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Supersede overview presentation

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The SUPERSEDE project will provide advancements in several research areas, from end-user feedback and contextual data analysis, to decision making support in software evolution and adaptation. But the major novel contribution will be in integrating methods and tools from the mentioned areas, thus providing a new solution framework for software evolution and adaptation for data-intensive applications.

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Supersede overview presentation

  1. 1. The SUPERSEDE project
  2. 2. 2 For who is SUPERSEDE: • For Software developers who want to increase the acceptance of their software. What is SUPERSEDE: • The SUPERSEDE toolset helps you, as developer, to make the best decision to improve your software product. Why is SUPERSEDE is unique: • Unlike other toolkits, SUPERSEDE adopts a feedback-driven software engineering perspective thus helping software developers understand the evolving user's needs. SUPERSEDE Who, What and Why
  3. 3. 3 • An HORIZON 2020 project • Call: H2020-ICT-2014-1 (Tools and methods for Software Development) • Title: SUpporting evolution and adaptation of PERsonalized Software by Exploiting contextual Data and End-user feedback • Started on: May 1, 2015 (Duration: 36 months) • Type of Action: RIA - to establish new knowledge and/or to explore the feasibility of a new or improved technology, product, process, service or solution - basic and applied research, technology development and integration, testing and validation on a small-scale prototype in a laboratory or simulated environment • Consortium: 8 Partners (4 Academic/Research; 4 Industrial) SUPERSEDE project details
  4. 4. 4 • Context & Vision • Project Objective • Approach • Knowledge areas & their challenges • Use Case iterative validation • Expected Impact • Consortium Outline
  5. 5. 5 Context Big data • Networked smart objects (e.g. smart shoes that monitor your practice), smart appliances (e.g. energy metering and app to help reducing consumption) … smart city services (healthcare, transportation, e-government,…) become available at increasing speed • These software applications exploits contextual data collected at runtime through various sensors and online data sources • Logs on their usage produce additional data Online End-users feedback • Users express their feedback upon their experience in using a software application through online forums, app stores, social networks, or customized user feedback platforms, accessible on the go • Feedback can be in the form of ratings, emoticons, textual comments … multi-modal, e.g. written text + voice or images or emoticons iRequire [SeyffEtal.RE’10 http://myexperience.sourceforge.net
  6. 6. 6 • Can we exploit feedback from end-user and big data to support the development of better quality services and applications? • … and to accelerate their evolution life-cycle, independently of the size of the software company? • For examples, enabling: • continuous validation of requirements • continuous improvement of service qualities (integrity, robustness, …) • continuous evolution and dynamic reconfiguration • semi-automatic identification of business use cases • tool-supported prioritization for release planning • … Context: Challenges
  7. 7. 7 Vision 1) Collect: gathering of data both from the end-user, the execution context, usage logs 2) Analyse: reasoning about the collected data • e.g. extracting user intentions from their textual comments; automatically generating user models from patterns of usage; derive indicators for QoS compliance / QoE 3) Decide: derive appropriate decision-making models that can be fed by user feedback and big data to enable automated and semi-automated decision-making • software evolution tasks, for instance: identifying new requirements; identifying issues to be solved through software maintenance or evolution; etc. • software dynamic adaptation, e.g. getting recommendations about actions to be implemented to keep QoS and QoE at a good level 4) Act: implementing the decided changes at the right moment, i.e. schedule & assess the impact of the executed actions Adopt a feedback-driven software engineering perspective
  8. 8. 8 Vision • for better software applications - context-awareness, personalization (improve QoE) Ø End-user • for software engineering - better quality decisions in evolving software application and services (improve resource management; artifacts coherence; final product’s quality) - Integrated and extended mechanisms for a more situated run-time dynamic adaptation ØSoftware engineer For what? For whom?
  9. 9. 9 The Objective • The overall objective of the SUPERSEDE project is to provide methods and tools to support decision-making in the evolution and adaptation of software services and applications by exploiting end-user feedback and big data
  10. 10. 10 • provide methods & tools to collect end-users’ feedback and context / usage data which will be efficient, scalable and adaptable • provide methods & tools to perform an integrated analysis of the collected data • provide methods & tools to support decision-making in the evolution and runtime adaptation of services and applications based on user’s feedback and contextual data • provide methods and tools to enact the decisions made together with means to assess the impact of these decisions both in terms of users’ quality of experience and organization productivity Approach: 4 main sub-objectives
  11. 11. 11 Approach: 7 Knowledge areas
  12. 12. 12 • Area 1: Feedback Gathering • Multimodal feedback communication channels • User engagement mechanisms • Area 2: Run-time monitoring • comprehensive monitoring solution • mechanisms to ensure the correctness of the collected data • Area 3: User-Feedback Analysis • combining opinion mining and conversation analysis approaches • Area 4: Big data analysis • Integration of heterogeneous sources • Data changes/evolution • Area 5: Software Quality • Framework that integrates QoE and QoS • Area 6: Decision-making support • Models for decision-making (integrating data analytics/ end-user feedback) – customizable to specific domain settings • Area 7: Run-time Adaptation & Personalisation • Scalable solutions – customizable to specific domain settings Research challenges All the 7 research areas have their own research agendas, communities, and open challenges SUPERSEDE will focus on a subset, including the following:
  13. 13. 13 Three use cases proposed by companies will ensure: • the elicitation of relevant domain knowledge • a progressive validation of the methods and tools produced to ultimately provide evidence of potential for productivity gains Approach: Use Cases Demo Apps City Info API: Management and Operation SMART CITY INFORMATION API PLATFORM - SIEMENS •Smart City Information API provision and consumption •Ecosystem for Smart City Information exchange •Advanced Smart City Apps and Services for energy providers, grid operators and citizens •Runtime monitoring of platform •API access patterns and KPIs Interactive Energy Savings Account - SeEnerCON •SENERCON (software developer, management) Home Energy Efficiency - Energy evaluation application (https://www.energiesparkonto.de) SMART PLAYER Sport Media Application in Real Time - ATOS •Webscasting Media platform for large sport events •Sports Event Live •Allows people to watch sport videos on demand •Application in Real Time •Give stats with: live results and sport info •Multi-audio in different languages
  14. 14. 14 Expected Impact • Foster the use of inputs from end-users • users will feed the team developing software • Allow to collect feedback along the software lifecycle • Get support from monitor, listen and communicate with users • Foster runtime adaptation capacity and dynamic personalisation • Accelerate software life-cycle dynamic development process • Foster the design of applications to fulfill users’ needs (QoE) and expectations
  15. 15. 15 Consortium

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