Dr. Sebastiano Panichella

Sebastiano Panichella is a passionate Computer Science Researcher at Zurich University of Applied Science (ZHAW).

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).

His research interests are in the domain of Software Engineering (SE) and cloud computing (CC): Continuous Delivery, Continuous integration, Software maintenance and evolution (with particular focus on Cloud Applications), Code Review, Mobile Computing, Summarization Techniques for Code, Changes and Testing.

His research is funded by one Swiss National Science Foundation Grant.
For more information have a look on his CV.

Preferred Quotes:
- 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)
-
Major ingredients of successful and timely completion of PhD? Few, but important!
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Last News
  • Paper accepted at EMSE journal (2018): "Redundancy-free Analysis of Multi-revision Software Artifacts"
  • Member of EMSE Review Board
  • Selected as best Reviewer at SANER 2018
  • Paper accepted at SANER 2018: "BECLoMA: Augmenting Stack Traces with User Review Information"
    - Nominated as best tool demo
  • Paper accepted at MaLTeSQuE 2018: "How High Will It Be? Using Machine Learning
    Models to Predict Branch Coverage in Automated Testing"
  • Keynote speaker at VST 2018 (co-located to SANER 2018)
  • Editor of two Special Issues at EMSE and IST journals
  • Paper accepted at SANER 2018: "Exploring the Integration of User Feedback in
    Automated Testing of Android Applications"
    - Nominated as one of the best papers and invited to special issue to EMSE
  • Paper accepted at SANER 2018: "Context Is King: The Developer Perspective on the Usage of Static Analysis Tools"
    - Nominated as one of the best papers and invited to special issue to EMSE
  • PC member of ICSE-SRC 2018, SBST 2018, MSR 2018 and SANER 2018, SBSSE 2018, ICSME 2018, FSE 2018, MASES 2018.
  • ...
  • Project SNF accepted (2016) called " SURF-MobileAppsData "
Address: University of Zurich,
Department of Informatics
Binzmühlestrasse 14
CH-8050 Zurich, Switzerland
Contact Information:
Tel: +41 44 63 545 83
Office: BIN 2.D.03
email: spanichella at gmail.com

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. 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).

His research interests are in the domain of Software Engineering (SE). In particular, during his bachelor, master and doctoral studies, he had the opportunity to explore a wide range of research topics in SE such as IR-based Traceability Recovery, Mining Software Repositories (MSR), Software maintenance and evolution and Empirical Software Engineering. During the experience as postdoc in the SEAL group he investigated further SE research fields such as Mobile Computing, Continuous Delivery and Continuous integration, and the new line of research related to the use of Summarization Techniques for Code, Changes and Testing. He is mainly working on the interesting research problems that are collocated in the intersection of the following SE topics: Continuous Delivery, Continuous integration, Software maintenance and evolution, Mobile Computing, Summarization Techniques for Code, Changes and Testing. Another topic that is also of his interest is Code Review, indeed, he is currently working and advising students on research ideas aimed at automating the process of code inspection.

He is a member of IEEE. He is author or co-author of 44 (considering also demos, datasets and poster) papers appeared in International Conferences and Journals (26 of them published during the experience at the SEAL lab). In summary he published in high-ranked, peer-reviewed (according to the http://www.core.edu.au/conference-portal), and international venues (where he also received best and distinguished paper awards). Specifically, he published, considering the conference venues, 7 papers at ICSE (RANK: A*), 3 at FSE (RANK: A*), 6 at ICSME (RANK: A), 2 at ASE (RANK: A), 1 at GECCO (RANK: A), 7 at SANER, 1 at WCRE (RANK: B), 6 at ICPC (RANK: C). He also published papers at workshop like WAMA (1) and MaLTeSQuE (1). He also published in top journals such as EMSE (3), IST (1), STVR (1) and JSEP (1).

His research is funded by one Swiss National Science Foundation Grant. For more information have a look on his CV.
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Students
He mainly works with:
Andrea Di Sorbo(University of Sannio, PhD student);2015-Today
Carol V. Alexandru(University of Zurich, PhD student, Whiteboard);2015-Today
Adelina Ciurumelea(University of Zurich, PhD student, SURF-MobileAppsData);2016-Today
Giovanni Grano(University of Zurich, PhD student, SURF-MobileAppsData);2017-Today
Carmine Vassallo(University of Zurich, PhD student, SURF-MobileAppsData).2017-Today

Personal Bio:

Professionally, I'm a passionate Computer Science Researcher - My research interests are in the domain of Software Engineering (SE) and cloud computing (CC). You can see more about about my publications, ongoing research projects, and open master/bachelor theses at: https://spanichella.github.io/

On a personal point of view, I like to have a few close and honest (very important and crucial thing for me) friends. There is no life without very good friends. I'm very lucky on this: my brother Annibale and my sister Lucia are also my two best friends. My girlfriend Cristiana completes me in many aspects and I love her with all my heart. I enjoy on a personal level know new people and learn something about their provenance, their culture, their ambitions, etc. I strongly believe that there is always something to learn from others in both personal and professional life.

Education

University of Sannio, Italy

PhD., Computer Engineering

Thesis Title: "Supporting Newcomers in Open Source Software Development Projects"
Thesis Topics: "Supporting Developers, Mining of Software Repositories (Mailing lists, Issue trackers, Versioning Systems etc.)"

