositories. For more information have a look at the papers accepted "Mining source code descriptions from developer communications" and "CODES: mining sourCe cOde Descriptions from developErs diScussions".

- Automatic identification of skills and teamwork in software projects by mining software repositories For more information have a look at the paper accepted "Supporting Newcomers in Software Development Projects and the list of recent publications.

- Development of recommender systems, i.e., of systems able to provide suggestions to developers and managers during development or maintenance activities. For more information have a look at the paper accepted "Development Emails Content Analyzer: Intention Mining in Developer Discussions and the related tool called DECA.

LAST NEWS

Paper accepted at FSE 2016: "ARdoc: App Reviews Development Oriented Classifier"

Paper accepted at FSE 2016: "What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes"

Project SNF accepted (2016) called " SURF-MobileAppsData "

Paper accepted at GECCO 2016: " A Search-based Training Algorithm for Cost-aware Defect Prediction"

Paper accepted at ICSE 2016: "The impact of test case summaries on bug fixing performance: An empirical investigation"

Paper (Demonstrations Track) accepted at ICSE 2016: "DECA: Development Emails Content Analyzer"

Paper accepted at ASE 2015: "Development Emails Content Analyzer: Intention Mining in Developer Discussions"

Paper accepted at ICSME 2015: "Supporting Newcomers in Software Development Projects"

Paper accepted at ICSME 2015: "How Can I Improve My App? Classifying User Reviews for Software Maintenance and Evolution"

Paper accepted at ICPC 2015: "Discovering Loners and Phantoms in Commit and Issue Data"

Paper accepted at SANER 2015: "Would Static Analysis Tools Help Developers with Code Reviews?"

Paper accepted at STVR 2015: " Defect Prediction as a Multi-Objective Optimization Problem"

Paper accepted at ICSME 2014: "How Developers' Collaborations Identified from Different Sources Tell us About Code Changes"

BEST TOOL AWARD, ICPC 2014: "CODES: mining sourCe cOde Descriptions from developErs diScussions"