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Hamburg Requirements Engineering Symposium

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An introduction of the SUPERSEDE solution.

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Hamburg Requirements Engineering Symposium

  1. 1. Anna Perini – Project coordinator FBK, Center for Information and Communication Technology – ICT Trento (Italy) Software Engineering Unit http://se.fbk.eu Data-driven software evolution The SUPERSEDE way Hamburg Requirements Engineering Symposium Wednesday, May 23rd, 2018
  2. 2. 2 • SUpporting evolution and adaptation of PERsonalized Software by Exploiting contextual Data and End-user feedback • An European funded project (HORIZON 2020 framework, RIA) • Call: H2020-ICT-2014-1 (Tools and methods for Software Development) • Started May 1, 2015 (3 Years) <- JUST ended! What is SUPERSEDE? • Consortium: 4 Academic/Research and 4 Industrial partners
  3. 3. 3 • Software at use … Software applications and services increasingly exploit and generate data – sensors embedded in the environment – online data sources – users’ feedback Motivations: Observed trends … • Software development - The “move fast” trend: Agile approaches - Quality & Efficiency: • software product quality matters more and more • taking care of changing/evolving customers' needs
  4. 4. 4 • Multi-modal feedback / monitoring • Feedback analysis / Data analytics • Automated reasoning at support of decision making in software development Motivations: Candidate solutions from research
  5. 5. 5 Objective & Approach Enable a data-driven engineering process • collect end-users’ feedback and runtime data in an efficient, scalable and adaptable way • perform an integrated analysis of the collected data for evolution and adaptation decision-making • support decision-making in the evolution and runtime adaptation of services and applications based on user’s feedback and contextual data • enact the decisions made
  6. 6. 6 ü The SUPERSEDE project • Facts – Motivations – Vision – Objective – Approach • Results at Y3 • Glimpse on main achievements • Illustrating the Data-Driven Software Evolution – the ATOS’s UC • Conclusion Outline
  7. 7. 7 Main Achievements SUPERSEDE solutions • Development of software tools - available for download at https://github.com/supersede-project
  8. 8. 8 The ATOS Smart Player •Webcasting Media platform for large sport events •Allows people to watch sport videos on demand, in real time •Give stats with: live results and sport info
  9. 9. 9 The ATOS Smart Player REFERENCES M. Stade, F. Fotrousi, N. Seyff, O. Albrecht (2017). Feedback Gathering from an Industrial Point of View. 25th IEEE International Requirements Engineering Conference (RE’17) pp. 71-79.
  10. 10. 10 Big Data architecture REFERENCES S. Nadal, V. Herrero, O. Romero, A. Abelló, X. Franch, S. Vansummeren, & D. Valerio (2017). A Software Reference Architecture for Semantic-Aware Big Data Systems. Information and Software Technology.
  11. 11. 11 • Results: - Found association between types of speech acts (e.g. Informative, Responsive, Requestive, etc.) and type of issues (e.g. Enhancement, Defect) - Distribution of speech acts for the first ten comments for Defect and Enhancement, and identified common patterns Textual feedback classification Speech-act & sentiment analysis Textual online discussion • Techniques: - NLP techniques for pre-processing - speech acts and the sentiment as parameters for training three machine learning algorithms (Random Forest, J48 and SMO) classify comments into Enhancement, Feature and Defect REFERENCES Moralez-Ramirez, Kifetew, Perini, CAISE 17 Analysis of Online Discussions in Support of Requirements Discovery
  12. 12. 12 ECA rule If the we receive more than N (e.g. N=2) feedbacks in the window’s time frame an alert is raised for decision
  13. 13. 13 Rule 1 (R1): “Two or more negative feedbacks in 5 min” Sliding Window R1“I don’t like Y”“I don’t like X” Big-data platform & Analytics Running example
  14. 14. 14 SUPERSEDE at Y3 Decision-Making and release planning as JIRA plug-in Alerts are sent to JIRA * *https://www.atlassian.com/software/jira demo video at: https://www.supersede.eu/do wnloads/other-publications/
  15. 15. 15 Analysing SUPERSEDE Alerts in JIRA
  16. 16. 16 Prioritising Requirements with DMGame as JIRA plug-in
