SFScon21 - Virgile Prevosto - DECODER Platform to speed up software development, with quality and security
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Thanks to state-of-the-art Artificial Intelligence techniques, IoT and cloud computing projects are now automatically analyzed and documented by DECODER. This is increasing workgroup productivity from software designers to SaaS operators, including testers and maintainers. First external contributions are made possible through the ReachOut platform, where beta-testers can try and run several DECODER software in their own environment.
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SFScon21 - Virgile Prevosto - DECODER Platform to speed up software development, with quality and security
- 1. DEveloper COmpanion for Documented and annotatEd code Reference The DECODER project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824231. DECODER Platform to speed up software development, with quality and security Virgile Prevosto CEA, List SFSCon 2021-11-12
- 2. DEveloper COmpanion for Documented and annotatEd code Reference Project at a glance I https://www.decoder-project.eu/ I Started in January 2019, for 36 months I Provide a unified platform for managing all kinds of information on a given codebase. I Target all stakeholders in software development life cycle: I developers I reviewers I maintainers Methodology Use-cases UX Natural Language Processing Software Engineering Tools Coordination: 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 2
- 3. PKM Architecture Node.js PKM cli PKM over TCP MongoDB driver PKM util PKM core PKM RESTful HTTP server Bash scripts User’s console JS SDK UI and tools over https PKM API I Use docker containers I REST server uses OpenAPI I AGPL and Apache licenses I https://gitlab.ow2. org/decoder/pkm-api 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 3
- 4. PKM tools PKM Decoder Front-end Jupyter Process Engine doc-to-asfm asfm-to-doc Trace recovery tool NER SP SRL Summarization Code repair Variable Misuse JMLGen Frama-C OpenJML Testar Tool Formal Debug 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 4
- 5. Code summarization I Identification of possible variable misuse I Suggestion for code repair 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 5
- 6. Correspondance between natural language and code I Semantic role labeling I Semantic parsing I Traceability matrix 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 6
- 7. Abstract Semi-Formal Models ASFM Language I class diagrams I type/class invariants I state machines description ASFM Tools I doc-to-asfm with user-defined parsers I asfm-to-doc I excavator and Testar can generate ASFM templates I FormalDebug tool 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 7
- 8. Decoder Front-end I browser-based I basic support for the main tools feeding the PKM 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 8
- 9. Decoder Front-end I browser-based I basic support for the main tools feeding the PKM I Traceability matrix 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 8
- 10. Decoder Front-end I browser-based I basic support for the main tools feeding the PKM I Traceability matrix I Jupyter notebook 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 8
- 11. In Practice Use Cases in Decoder I PKM and tools have been assessed on all projects (C, C++, Java) I Development of helper tools I Experiments with doc-to-asfm I First version of datasets for NLP tools extracted Outside of the project beta-campaigns I doc2json I JmlGen 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 9
- 12. Summary Decoder achievements I Robust infrastructure for the PKM I Tools well connected with the PKM I Process Engine for guiding users through their tasks I Powerful UI Future directions I Extend ASFM and related tooling (FormalDebug) I Improve usage of AI-based tools for software analysis I LEIA project 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 10
- 13. Contacts GLOBE https://www.decoder-project.eu/ @ https://www.decoder-project.eu/view/Main/Contacts TWITTER decoderproject LINKEDIN Decoder H2020 Slideshare DecoderProject Acknowledgments The DECODER project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824231. Icons designed by ultimatearm, eucalyp, Freepik, and pixel-perfect from Flaticon 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 11
- 14. Thank You! The DECODER project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 824231. If you need further information, please contact the coordinator: TECHNIKON Forschungs- und Planungsgesellschaft mbH, Burgplatz 3a, 9500 Villach, AUSTRIA, Tel: +43 4242 233 55, Fax: +43 4242 233 55 77, E-Mail: coordination@DECODER.eu The information in this document is provided “as is”, and no guarantee or warranty is given that the information is fit for any particular purpose. The content of this document reflects only the author`s view – the European Commission is not responsible for any use that may be made of the information it contains. The users use the information at their sole risk and liability. 2021 DEveloper COmpanion for Documented and annotatEd code Reference 2021-11-12 12