July 2014

University of Salerno, Italy

M.S., Computer Science

Thesis Title: Improving IR-based Traceability Recovery Using Smoothing Filters
Magna cum Laude
Adviser: Prof. Andrea De Lucia

December 2010

University of Molise, Italy

B.S., Computer Science,

Thesis Title: Improving IR-based traceability recovery via noun-based indexing of software artifacts
Thesis Topics: Software Engineering, Traceability Management, Natural Lan- guage Processing (NLP)
Magna cum Laude
Advisers: Prof. Giovanni Capobianco, Dr Rocco Oliveto

October 2008

Research Interests

Mining Software Repositories

Software repositories such as source control systems, archived communications between project personnel, and defect tracking systems are used to help manage the progress of software projects. Software practitioners and researchers are recognizing the benefits of mining this information to support the maintenance of software systems, improve software design/reuse, and empirically validate novel ideas and techniques. Research is now proceeding to uncover the ways in which mining these repositories can help to understand software development and software evolution, to support predictions about software development, and to exploit this knowledge concretely in planning future development. The Mining Software Repositories (MSR) field analyzes the rich data available in software repositories to uncover interesting and actionable information about software systems and projects.

Empirical Software Engineering

Empirical software engineering is a sub-domain of software engineering focusing on experiments on software systems (software products, processes, and resources). It is interested in devising experiments on software, in collecting data from these experiments, and in devising laws and theories from this data. Proponents of experimental software engineering advocate that the nature of software is such that we can advance the knowledge on software through experiments only. The scientific method suggests a cycle of observations, laws, and theories to advance science. Empirical software engineering applies this method to software.

Code Review

Peer code review, a manual inspection of source code by developers other than the author, is recognized as a valuable tool for reducing software defects and improving the quality of software projects. In 1976, Fagan formalized a highly structured process for code reviewing, based on line-by-line group reviews, done in extended meetings--code inspections. Over the years, researchers provided evidence on code inspection benefits, especially in terms of defect finding, but the cumbersome, time-consuming, and synchronous nature of this approach hinders its universal adoption in practice. Nowadays, many organizations are adopting more lightweight code review practices to limit the inefficiencies of inspections. In particular, there is a clear trend toward the usage of tools specifically developed to support code review. Modern code reviews are (1) informal (in contrast to Fagan-style), (2) tool-based, and (3) occurs regularly in practice nowadays, for example at companies such as Microsoft, Google, Facebook, and in other companies and OSS projects. The growth in usage of the modern code review process raises many questions. Recently, the research effort has as main focus to find approeaches and tools to improve the code review process. Specifically, develop recommender systems able to (better) support developers during the code review process.

IR-based Traceability Recovery

Traceability has been defined as "the ability to describe and follow the life of an artefact (requirements, code, tests, models, reports, plans, etc.), in both a forwards and backwards direction". Thus, traceability links help software engineers to understand the relationships and dependencies among various software artefacts (requirements, code, tests, models, etc.) developed during the software lifecycle. The two main research topics related to the traceability management are event-based systems for traceability management and information retrieval based methods and tools supporting the software engineer in the traceability link recovery.

Textual analysis

Textual analysis can be described as the examination of a text in which an educated guess is formed as to the most likely interpretations that might be made of that text. It is where the researcher must decentre the text to reconstruct it, working back through the narrative’s mediations of form, appearance, rhetoric, and style to uncover the underlying social and historical processes, the metalanguage that guided the production. It is suggested that textual analysis can cover four main underlying constructs: language and meaning, ideology, ideology and myth, and historicity. In this sense, textual analysis is a methodology: a way of gathering and analysing information in academic research. (Mckee, A 2001)

Machine Learning and Genetic Algorithms

Machine learning and Genetic Algorithms deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning and Genetic algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. Examples of the successful application of machine learning algorithms to SE problems are Bug prediction, Code (and code change) prediction, Cost estimation, Prioritization or clustering of user reviews (in the context of mobile apps), test case generation, etc.

Continuos Delivery

Continuous delivery (CD) is a software engineering approach in which teams produce software in short cycles, ensuring that the software can be reliably released at any time. It aims at building, testing, and releasing software faster and more frequently. The approach helps reduce the cost, time, and risk of delivering changes by allowing for more incremental updates to applications in production. A straightforward and repeatable deployment process is important for continuous delivery. 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. Researchers in this field have as main focus the development of recommender systems able to provide suggestions to developers and testers during Continuous Integration activities.

Open Bachelor- / Master- / PhD- Theses

There are theses available (for both bachelor and master degree) on topics related to his research interests. 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:

1) Mobile and Automated Testing 

2) Machine Learning Applied to Software Engineering

3) Continuos Delivery and Continuos Integration

4) Maintenance, development and testing of Cloud Application

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. 

5) Mining software repositories

- Define a Feedback Mechanisms able 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.

Publications

Bibliometrics:

   
Citations per year
Presentation  - ICSE 2017

 

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2018


Ardoc

[C39] Carol V. Alexandru; José J. Merchante; Sebastiano Panichella; Sebastian Proksch; Harald C. Gall; Gregorio Robles.On the Usage of Pythonic Idioms. Artifacts.  Onward 2018 

 
Ardoc

[J6] Carol Alexandru,Sebastiano Panichella, Sebastian Proksch and Harald GallRedundancy-free Analysis of Multi-revision Software Artifacts.  Empirical Software Engineering Journal. 

 
Ardoc

[C38]  S. Panichella: Summarization Techniques for Code, Change, Testing and User Feedback . In Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018) RANK: B   

 
Ardoc

[C37]  A. Ciurumelea, S. Panichella, H. Gall.: Automated User Reviews Analyser. In Proceedings of the 40th International Conference on Software Engineering (ICSE 2018).  RANK: B.   

Ardoc

[C36]  L. Pelloni, G. Grano, A. Ciurumelea, S. Panichella, F. Palomba, H. Gall.: BECLoMA: Augmenting Stack Traces with User Review Information. Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018) RANK: B.   

Ardoc

[C35] G. Grano, T. Titov, S. Panichella, H. Gall:  How High Will It Be? Using Machine Learning Models to Predict Branch Coverage in Automated Testing. MaLTeSQuE (co-located with SANER 2018)RANK: B.    

