___

• [1] Han H, Yonggang W, Tat-Seng C, Xuelong L. Toward scalable systems for big bata analytics: a technology tutorial. IEEE Access 2014; 2: 652-687. doi: 0.1109/ACCESS.2014.2332453
• [2] Palen L, Anderson KM, Mark G, Martin J, Sicker D et al. A vision for technology-mediated support for public participation & assistance in mass emergencies & disasters. In: ACM-BCS Visions of Computer Science Conference; Edinburgh, UK; 2010. pp. 1-12.
• [3] Aydin AA. Incremental data collection & analytics the design of next generation crisis informatics software. PhD, University of Colorado, Boulder, CO, USA, 2016.
• [4] Gu T, Lu M, Li L. Runtime models for analysing and evaluating quality attributes of self-adaptive software: a survey. In: 12th International Conference on Reliability, Maintainability, and Safety; China; 2018. pp. 52-61.
• [5] Jaffar RN, Hussain AAAM, Chiad W. A new model for study of quality attributes to components based development approach. Periodicals of Engineering and Natural Sciences 2019; 7 (3): 1177-1185. doi: 10.21533/pen.v7i3
• [6] Arcos-Medina G, Mauricio D. Aspects of software quality applied to the process of agile software development: a systematic literature review. International Journal of Systems Assurance Engineering and Management. Springer India 2019; 10 (5): 867-897. doi: 10.1007/s13198-019-00840-7
• [7] Alakus TB, Das R, Turkoglu I. An overview of quality metrics used in estimating software faults.In: IEEE 2019 International Conference on Artificial Intelligence and Data Processing Symposium; Malatya, Turkey; 2019. pp. 1-6.
• [8] Nistala P, Nori KV, Reddy R. Software quality models: a systematic mapping study. In: IEEE/ACM International Conference on Software and System Processes; Montreal, Canada; 2019. pp. 125-134. AYDIN/Turk J Elec Eng & Comp Sci
• [9] Lytra I, Carrillo C, Capilla R, Zdun U. Quality attributes use in architecture design decision methods: research and practice. Computing Springer Vienna 2019; 102 (2): 551-572. doi: 10.1007/s00607-019-00758-9
• [10] Senthilkumar R, Arunkumar T. A survey on prioritization of software quality attributes. Indian Journal of Science and Technology 2016; 9 (44): 1-7. doi: 10.17485/ijst/2016/v9i44/86988
• [11] Becker S, Happe L, Mirandola R, Trubiani C. Towards a methodology driven by relationships of quality attributes for QoS-based analysis. In: ACM/SPEC International Conference on Performance Engineering; Prague, Czech Republic; 2013. pp. 311-314.
• [12] Aydin AA. An overview of quality attributes for data intensive systems in crisis informatics. In: International Artificial Intelligence and Data Processing Symposium; Malatya, Turkey; 2017. pp. 1-5.
• [13] Salfinger A, Girtelschmid S, Proll B, Retschitzegger W, Schwinger W. Crowd-sensing meets situation awareness: a research roadmap for crisis management. In: Hawaii International Conference on System Sciences; Kauai, HI, USA; 2015. pp. 153-162.
• [14] Lee N, Hirschmeier S, Müller S, Luz L J. Enablers in crisis information management: a literature review. In: 50th Hawaii International Conference on System Sciences; Waikoloa Village, HI, USA; 2017. pp. 274-283.
• [15] Fischer D, Poseggga O, Fischbach K. Communication barriers in crisis management: a literature review. In: 24th European Conference on Information Systems; İstanbul, Turkey; 2016. pp. 1-18.
• [16] Verma S, Vieweg S, Corvey WJ, Palen L, Martin J et al. Natural language processing to the rescue ?: extracting ‘situational awareness’ tweets during mass emergency. In: Fifth International AAAI Conference on Weblogs and Social Media; Barcelona, Spain; 2011. pp. 385-392.
• [17] Mukkamala A, Beck R. Disaster management and social media use for decision making by humanitarian organiza- tions. In: 49th Hawaii International Conference on System Sciences; Kauai, HI, USA; 2016. pp. 1379-1385.
• [18] Pavković B, Berbakov L, Vraneš S, Milenković M. Situation awareness and decision support tools for response phase of emergency management: a short survey. In: 25th International Workshop on Database and Expert Systems Applications; Munich, Germany; 2014. pp. 154-159.
• [19] Lindsay BR. Federal Emergency Management: A Brief Introduction. Washington, DC, USA: Congressional Research Service, 2012.
• [20] Chandrasekar A, Sudharajesh M, Rajesh P. A research study on software quality attributes. International Journal of Scientific and Research Publications 2014; 4 (1): 2250-3153. doi: 10.29322
• [21] Losavio F, Chirinos L, Lévy N, Ramdane-Cherif A. Quality characteristics for software architecture. The Journal of Object Technology 2003; 2 (2): 133-150. doi: 10.5381/jot.2003.2.2.a2
• [22] Chen L, Babar MA, Nuseibeh B. Characterizing architecturally significant requirements. IEEE Software 2013; 30 (2): 38-45. doi: 10.1109/MS.2012.174
• [23] Mattsson M, Grahn H, Mårtensson F. Software architecture evaluation methods for performance, maintainability, testability, and portability. In: 2nd International Conference on the Quality of Software Architectures; Västerås, Sweden; 2006. pp. 1-20.
• [24] ISO. Information Technology-Software Product Quality. Geneva, Switzerland: ISO, 2000.
