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PROBE - Live Actionable Software Analytics

English title PROBE - Live Actionable Software Analytics
Applicant Lanza Michele
Number 172799
Funding scheme Project funding (Div. I-III)
Research institution Software Institute Facoltà di scienze informatica Università della Svizzera italiana
Institution of higher education Università della Svizzera italiana - USI
Main discipline Information Technology
Start/End 01.10.2017 - 30.09.2021
Approved amount 600'000.00
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Keywords (6)

devops; software analytics; mining software repositories; software evolution; recommendation systems; software visualization

Lay Summary (Italian)

Lead
L'obiettivo di questo progetto di ricerca è di sviluppare una metodologia, complementata da strumenti da implementare, che rendi possible delle analisi approfondite e interattive di sistemi di software che vengono sviluppati seguendo l'approccio "devops", dove i dati collaterali che vengono prodotti durante lo sviluppo vengono ri-immessi nel processo di sviluppo.
Lay summary
L'obiettivo di questo progetto di ricerca è di sviluppare una metodologia, complementata da strumenti da implementare, che rendi possible delle analisi approfondite e interattive di sistemi di software che vengono sviluppati seguendo l'approccio "devops", dove i dati collaterali che vengono prodotti durante lo sviluppo vengono ri-immessi nel processo di sviluppo.
Per raggiungere questo obiettivo, creeremo una piattaforma interattiva basandoci su una rappresentazione tra-dimensionale di sistemi software. 
Direct link to Lay Summary Last update: 07.02.2018