Ardoc

[C34]  G. Grano, A. Ciurumelea, S. Panichella, F. Palomba, H. Gall.Exploring the Integration of User Feedback in Automated Testing of Android Applications. Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018) RANK: B. Invited for journal extension   

Ardoc

[C33] C. Vassallo, S. Panichella, F. Palomba, S. Proksch, A. Zaidman and H. Gall Context is King: The Developer Perspective on the Usage of Static Analysis Tools. Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018)RANK: B.Invited for journal extension    

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2017


Ardoc

[C32]  G. Grano, A. Di Sorbo, F. Mercaldo, C. Visaggio, G. Canfora, S. Panichella: Android Apps and User Feedback: a Dataset for Software Evolution and Quality Improvement. Proceedings of the International Workshop on App Market Analytics (WAMA 2017). Pderborn, Germany.  

Ardoc

[C31] C. Vassallo, G. Schermann, F. Zampetti, D. Romano, P. Leitner, A. Zaidman, M. di Penta, S. Panichella: A Tale of CI Build Failures: an Open Source and a Financial Organization Perspective. Proceedings of the 33rd International Conference on Software Maintenance and Evolution (ICSME 2017). Shangai, Asia. RANK: A.   

Ardoc

[C30]Carol Alexandru, Sebastiano Panichella,Harald GallReplicating Parser Behavior using Neural Machine Translation. Proceedings of the 25th International Conference on Program Comprehension (ICPC 2017). Buenos Aires, Argentina. RANK: C.  

Ardoc

[C29] Andrea Di Sorbo, Sebastiano PanichellaCarol Alexandru, Corrado A. Visaggio, Gerardo CanforaHarald GallSURF: Summarizer of User Reviews Feedback. Proceedings of the 39th IEEE International Conference on Software Engineering (ICSE 2017). Buenos Aires, Argentina. RANK: A* 

Ardoc 

[C28] F. Palomba, P. Salza,Adelina Ciurumelea,Sebastiano PanichellaHarald Gall, F. Ferrucci, A. De Lucia:   Recommending and Localizing Change Requests for Mobile Apps based on User Reviews. Proceedings of the 39th IEEE International Conference on Software Engineering (ICSE 2017). Buenos Aires, Argentina. RANK: A* 

Ardoc

[C27] Y. Zhou, R. Gu, T. Chen, Z. Huang, Sebastiano PanichellaHarald GallAnalyzing APIs Documentation and Code to Detect Directive Defects. Proceedings of the 39th IEEE International Conference on Software Engineering (ICSE 2017). Buenos Aires, Argentina. RANK: A* 

Ardoc

[C26] Adelina Ciurumelea, Andreas Schaufelbühl, Sebastiano Panichella and Harald GallAnalyzing Reviews and Code of Mobile Apps for better Release Planning. Proceedings of the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017). Klagenfurt, Austria. RANK: B   

Ardoc

[C25] Carol Alexandru,Sebastiano Panichella and Harald GallReducing Redundancies in Multi-Revision Code Analysis. Proceedings of the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017). Klagenfurt, Austria. RANK: B. Invited for journal extension  

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2016


Ardoc

[C24] Sebastiano Panichella, Andrea Di Sorbo, Emitza Guzman, Corrado Aaron Visaggio, Gerardo Canfora and Harald GallARdoc: App Reviews Development Oriented Classifier. 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2016). Seattle, WA, USA. RANK: A  

ApproachOverview
[C23] Andrea Di Sorbo, Sebastiano Panichella, Carol Alexandru, Junji Shimagaki, Aaron Visaggio, Gerardo Canfora and Harald Gall : What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes. 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2016). Seattle, WA, USA. RANK: A   
ApproachOverview
[C22] Annibale Panichella, Carol Alexandru, Sebastiano Panichella, Alberto Bacchelli, Harald Gall: A Search-based Training Algorithm for Cost-aware Defect Prediction. 25th International Conference on Genetic Algorithms (ICGA) and the 21st Annual Genetic Programming Conference (GP) (GECCO 2016). Denver, Colorado, USA. RANK: A 
ApproachOverview

[C21] Sebastiano Panichella, Annibale Panichella, Mauritz Bella, Andy Zaidman, and Harald Gall: The impact of test case summaries on bug fixing performance: An empirical investigation. In Proceedings of the 38th International Conference on Software Engineering (ICSE 2016), Austin, TX, May 14 - 22, 2016. RANK: A*   

     
howTo

[C20] Andrea Di Sorbo, Sebastiano Panichella, Corrado A. Visaggio, Massimiliano Di Penta, Gerardo Canfora and Harald C. Gall: DECA: Development Emails Content Analyzer. In Proceedings of the 38th International Conference on Software Engineering (ICSE 2016), Austin, TX, May 14 - 22, 2016. RANK: A*  

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2015


resultsSTVR2015

[J5] Gerardo Canfora, Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella e Sebastiano Panichella: Defect Prediction as a Multi-Objective Optimization Problem. Software Testing, Verification and Reliability (STVR 2015).

ApproachOverview

[C19] Sebastiano Panichella: Supporting Newcomers in Software Development Projects In Proceedings of the 31st International Conference on Software Maintenance and Evolution (ICSME 2015), Bremen, Germany, Sep 29 - Oct 1, 2015. RANK: A   

ApproachOverview

[C18] Andrea Di Sorbo, Sebastiano Panichella, Corrado Aaron Visaggio, Massimiliano Di Penta, Gerardo Canfora and Harald Gall: Development Emails Content Analyzer: Intention Mining in Developer Discussions In Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering (ASE 2015), Lincoln, Nebraska, USA, November 9–13, 2015. RANK: A   

ApproachOverview
[C17] Sebastiano Panichella, Andrea Di Sorbo, Emitza Guzman, Corrado Aaron Visaggio, Gerardo Canfora and Harald Gall: How Can I Improve My App? Classifying User Reviews for Software Maintenance and Evolution In Proceedings of the 31st International Conference on Software Maintenance and Evolution (ICSME 2015), Bremen, Germany, Sep 29 - Oct 1, 2015. RANK: A   
ApproachOverview

