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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

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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