Responsible applicant and co-applicants

Employees

Publications

Publication
A Large-Scale Empirical Study on Code-Comment Inconsistencies
WenFengcai, NagyCsaba, BavotaGabriele, LanzaMichele (2019), A Large-Scale Empirical Study on Code-Comment Inconsistencies, in Proceedings of ICPC 2019 (27th International Conference on Program Comprehension), IEEE CS Press, IEEE Digital Library.
Automatic Identification and Classification of Software Development Video Tutorial Fragments
Ponzanelli Luca, Bavota Gabriele, Mocci Andrea, Oliveto Rocco, Penta Massimiliano Di, Haiduc Sonia, Russo Barbara, Lanza Michele (2019), Automatic Identification and Classification of Software Development Video Tutorial Fragments, in IEEE Transactions on Software Engineering (TSE), 45(5), 464-488.
Characterizing Leveraged Stack Overflow Posts
Geremia Salvatore, Bavota Gabriele, Oliveto Rocco, Lanza Michele, Penta Massimiliano Di (2019), Characterizing Leveraged Stack Overflow Posts, in Proceedings of SCAM 2019 (19th International Working Conference on Source Code Analysis and Manipula, 141-151, IEEE CS Press, IEEE Digital Library141-151.
Data-Driven Solutions to Detect API Compatibility Issues in Android: An Empirical Study
Scalabrino Simone, Bavota Gabriele, Linares-Vasquez Mario, Lanza Michele, Oliveto Rocco (2019), Data-Driven Solutions to Detect API Compatibility Issues in Android: An Empirical Study, in Proceedings of MSR 2019 (16th Working Conference on Mining Software Repositories), 288-298, IEEE CS Press, IEEE Digital Library288-298.
On the Impact of Refactoring Operations on Code Naturalness
Lin Bin, Nagy Csaba, Bavota Gabriele, Lanza Michele (2019), On the Impact of Refactoring Operations on Code Naturalness, in Proceedings of SANER 2019 (26th International Conference on Software Analysis, Evolution, and Reengi, 594-598, IEEE CS Press, IEEE Digital Library594-598.
On The Quality of Identifiers in Test Code
Lin Bin, Nagy Csaba, Bavota Gabriele, Marcus Andrian, Lanza Michele (2019), On The Quality of Identifiers in Test Code, in Proceedings of SCAM 2019 (19th International Working Conference on Source Code Analysis and Manipula, 204-215, IEEE CS Press, IEEE Digital Library204-215.
Pattern-based mining of opinions in Q&A websites
Lin Bin, Zampetti Fiorella, Bavota Gabriele, Penta Massimiliano Di, Lanza Michele (2019), Pattern-based mining of opinions in Q&A websites, in Proceedings of ICSE 2019 (41st International Conference on Software Engineering), 548-559, IEEE CS Press, IEEE Digital Library548-559.
Software Documentation Issues Unveiled
Aghajani Emad, Nagy Csaba, Vega-Márquez Olga Lucero, Vasquez Mario Linares, Moreno Laura, Bavota Gabriele, Lanza Michele (2019), Software Documentation Issues Unveiled, in Proceedings of ICSE 2019 (41st International Conference on Software Engineering), 1199-1210, ACM Press, ACM Digital Library1199-1210.
A Large-scale Empirical Study on Linguistic Antipatterns Affecting APIs
Aghajani Emad, Nagy Csaba, Bavota Gabriele, Lanza Michele (2018), A Large-scale Empirical Study on Linguistic Antipatterns Affecting APIs, in Proceedings of ICSME 2018 (34th International Conference on Software Maintenance and Evolution), 25-35, IEEE CS Press, IEEE Digital Library25-35.
Improving Code: The (Mis)perception of Quality Metrics
Pantiuchina Jevgenija, Lanza Michele, Bavota Gabriele (2018), Improving Code: The (Mis)perception of Quality Metrics, in Proceedings of ICSME 2018 (34th International Conference on Software Maintenance and Evolution), 80-91, IEEE CS Press, IEEE Digital Library80-91.
RETICULA: REal-TIme Code qUaLity Assessment
FrunzioLuigi, LinBin, LanzaMichele, BavotaGabriele (2018), RETICULA: REal-TIme Code qUaLity Assessment, in Proceedings of SANER 2018 (25th International Conference on Software Analysis, Evolution, and Reengi, IEEE CS Press, IEEE Digital Library.
Sentiment Analysis for Software Engineering: How Far Can We Go?
Lin Bin, Zampetti Fiorella, Bavota Gabriele, di Penta Massimiliano, Lanza Michele, Oliveto Rocco (2018), Sentiment Analysis for Software Engineering: How Far Can We Go?, in Proceedings of ICSE 2018 (40th ACM/IEEE International Conference on Software Engineering), 94-104, IEEE CS Press, IEEE Digital Library94-104.
Two Datasets for Sentiment Analysis in Software Engineering
Lin Bin, Zampetti Fiorella, Oliveto Rocco, Penta Massimiliano Di, Lanza Michele, Bavota Gabriele (2018), Two Datasets for Sentiment Analysis in Software Engineering, in Proceedings of ICSME 2018 (26th International Conference on Software Analysis, Evolution, and Reengi, 712-712, IEEE CS Press, IEEE Digital Library712-712.
An Annotation-based API for Supporting Runtime Code Annotation Reading
Lima Phyllipe, Guerra Eduardo, Nardes Marco, Mocci Andrea, Bavota Gabriele, Lanza Michele (2017), An Annotation-based API for Supporting Runtime Code Annotation Reading, in Proceedings of META 2017 (2nd International Workshop on Meta-Programming Techniques and Reflection), 6-14, ACM Press, ACM Digital Library6-14.
Investigating the Use of Code Analysis and NLP to Promote a Consistent Usage of Identifiers
Lin Bin, Scalabrino Simone, Mocci Andrea, Oliveto Rocco, Bavota Gabriele, Lanza Michele (2017), Investigating the Use of Code Analysis and NLP to Promote a Consistent Usage of Identifiers, in Proceedings of SCAM 2017 (17th International Working Conference on Source Code Analysis and Manipula, 81-90, IEEE CS Press, IEEE Digital Library81-90.
Mining Structured Data in Natural Language Artifacts with Island Parsing
Bacchelli Alberto, Cleve Anthony, Mocci Andrea, Lanza Michele (2017), Mining Structured Data in Natural Language Artifacts with Island Parsing, in Science of Computer Programming (SCP), 150, 31-55.
On-Demand Developer Documentation
Robillard Martin, Marcus Andrian, Treude Christoph, Bavota Gabriele, Chaparro Oscar, Ernst Neil, Gerosa Marco, Godfrey Michael, Lanza Michele, Linares-Vasquez Mario, Murphy Gail, Moreno Laura, Shepherd David, Wong Edmund (2017), On-Demand Developer Documentation, in Proceedings of ICSME 2017 (33rd International Conference on Software Maintenance and Evolution), 479-483, IEEE CS Press, IEEE Digital Library479-483.