[C16] Gerald Schermann, Martin Brandtner, Sebastiano Panichella, Philipp Leitner, and Harald Gall: Discovering Loners and Phantoms in Commit and Issue Data.  In Proceedings of the 23rd IEEE International Conference on Program Comprehension (ICPC 2015), Firenze, Italy, May 18th - 19th, 2015. RANK: C 

ApproachOverview

[C15] Sebastiano Panichella, Venera Arnaoudova, Massimiliano Di Penta, Giuliano Antoniol:Would Static Analysis Tools Help Developers with Code Reviews? In Proceedings of the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2015), Montréal, Québec, Canada, May 2nd - 6th, 2015. RANK: B  

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2014


ApproachOverview

[J4] Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta, Rocco Oliveto, Sebastiano Panichella: How the Apache Community Upgrades Dependencies: An Evolutionary Study. Empirical Software Engineering (EMSE 2014). 

ApproachOverview
[C14] Sebastiano Panichella, Gabriele Bavota, Massimiliano Di Penta, Gerardo Canfora, Giulio Antoniol: How Developers' Collaborations Identified from Different Sources Tell us About Code Changes. The 30th International Conference on Software Maintenance and Evolution, Victoria, Canada, 28 September - 3 October 2014. DOI:10.1109/ICSME.2014.47 RANK: A. Nominated for best paper award   
ApproachOverview
[C13] Gabriele Bavota, Sebastiano Panichella, Nikolaos Tsantalis, Massimiliano Di Penta, Rocco Oliveto, Gerardo Canfora: Recommending Refactorings based on Team Co-Maintenance Patterns. The 29th IEEE/ACM International Conference on Automated Software Engineering, Vasteras, Sweden, 15-19 September 2014. RANK: A  
ApproachOverview
[C12] Carmine Vassallo, Sebastiano Panichella, Massimiliano Di Penta, and Gerardo Canfora:CODES: mining sourCe cOde Descriptions from developErs diScussions. The 22nd International Conference on Program Comprehension, Hyderabad, India, 2-3 June 2014. DOI:10.1145/2597008.2597799 RANK: C. Best tool award   
ApproachOverview

[C11] Sebastiano Panichella, Massimiliano Di Penta, and Gerardo Canfora: How the Evolution of Emerging Collaborations Relates to Code Changes: An Empirical Study. The 22nd International Conference on Program Comprehension, Hyderabad, India, 2-3 June 2014. DOI:10.1145/2597008.2597145 RANK: C. Invited for journal extension   

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2013


ApproachOverview
[J3] Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Labeling Source Code with Information Retrieval Methods: An Empirical Study. Empirical Software Engineering (EMSE 2013).
ApproachOverview
[C10] Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta, Rocco Oliveto, Sebastiano Panichella: The Evolution of Project Inter-Dependencies in a Software Ecosystem: the Case of Apache. The 29th IEEE International Conference on Software Maintenance (ICSM 2013), Eindhoven, Netherlands, 22 - 28 September 2013. DOI:10.1109/ICSM.2013.39 RANK: A. Nominated for best paper award  
ApproachOverview
[C9] Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta, Rocco Oliveto, Sebastiano Panichella: An Empirical Investigation on Documentation Usage Patterns in Maintenance Tasks. The 29th IEEE International Conference on Software Maintenance (ICSM 2013), Eindhoven, Netherlands, 22 - 28 September 2013. RANK: A   
ApproachOverview

[C8] Gerardo Canfora, Massimiliano Di Penta, Stefano Giannantonio, Rocco Oliveto, Sebastiano Panichella: YODA: Young and newcOmer Developer Assistant. In Proceedings of the 35th International Conference on Software Engineering (ICSE 2013), San Francisco, CA, May 18th - 26th, 2013. RANK: A*   

ApproachOverview
[C7] Gerardo Canfora, Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella e Sebastiano Panichella: Multi-Objective Cross-Project Defect Prediction. In Proceedings of the Sixth IEEE International Conference on Software Testing, Verification and Validation (ICST 2013), Luxembourg, Belgium, 18-22 March 2013. DOI:10.1109/ICST.2013.38 RANK: C. Invited for journal extension   

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2012


IST2012
[J2] Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Applying a Smoothing Filter to Improve IR-based Traceability Recovery Processes: An Empirical Investigation. Information and Software Technology (IST 2012), pp. 741-754.
ApproachOverview
[J1] Giovanni Capobianco, Andrea De Lucia, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Improving IR-based Traceability Recovery via Noun-based Indexing of Software Artifacts. Journal of Software: Evolution and Process (JSEP 2012),
ApproachOverview
[C6] Gerardo Canfora, Massimiliano Di Penta, Rocco Oliveto, Sebastiano Panichella: Who is going to Mentor Newcomers in Open Source Projects? In Proceedings of the 20th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2012), Cary, North Carolina, USA, 11-16 November 2012. ISBN: 978-1-4503-1614-9. RANK: A   
ApproachOverview
[C5] Sebastiano Panichella, Jairo Aponte, Massimiliano Di Penta, Andrian Marcus, Gerardo Canfora: Mining source code descriptions from developer communications. In Proceedings of; IEEE 20th International Conference on Program Comprehension (ICPC 2012), pages; 63-72, Passau, Germany, June 11-13, 2012. 2012, ISBN 978-1-4673-1216-5. RANK: C   
ApproachOverview
[C4] Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Using IR methods for labeling source code artifacts: Is it worthwhile? In Proceedings of; IEEE 20th International Conference on Program Comprehension (ICPC 2012), pages 193-202, Passau, Germany, June 11-13, 2012. 2012, ISBN 978-1-4673-1216-5. DOI:10.1109/ICPC.2012.6240488 RANK: C. Invited for journal extension    