  17. 17. Requirements lifecycle in SUPERSEDE Existing requirements • ASP-1 Deployment configuration • ASP-2 Connection issues • ASP-3 Infra not 100 percent redundant • ASP-4 Fail over • ASP-5 Insufficient security level • ASP-6 Insufficient Monitoring • ASP-7 Third party integration • ASP-8 Advertising needs to be monitored • ASP-9 Convert xml to jsons • ASP-10 Plan to port the App from Flash to HTML5 • ASP-11 Design a new Menu Requirements after the alerts • ASP-1 Deployment configuration • ASP-2 Connection issues • ASP-3 Infra not 100 percent redundant • ASP-4 Fail over • ASP-5 Insufficient security level • ASP-6 Insufficient Monitoring • ASP-7 Third party integration • ASP-8 Advertising needs to be monitored • ASP-9 Convert xml to jsons • ASP-10 Plan to port the App from Flash to HTML5 • ASP-11 Design a new Menu • ASP-16 Add support for Chrome Prioritized requirements • ASP-4 Fail over • ASP-11 Design a new Menu • ASP-10 Plan to port the App from Flash to HTML5 • ASP-16 Add support for Chrome • ASP-2 Connection issues • ASP-6 Insufficient Monitoring • ASP-1 Deployment configuration • ASP-9 Convert xml to jsons • ASP-5 Insufficient security level • ASP-3 Infra not 100 percent redundant • ASP-7 Third party integration • ASP-8 Advertising needs to be monitored
  18. 18. Release planning with REPlan as JIRA plug-in 18
  19. 19. 19 What’s behind DMGame • Automated reasoning: • Analytic Hierarchy Process (AHP) method that was selected because its pairwise comparison mechanism allows us to perform a fine-grained analysis of the motivations that lead to a resulting ranking, thus exploiting at best the different skills and expertise of the decision makers • Genetic Algorithms (GA) because it allows to overcome some of the limitations of AHP, at the cost of a reduced granularity of the ranking • Gamification • To foster user engagement, game elements are included, such as: - Progress, that is user completion rate is reported to each user - Time Pressure, that is the process has a fixed duration, and actions done after the process expiration are discarder; - Pointsification, that is a point attribution mechanism has been designed, with the purpose of providing an incentive to (i) perform the voting task quickly, and (ii) perform an accurate REFERENCES F. Kifetew, D. Munante, A. Perini, A. Susi, A. Siena, P. Busetta D. Valerio, Gamifying Collaborative Prioritization: Does Pointsification Work?, RE’17 I. Morales-Ramirez, D. Munante, F. Kifetew, A. Perini, A. Susi and A. Siena. Exploiting User Feedback in Tool-supported Multi-criteria Requirements Prioritization. RE’17.
  20. 20. 20 What’s behind REPlan • RePlan Optimizer uses optimization algorithms from the JMetal library REFERENCES D. Ameller, C. Farré, X. Franch, D. Valerio, A. Cassarino, and V. Elvassore, “Replan: a Release Planning Tool,” in 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER), 2017. D. Ameller, C. Farré, X. Franch, D. Valerio, and A. Cassarino, “Towards Continuous Software Release Planning,” in 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER), 2017.
  21. 21. 21 How to use the SUPERSEDE tool-suite? A tool supported Methodology • Situational Method Engineering to describe SUPERSEDE and guide its tailoring to a particular context • A catalogue of method chunks • A process for their selection and assembly • https://www.supersede.eu/method-explorer/#!/overview REFERENCES X. Franch, J.Ralyté,A. Perini, A. Abelló, D. Ameller, J. Gorroñogoitia, S. Nadal, M. Oriol, N.Seyff, A. Siena, A. Susi, A Situational Approach for the Definition and Tailoring of a Data-Driven Software Evolution Method, CAISE 2018. .
  22. 22. 22 Conclusion 6 Objective & Approach Support a data-driven engineering process •  collect end-users’ feedback and runtime data in an efficient, scalable and adaptable way •  perform an integrated analysis of the collected data for evolution and adaptation decision- making •  support decision-making in the evolution and runtime adaptation of services and applications based on user’s feedback and contextual data •  enact the decisions made 12 The ATOS Smart Player • A tool chain for supporting data-driven software evolution • available for download at https://github.com/supersede-project • SUPERSEDE’s solutions integrated into the JIRA© issue tracking system • demo software evolution SUPERSEDE-JIRA at: https://www.supersede.eu/downloads/other-publications/ • A tool-supported methodology: • https://www.supersede.eu/method-explorer/#!/overview • Scientific publications: https://www.supersede.eu/scientific-publications/ • Please contact us if you are interested to use the SUPERSEDE tools
  23. 23. Thank you for your attention Questions?

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