Software Analytics
Led by Diomidis Spinellis and Georgios Gousios
How can we harness the massive data modern development and deployment processes generate, as well as Big Code, to increase development productivity and operational efficiency?
Introduction
Modern software projects are more than just the code that comprises them: teams follow specific development processes; the code runs on servers or mobile phones and produces runtime logs; users talk about the software in forums like StackOverflow and GitHub and rate the product in app stores. The software is part of a collection of similar applications and depends on external code or service API’s to deliver its functionality. Modern software teams need data to make informed decisions that enable continuous, feedback-driven improvement.
At the Software Analytics lab, we work to make software analytics a core asset for software development teams. Our research touches topics such as computer-supported collaborative work (CSCW), big data systems, software engineering processes, software reliability, software analysis, machine learning, and data science.
Currently, we focus on the following 2 research lines, even though we are always open to new ideas:
-
Engineering for (software) analytics: creating platforms for data ingestion, integration and querying in a streaming fashion. Related projects:
- AI4Fintech Making large software-based organizations more efficient.
- Codefeedr A platform to ingest and process software analytics data in a streaming fashion
- GHTorrent Collects all data from the GitHub event API
-
Software ecosystems: We build ecosystem-wide, versioned call graphs out of package networks to make studies such as precise security vulnerability tracking, software license tracking, data-based API evolution, etc possible.
- FASTEN A platform for analyzing dependency management services at the call graph level granularity
Researchers
(Some) Members of the Software Analytics Lab in May 2020. Left to right: Elvan Kula, Georgios Gousios, Maliheh Izadi, Mehdi Keshani, Amir Mir, Joseph Hejderup
The following people are part of the Software Analytics lab:
- Diomidis Spinellis (Lab leader)
- Arie van Deursen (Leader of the Software Engineering group)
-
Georgios Gousios (Lab co-leader)
- Joseph Hejderup (PhD student) working on ecosystem analysis/tics
- Mehdi Keshani (PhD student), working on scaling static analyses
- Elvan Kula (PhD student, also with ING), working on analytics for software process optimization
- Chandra Maddila (PhD student, also with Microsoft), working on tools for software engineering
- Amir Mir (PhD student), working on making Python better through Machine Learning
Collaborators
The lab collaborates with the following organizations:
Student collaborators
SAL is always open to hosting brilliant MSc/BSc students to work on the exiting topics we offer.
Alumni
The following people were part of the Software Analytics lab:
- Ayushi Rastogi (Postdoc, now assist prof at U Groningen)
- Enrique Larios (Postdoc, now postdoc at U Vic)
- Chushu Gao (visitor, now at SIG)
- Moritz Beller (Postdoc, now at Facebook)
- Maria Kechagia (Postdoc, now at UCL)
- Maliheh Izadi (visitor from Sharif University of Technology, now postdoc at SERG)
-
Xunhui Zhang (visitor from NUDT, China)
- Ilya Grishkov (BSc student). Worked on FASTEN.
- Wouter Zorgdrager (MSc student). Worked on FASTEN, system administration
- Roberta Gismondi (BSc student). Worked on ML-based auto-completion for Python
- Evaldas Latoškinas (BSc student). Worked on type prediction for Python
- Mihhail Sokolov (BSc student). Worked on FASTEN
- Edoardo Lanzini (BSc student). Worked on FASTEN
- Konstantinos Triantafyllou (MSc intern from ETH Zürich). Worked on call graph generator for Rust
Funding
The Software Analytics Lab has received funding from:
- NWO
- European Commission
- Microsoft
- ING