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2011


ApproachOverview
[C3] Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Improving IR-based Traceability Recovery Using Smoothing Filters. In Proceedings of 19th IEEE International Conference on Program Comprehension (ICPC 2011), pages 21-30. Kingston, ON, Canada, June 22-24, 2011. IEEE Computer Society 2011, ISBN 978-1-61284-308-7. DOI:10.1109/ICPC.2011.34 RANK: C. Best paper award  

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2009


ApproachOverview
[C2] Giovanni Capobianco, Andrea De Lucia, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Traceability Recovery Using Numerical Analysis. In Proceedings of 16th Working Conference on Reverse Engineering (WCRE 2009), pages 195-204, Lille, France, 13-16 October 2009. IEEE Computer Society 2009, ISBN 978-0-7695-3867-9. RANK: B 
   
ApproachOverview
[C1] Giovanni Capobianco, Andrea De Lucia, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: On the role of the nouns in IR-based traceability recovery. In Proceedings of 17th IEEE International Conference on Program Comprehension (ICPC 2009), pages 148-157, Vancouver, British Columbia, Canada, May 17-19, 2009. IEEE Computer Society Press. RANK: C 
   

Professional Services

Keynote Speaker of International Conferences and co-located events:

Keynote speaker at VST 2018 (co-located to SANER 2018)

Editor or Co-editor of special Issues at International Journals:

- Editor of a the special Issue at EMSE entitled "Software Engineering for Mobile Applications"

- Editor of a the special Issue at IST entitled "User Feedback and Software Quality in the Mobile Domain"

Organising research workshops:

Co-organizer of the CHOOSE-forum 2017 (http://www.choose.s-i.ch/events/forum2017/index.html)

Organising committee member of International Conferences:

Program Committee member of the SANER 2019 (IEEE International Conference on Software Analysis, Evolution and Reengineering).

Program Committee member of the 10th Symposium on Search-Based Software Engineering, Montpellier, France.

Program Committee member of  34th International Conference on Software Maintenance and Evolution (ICSME).

Program Committee member of 1st International Workshop on Machine Learning and Software Engineering in Symbiosis.

Program Committee member of  ESEC/FSE 2018 - Formal Demonstration Track.

Program Committee member of SBST 2018 (11th International Workshop on Search-Based Software Testing), Gothenburg, Sweden.

Program Committee member of the 15th Working Conference on Mining Software Repositories (MSR 2018), Gothenburg, Sweden.

Program Committee member of the SANER 2018 (IEEE International Conference on Software Analysis, Evolution and Reengineering), Campobasso, Italy.

Program Committee member of the 40th International Conference on Software Engineering - Student Research Competition (ICSE SRC 2018), Gothenburg, Sweden.

Expert Review Panel Member of the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017), Urbana-Champaign, Illinois, USA.

Program Committee member of the 33rd International Conference on Software Maintenance and Evolution (ICSME Tool Demo Track 2017), Shanghai, China

Program Committee member of the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017 - ERA Track), Klagenfurt, Austria.

Program Committee member of the 25th International Conference on Program Comprehension (ICPC 2017 - NIER Track), Buenos Aires, Argentina.

Program Committee member of the 43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2017), Vienna, 2017.

Program Committee member of the 10th Seminar on Advanced Techniques & Tools for Software Evolution" (SATToSE 2017), Madrid, Spain.

Program Committee member of the 38th International Conference on Software Engineering (ICSE 2016), Austin, TX, May 14 - 22, 2016.

Program Committee member of the 13th International Conference on Mining Software Repositories - Mining Challenge (MSR 2016), Austin, TX, May 14 - 15, 2016.

Program Committee member of the 24th International Conference on Program Comprehension (ICPC 2016 - NIER Track), Austin, TX.

Program Committee member of the 42nd Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2016), Limasol, Cyprus

Program Committee member of the 23rd International Conference on Program Comprehension (ICPC 2015 - NIER Track), Florence, Italy.

Program Committee member of the 41st Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2015), Funchal, Madeira, Portugal.

Program Committee member of the 22nd International Conference on Program Comprehension (ICPC 2014 - NIER Track), Hyderabad, India.

Reviewer for the following International Journals:

- Empirical Software Engineering
- Transactions on Software Engineering
- Transactions on Software Engineering and Methodology
- Journal of Systems and Software
- Information and Software Technology
- Journal of Software: Evolution and Process
- Science of Computer Programming
- Journal of Computer Science and Technology
- Communications of the ACM

Additional reviewer of International Conferences:

31st IEEE/ACM International Conference on Automated Software Engineering (ASE 2016), Singapore, Singapore

30th IEEE/ACM International Conference on Automated Software Engineering (ASE 2015), Lincoln, Nebraska, USA.

22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2015), Montréal, Canada.

Web Chair of International Conferences:

21st International Conference on Program Comprehension (ICPC 2013), San Francisco, California, USA.

Session Chair of International Conferences:

- at the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017 - ERA Track), Klagenfurt, Austria.

- at the MSR 2018 - technical session, entitled "APIs and Code", Gothenburg, Sweden.

Editorial Board Member of International Journals:

Journal of Software: evolution and process

Internship in Canada:

From 27 May 2013 to 27 July 2013 he has been a visiting researcher at the Ecole Polytechnique de Montreal, Canada. Supervisor: Prof. Giuliano Antoniol.

EU projects:

Sebastiano Panichella partially funded with Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta, the EU FP7-ICT-2011-8 project Markos, contract no. 317743. Specifically, the MARKOS project is aimed to realize the prototype of a service and an interactive application providing an integrated view on the Open Source projects available the on web, focusing on functional, structural and licenses aspects of software code. My effort is focused on implementing relevant aspects of the Software System realized by Markos and and a generate new research results in the field of Software Engineering. Particular effort is spent on analysis of source code to study the evolution of software project to automatically extract reusable components from source code. From the other things I also extract licensing statements from the source code to monitor their evolution and avoid that changes in source code also generate the break of licenses.

