||Senior Research Associate
University of Zurich
Department of Informatics
CH-8050 Zurich, Switzerland
Tel: +41 44 63 545 83
Office BIN 2.D.03
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, Continuous Delivery (with special attention to Continuos Integration Problems), Software maintenance and evolution and Empirical Software Engineering. For more information have a look on his CV ( )
His research is funded by two Swiss National Science Foundation Grants
- I never teach my pupils. I only attempt to provide the conditions in which they can learn. (Albert Einstein)
- You cannot teach a man anything; you can only help him find it within himself. (Galileo Galilei)
- Carmine Vassallo (University of Zurich, PhD student, SURF-MobileAppsData);
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:
Continuos Delivery and Continuos Integration
Continuous Integration (CI) consists in a specific stage of CD process where team members integrate their work in an automatic manner, which allows a fast building, testing, and releasing of software, leading to multiple integrations per day. A thesis in this topic will have as main focus the development of recommender systems able to provide suggestions to developers and testers during Continuous Integration activities.
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", "Analyzing Reviews and Code of Mobile Apps for better Release Planning", "Recommending and Localizing Change Requests for Mobile Apps based on User Reviews" 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", "Analyzing APIs Documentation and Code to Detect Directive Defects" and the related tool called DECA.
Paper accepted at ICPC 2017: "Replicating Parser Behavior using Neural Machine Translation"
Paper accepted at ICSE 2017: "Recommending and Localizing Change Requests for Mobile Apps based on User Reviews"
Paper accepted at ICSE 2017: "Analyzing APIs Documentation and Code to Detect Directive Defects"
Paper accepted at ICSE 2017: "SURF: Summarizer of User Reviews Feedback"
Paper accepted at SANER 2017: "Reducing Redundancies in Multi-Revision Code Analysis"
Paper accepted at SANER 2017: "Analyzing Reviews and Code of Mobile Apps for better Release Planning"
Expert Review Panel Member of ASE 2017
Editorial Board Member of Journal of Software: evolution and process (period 2017-2019)
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"