Collaboration

Group / person Country
Types of collaboration
University of Zurich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
University of Los Andes Colombia (South America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
University of Bozen-Bolzano Italy (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
University of Molise Italy (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
University of Basilicata Italy (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
Colorado State University United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
University of Namur Belgium (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
University of Sannio Italy (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
University of Texas at Dallas United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure

Scientific events



Self-organised

Title Date Place
DysDoc 6 - 6th International Workshop on Software Documentation 07.02.2020 McGill Bellairs Research Institute, Barbados
SIESTA 2019 - 2nd International Summer School on Software Engineering 03.09.2019 Termoli, Italy
DysDoc5 - 5th International Workshop on Software Documentation 16.06.2019 Okinawa, Japan
DysDoc 4 - 4th International Workshop on Software Documentation 02.02.2019 McGill University Bellairs Research Institute, Barbados
DysDoc 3 - 3rd International Workshop on Software Documentation 14.09.2018 Madrid, Spain
SIESTA 2018 - 1st International Summer School on Software Engineering 10.09.2018 Lugano, Switzerland
CHOOSE Forum 2017 17.11.2017 Zurich, Switzerland

Knowledge transfer events



Self-organised

Title Date Place
USI Hackathon 2019 16.11.2019 Lugano, Switzerland

Awards

Title Year
ACM SIGSOFT Distinguished Paper Award (for the paper "Data-Driven Solutions to Detect API Compatibility Issues in Android: An Empirical Study") 2019

Associated projects

Number Title Start Funding scheme
146734 HI-SEA - Holistic Immersive Software Evolution Ambient 01.04.2013 Project funding (Div. I-III)

Abstract

Software analytics has grown in the past years out of the software analysis and program comprehension areas into a full-fledged, self-contained, and established research field of its own. The central underlying idea is to reflect on the plethora of data generated while software systems are being developed. This data resides for example in versioning system repositories, bug trackers, code review systems, mailing lists, etc., and is also available as online resources, e.g., Q&A websites and online video tutorials.Research has shown that this data, if correctly leveraged, can be transformed into precious knowledge that can inform decisions about the evolution of a system. However, many research results, while inter- esting, have a hard time being actionable, i.e., useful and usable suggestions with immediate and concrete impact on the system. We believe this is due to the fact that each data source provides a limited and in- complete perspective on any given development task. What is missing is a holistic take, which is only possible when diverse data sources are integrated and made accessible to software developers. Moreover, the obtained insights and the concrete consequences of those insights are disconnected.Our goal is to develop a comprehensive methodology, complemented by appropriate tool support, to enable visual and live software analytics, where the plethora of data produced in the context of any software project is integrated in a holistic fashion and is therefore elevated to the state of knowledge, which can then be made actionable by directly feeding back into the software development process.To attain that goal, we envision the creation of a web-based immersive analytics environment, featuring a 3D representation of the software system under development. In this environment, the developer is represented by an avatar, a virtual persona about which the environment keeps track in terms of the past and current actions and achievements. The system depiction is augmented with what we define as corollary knowledge, harvested (i.e., extracted, modeled, and integrated) from the aforementioned data sources. This corollary knowledge is then proposed on-the-fly by the environment which has at its disposal integrated knowledge about the system and an understanding of the developer’s context. With that understanding, the environment can suggest pertinent knowledge, by visually super-imposing it over the actual depiction of the system. The developer can interact with those knowledge bits and render them actionable, by consulting them, by linking them to the code base, and/or by diving into them. Moreover, the developer can also interact with other developers in the thus created immersive virtual space.
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