SNF projects:

Sebastiano Panichella obtained funding for the SURF-MobileAppsData SNF (No. 200021-166275) project. The goal of the SURF-MobileAppsData project is mining mobile apps data available in app stores to support software engineers in better supporting maintenance and evolution activities for these apps.

External Reviewer of Grant Applications:

External Reviewer of projects submitted in the Quebec-Flanders bilateral research cooperation program.

Research Meetings:

Sebastiano Panichella was invited by the National Institute of Informatics (NII), Japan, to participate in NII Shonan Meeting entitled Mobile App Store Analytics (Japan).

Talks Given:

- International Summer School on Software Engineering 2011 How identify Mentors in software projects? Discussion and perspectives July 2011.
- FSE 2012 Who is going to Mentor Newcomers in Open Source Projects?, November 2012.
- ICPC 2012 Mining source code descriptions from developer communications, June 2012.
- ICSE 2013 YODA: Young and newcOmer Developer Assistant, May 2013.
- ICSM 2013 Empirical Investigation on Documentation Usage Patterns in Maintenance Tasks, September.
- CSER 2013 - Concordia University downtown Montral (http://concordia.ca) Supporting Developers, Mining of Software Repositories, June.
- ICPC 2014 How the Evolution of Emerging Collaborations Relates to Code Changes: an Empirical Study, June.
- ICPC 2014 CODES: mining sourCe cOde Descriptions from developErs diScussions, June.
- ICMSE 2014 How Developers Collaborations Identified from Different Sources Tell us About Code Changes, September.
- ASE 2014 Recommending Refactorings based on Team Co-Maintenance Patterns, September.
- SANER 2015 Would Static Analysis Tools Help Developers with Code Reviews? March.
- ICSME 2015 How Can I Improve My App? Classifying User Reviews for Software Maintenance and Evolution, October.
- ICSME 2015 Supporting Newcomers in Software Development Projects, October.
- ASE 2015 Development Emails Content Analyzer: Intention Mining in Developer Discussions, November.
- EOSESE 2015 Textual Analysis or Natural Language Parsing? A Software Engineering Perspective, December.
- "Adesso Quartalsmeeting" - 2016 Summarization Techniques for Code, Changes, and Testing, February.
- Invited by Gran Sasso Science Institute, Center of Advanced Studies - 2016 Systematic Mining of Software Repositories, July.
- ICSE 2016 The Impact of Test Case Summaries on Bug Fixing Performance: An Empirical Investigation, May.
- FSE 2016 ARdoc: App Reviews Development Oriented Classifier, November.
- FSE 2016 What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes, November.
- ICSE 2017 SURF: Summarizer of User Reviews Feedback, May.
- ICSE  2017 Analyzing APIs Documentation and Code to Detect Directive Defects, May.
- VSS  2017  Summarization Techniques for Code, Change, Testing and User Feedback, December.

Grants and EU projects

EU projects:

MARKOS EU project

Sebastiano Panichella was partially funded with Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta, in the EU FP7-ICT-2011-8 project Markos, contract no. 317743. Specifically, the MARKOS project aimed to realize the prototype of a service and an interactive application providing an integrated view on the Open Source projects available the on web, focusing on functional, structural and licenses aspects of software code. My e ort is focused on implementing relevant aspects of the Software System realized by Markos and and a generate new research results in the field of Software Engineering. Particular e ort is spent on analysis of source code to study the evolution of software project to automatically extract reusable components from source code. From the other things I also extract licensing statements from the source code to monitor their evolution and avoid that changes in source code also generate the break of licenses.

SNF projects:

SURF-MobileAppsData SNF project

Sebastiano Panichella obtained funding for the SURF-MobileAppsData SNF (No. 200021_166275) project. The goal of the SURF-MobileAppsData project is mining mobile apps data available in app stores to support software engineers in better supporting maintenance and evolution activities for these apps (Total SNSF (CHF) 349,926).

Link to the project: http://www.ifi.uzh.ch/en/seal/research/projects/SURF-MobileData.html

Teaching duties and Students Advised

Preferred Quotes:

- 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)

Teaching Experience

Courses:

University of Zurich, Switzerland

Lecturer September-December 2017
• Lecturer for the Software Maintenance and Evolution course.
Lecturer March-June 2016
• Lecturer for the Software Maintenance and Evolution course.
Lecturer March-June 2015
• Lecturer for the Software Maintenance and Evolution course.

University of Sannio, Italy
Lab Instructor (December 2013) for the Programming Techniques course of Professor Gerardo Canfora:
• The Languages and Grammars
• JavaCC parser University of Sannio, Italy

Seminaries:
Seminaries in the Software Engineering course of Prof. Massimiliano Di Penta:
• Recovering Traceability Links via Information Retrieval Methods

Seminaries at the Ecole Polytechnique de Montreal:
• Who is going to Mentor Newcomers in Open Source Projects?
• Mining Source Code Descriptions from Developers Communications University of Molise, Italy

Seminary in the Software Engineering course of Dott. Rocco Oliveto: • Improving IR-based Traceability Recovery Using Smoothing Filters.

ADVISED bachelor/master/PhD students:

Giovanni Grano, PhD student at University of Zurich, Switzerland (2017).

- Android Apps and User Feedback: a Dataset for Software Evolution and Quality Improvement  (WAMA 2017)

- Exploring the Integration of User Feedback in Automated Testing of Android Applications  (SANER 2018).

BECLoMA: Augmenting Stack Traces with User Review Information. (SANER 2018).

How High Will It Be? Using Machine Learning Models to Predict Branch Coverage in Automated Testing. MaLTeSQuE 2018

Carmine Vassallo, PhD student at University of Zurich, Switzerland (2017).

- A Tale of CI Build Failures: an Open Source and a Financial Organization Perspective (ICSME 2017)

- Context is King: The Developer Perspective on the Usage of Static Analysis Tools (SANER 2018).

Carol V. Alexandru, PhD student at University of Zurich, Switzerland (2017).

Replicating Parser Behavior using Neural Machine Translation (ICPC 2017).

Reducing Redundancies in Multi-Revision Code Analysis (SANER 2017).

- A Search-based Training Algorithm for Cost-aware Defect Prediction (GECCO 2016).
- What Would Users Change in My App? Summarizing App Reviews for Recom- mending Software Changes (FSE 2016).

- ARdoc: App Reviews Development Oriented Classifier (FSE 2016)

- Exploring Deep Learning Techniques for Supporting the Mining of information in Structured and Unstructured Data.

Adelina Ciurumelea, PhD student at University of Zurich, Switzerland (2016).

- Automated User Reviews Analyser.  (ICSE 2018). 

- Analyzing Reviews and Code of Mobile Apps for better Release Planning (SANER 2017).

- Recommending and Localizing Code Changes for Mobile Apps based on User Reviews (ICSE 2017).

Gerald Schermann, PhD student at University of Zurich, Switzerland.
Discovering Loners and Phantoms in Commit and Issue Data (ICPC 2015).

Andrea Di Sorbo, PhD student at University of Sannio, Italy.
- How Can I Improve My App? Classifying User Reviews for Software Maintenance and Evolution (ICSME 2015).
- Development Emails Content Analyzer: Intention Mining in Developer Discussions (ASE 2015).
- DECA: Development Emails Content Analyzer (ICSE 2016).
- What Would Users Change in My App? Summarizing App Reviews for Recom- mending Software Changes (FSE 2016).

- ARdoc: App Reviews Development Oriented Classifier (FSE 2016)

Timofey Titov, Master student at University of Zurich, Italy.
How High Will It Be? Using Machine Learning Models to Predict Branch Coverage in Automated Testing. MaLTeSQuE 2018

Alessandro Rigamonti, Master student at University of Zurich, Italy.
Develop search-based approaches to better predict change and defect prone classes. Zurich, Switzerland. 2015.

Te Tan, master student at University of Zurich, Switzerland, 2017. 
Advised on a Work on App Store Mining.

Gulshan Kundra, master student at LUT, Finland, 2018

Simon Taennler, master student at University of Zurich, Switzerland, 2017. 

Advised on a Work on App Store Mining.

Farul Acibal, bachelor student at University of Zurich, Switzerland, 2018.

Nik Zaugg, bachelor student at University of Zurich, Switzerland, 2018.

Ivan Taraca, bachelor student at University of Zurich, Switzerland, 2017.

Tool-support for Test Cases Summaries generator and Enhancements. 

Alexander Hofmann, bachelor student at University of Zurich, Switzerland, 2017. ChangeAdvisor - A tool for Recommending and Localizing Change Requests for Mobile Apps based on User Reviews.

Antonio Galluccio, Bachelor student at University of Zurich, Switzerland, 2017.

Toward Generating Test Case Summaries

Lucas Pelloni, Bachelor student at University of Zurich, Switzerland, 2017.

BECLoMA: Augmenting Stack Traces with User Review Information. (SANER 2018).

Andreas Schaufelbuhl, Bachelor student at University of Zurich, Switzerland, 2016.

Analyzing Reviews and Code of Mobile Apps for better Release Planning (SANER 2017).

Carmine Vassallo, Master student at University of Sannio, Italy
"CODES: mining source code descriptions from developers discussions. (ICPC 2014)"

Stefano Giannantonio, Bachelor student at University of Molise, Italy
"YODA: Young and newcOmer Developer Assistant. (ICSE 2013)"

Awards / Best Paper Nominations

Awards as Reviewer:

[1] Distinguished Reviewer Award SANER 2018

[2] Distinguished Reviewer Award SATToSE 2017

Awards/Best Paper Nominations:

[1]     G. Grano, A. Ciurumelea, S. Panichella, F. Palomba, H. Gall.   Exploring the Integration of User Feedback in Automated Testing of Android Applications   Proceedings of the {IEEE} 25th International Conference on Software Analysis, Evolution and Reengineering.  Invited for journal extension  

[2]     C. Vassallo, S. Panichella, F. Palomba, S. Proksch, A. Zaidman and H. Gall.:   Context is King: The Developer Perspective on the Usage of Static Analysis Tools   Proceedings of the {IEEE} 25th International Conference on Software Analysis, Evolution and Reengineering.  Invited for journal extension  

[3]    G. Grano, T. Titov, S. Panichella, H. Gall:  How High Will It Be? Using Machine Learning Models to Predict Branch Coverage in Automated Testing. MaLTeSQuE (co-located with SANER 2018).  Invited for journal extension  

[4] Carol Alexandru,Sebastiano Panichella and Harald GallReducing Redundancies in Multi-Revision Code Analysis. Proceedings of the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017). Klagenfurt, Austria.    Invited for journal extension 

[5] Sebastiano Panichella, Gabriele Bavota, Massimiliano Di Penta, Gerardo Canfora, Giulio Antoniol: How Developers' Collaborations Identified from Different Sources Tell us About Code Changes. The 30th International Conference on Software Maintenance and Evolution, Victoria, Canada, 28 September - 3 October 2014.  Nominated for best paper award   

 [6]  Sebastiano Panichella, Massimiliano Di Penta, and Gerardo Canfora: How the Evolution of Emerging Collaborations Relates to Code Changes: An Empirical Study. The 22nd International Conference on Program Comprehension, Hyderabad, India, 2-3 June 2014. DOI:10.1145/2597008.2597145 Invited for journal extension   

 [7] Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta, Rocco Oliveto, Sebastiano Panichella: The Evolution of Project Inter-Dependencies in a Software Ecosystem: the Case of Apache. The 29th IEEE International Conference on Software Maintenance (ICSM 2013), Eindhoven, Netherlands, 22 - 28 September 2013. DOI:10.1109/ICSM.2013.39 Nominated for best paper award  

 [8] Gerardo Canfora, Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella e Sebastiano Panichella: Multi-Objective Cross-Project Defect Prediction. In Proceedings of the Sixth IEEE International Conference on Software Testing, Verification and Validation (ICST 2013), Luxembourg, Belgium, 18-22 March 2013. DOI:10.1109/ICST.2013.38 Invited for journal extension   

 [9] Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Using IR methods for labeling source code artifacts: Is it worthwhile? In Proceedings of; IEEE 20th International Conference on Program Comprehension (ICPC 2012), pages 193-202, Passau, Germany, June 11-13, 2012. 2012, ISBN 978-1-4673-1216-5. DOI:10.1109/ICPC.2012.6240488 Invited for journal extension     

 [10] Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella: Improving IR-based Traceability Recovery Using Smoothing Filters. In Proceedings of 19th IEEE International Conference on Program Comprehension (ICPC 2011), pages 21-30. Kingston, ON, Canada, June 22-24, 2011. IEEE Computer Society 2011, ISBN 978-1-61284-308-7. DOI:10.1109/ICPC.2011.34 Best paper award  

Best Tool Awards:

[11]  L. Pelloni, G. Grano, A. Ciurumelea, S. Panichella, F. Palomba, H. Gall.: BECLoMA: Augmenting Stack Traces with User Review Information. Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018) RANK: B.  Best tool award

[12] Carmine Vassallo, Sebastiano Panichella, Massimiliano Di Penta, and Gerardo Canfora:CODES: mining sourCe cOde Descriptions from developErs diScussions. The 22nd International Conference on Program Comprehension, Hyderabad, India, 2-3 June 2014. DOI:10.1145/2597008.2597799 Best tool award   

Skills, Competencies gained during the PhD and postdoctoral experience

Statistics:

During the PhD experience, because of his work in \Empirical software engineering", he gained good experience in Statistics (the R environment was the main tool used for such purposes). He widely used several statistical tests (parametric and non) for formulating hypothesis and demonstrating the statistical significance (or superiority) of the proposed techniques.

Main Programming Languages:

He currently uses for his work programming languages like Java (high level), Perl (base level). He is very skilled in scripting languages like R (high level), Matlab (medium level), Weka, RWeka.

Main Competencies Gained:

1) Machine Learning, Text Analysis and Natural Language Processing

He is an expert in Mining of Software repositories and successfully adopted/conceived tools based on Machine Learning (ADTree, Logistic Regression etc.) methods, Natural Language Processing (Stanford NLP parser, Stanford NLP POS Tagger etc.) techniques and Text Analysis (e.g. Vector Space Model, Latent Dirichlet Allocation, Latent Se- mantic Indexing Jensen and Shannon Model etc.) techniques. For example, a specific example of application of such competencies is represented by the implementation of the tool ARdoc (App Reviews Development Oriented Classifier) which is a Java tool that automatically recognizes natural language fragments in user reviews that are rele- vant for developers to evolve their applications. Specifically, natural language fragments are extracted according to a taxonomy of app reviews categories that are relevant to software maintenance and evolution. The categories were defined in our previous paper entitled \How Can I Improve My App? Classifying User Reviews for Software Main- tenance and Evolution" and are: (i) Information Giving, (ii) Information Seeking, (iii) Feature Request and (iv) Problem Discovery. ARdoc implements an approach that merges three techniques: (1) Natural Language Processing, (2) Text Analysis and (3) Sentiment Analysis to automatically classify app reviews into the proposed categories. The purpose of ARdoc is to capture informative user reviews (requesting a new feature, description of a problem, or proposing a solution) and consequently to allow developers to better manage the information contained in user reviews.

2) Genetic Algorithms in SE

His research has yielded approaches to predict future defects in software artifacts based on historical information, thus assisting companies in e ectively allocating limited de- velopment resources and developers in reviewing each others code changes. Developers are unlikely to devote the same effort to inspect each software artifact predicted to contain defects, since the effort varies with the artifacts size (cost) and the number of defects it exhibits (effectiveness). He adopted Genetic Algorithms (GAs) for training prediction models to maximize their cost-effectiveness. The evaluation of the approach was performed on on two well-known models, Regression Tree and Generalized Linear Model, and predict defects between multiple releases of six open source projects. The achieved results show that regression models trained by GAs significantly outperform their traditional counterparts, improving the cost-e ectiveness by up to 240%. Often the top 10% of predicted lines of code contain up to twice as many defects.

3) Social Network Analysis

He is also an expert in Social Network Analysis (SNA) and has successfully used such information for profiling developers/expert in developers' SNA. See for example the pa- pers How the Evolution of Emerging Collaborations Relates to Code Changes: an Em- pirical Study and Who is going to Mentor Newcomers in Open Source Projects? and download the related tool Yoda (Young and newcOmer Developer Assistant) which is an Eclipse plugin (available in http://www.ifi.uzh.ch/seal/people/panichella/tools/YODA- tool.html) able to profile expert in developers' SNA.

4) Other technologies

Other languages that he used during his academic experience are C, C++, Perl, Scilab, Pascal, Visual basic, Prolog, Lisp, PHP, JSP and Servlet. I also have strong experience with scientific software and tools, such as Matlab, R, Weka, that are widely used to build mathematical models through machine learning techniques (including defect pre- diction models). Other technologies and tools that he used during the academic years include SVN/GIT and DBMS, PostgreSQL, Gerrit code review Tool.

He works currently without problem with di erent Operating Systems, like Windows, Mac OS, and Linux (I know very well the Ubuntu distribution).

He is also very familiar with SQL (He currently use for his research work PostgreSQL). He proficiently use GIT/SVN as versioning systems. He also wrote a series of research paper using Latex tool as main reference.