• [25] Buschmann F, Ameller D, Ayala CP, Cabot J, Franch X. Architecture quality revisited. IEEE Software 2012; 29 (4): 22-24. doi: 10.1109/MS.2012.77
• [26] IEEE. Standard Glossary of Software Engineering Terminology. New York, NY, USA: IEEE, 1990.
• [27] ISO/IEC. Systems and software engineering - systems and software quality requirements and evaluation (SQuaRE)– System and software quality models. Geneva, Switzerland: ISO, 2011.
• [28] Yang Q, Zhao W. A method of selecting appropriate software architecture styles: quality attributes and analytic hierarchy process. BSc, University of Göteborg, Göteborg, Sweden, 2012
• [29] Wietfeld C, Wolff A, Bieker U. MobileEmerGIS: a wireless-enabled technology platform to support emergency response management. In: IEEE Conference on Technologies for Homeland Security; Woburn, MA, USA; 2007. pp. 51-56.
• [30] Ling A, Li X, Fan W, An N, Zhan J et al. Blue Arrow: a web-based spatially-enabled decision support system for emergency evacuation planning. In: International Conference on Business Intelligence and Financial Engineering; Beijing, China; 2009. pp. 575-578.
• [31] Han L, Potter S, Beckett G, Pringle G, Welch S et al. FireGrid: an e-infrastructure for next-generation emergency response support. Journal of Parallel and Distributed Computing 2010; 70 (11): 1128-1141. doi: 10.1016/j.jpdc.2010.06.005
• [32] Marcus A, Bernstein MS, Badar O, Krger DR, Madden S et al. Twitinfo: aggregating and visualizing microblogs for event exploration. In: ACM CHI Conference on Human Factors in Computing Systems; Vancouver, Canada; 2011. pp. 227-236.
• [33] Anderson KM, Schram A. Design and implementation of a data analytics infrastructure in support of crisis informatics research (nier track). In: International Conference on Software Engineering; Honolulu, HI, USA; 2011. pp. 844-847.
• [34] Maceachren AM, Jaiswal A, Robinson AC, Pezanowski S, Savelyev A. SensePlace2: GeoTwitter analytics support for situational awareness. In: IEEE Conference on Visual Analytics Science and Technology; Providence, RI, USA; 2011. pp. 181-190.
• [35] McTaggart C. Analysis and implementation of software tools to support research in crisis informatics. MSc, University of Colorado, Boulder, CO, USA, 2012.
• [36] Cameron MA, Power R, Robinson B, Yin J. Emergency situation awareness from twitter for crisis management. In: 21st International Conference Companion on World Wide Web; Lyon, France; 2012. pp. 695-698.
• [37] Oussalah M, Bhat F, Challis K, Schnier T. A software architecture for Twitter collection, search and geolocation services. Knowledge-Based Systems 2013; 37: 105-120. doi: 10.1016/j.knosys.2012.07.017
• [38] Purohit H, Sheth A. Twitris v3: from citizen sensing to analysis, coordination and action. In: Seventh International Association for the Advancement of Artificial Intelligence Conference on Weblogs and Social Media; Boston, MA, USA; 2013. pp. 3-4.
• [39] Zeitz K, Marchany R, Tront J. Designing an optimized alert system based on geospatial location data. In: 47th Hawaii International Conference on System Sciences; Washington, DC, USA; 2014. pp. 4159-4168.
• [40] Radianti J, Gonzalez JJ, Granmo O. Publish-subscribe smartphone sensing platform for the acute phase of a disaster: a framework for emergency management support. In: Fourth International Workshop on Pervasive Networks for Emergency Management; Budapest, Hungary; 2014. pp. 285-290.
• [41] Avvenuti M, Cresci S, Marchetti A, Meletti C, Tesconi M. EARS (earthquake alert and report system): a real time decision support system for earthquake crisis management. In: 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; New York, NY, USA; 2014. pp. 1749-1758.
• [42] Barrenechea M, Anderson KM, Palen L, White J. Engineering crowdwork for disaster events: the human-centered development of a lost-and-found tasking environment. In: 48th Hawaii International Conference on System Sciences; Kauai, HI, USA; 2015. pp. 182-191.
• [43] Anderson KM, Aydin AA, Barrenechea M, Cardenas A, Hakeem M et al. Design challenges/solutions for environ- ments supporting the analysis of social media data in crisis informatics research. In: 48th Hawaii International Conference on System Sciences; Kauai, HI, USA; 2015. pp. 163-172.
• [44] Parham K, Shash Y, Wong J, Frazier TZ, Cang L et al. DisasterBox: designing social media for disaster relief. In: 78th ASIS&T Annual Meeting; St. Louis, MO, USA; 2015. pp. 10-13.
• [45] Huang Q, Cervone G, Jing D, Chang C. DisasterMapper: a CyberGIS framework for disaster management using social media data. In: ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data; Seattle, WA, USA; 2015. pp. 1-6
• 46] Anderson J, Soden R, Anderson KM, Kogan M, Palen L. EPIC-OSM: a software framework for OpenStreetMap data analytics. In: 49th Hawaii International Conference on System Sciences; Kauai, HI, USA; 2016. pp. 5468-5477.
• [47] Aydin AA, Anderson KM. Batch to real-time: incremental data collection & analytics platform. In: 50th Hawaii International Conference on System Sciences; Waikoloa Village, HI, USA; 2017. pp. 5911-5920.
• [48] Gelernter J, Maheshwari N, Sussman A. Visualization and communication tool for emergency response. In: IEEE International Symposium on Technologies for Homeland Security; Woburn, MA, USA; 2018. pp. 1-5.
• [49] Parnas DL. On the criteria to be used in decomposing systems into modules. Communications of the ACM 1972; 15 (12): 1053-1058. doi: 10.1145/361598.361623
• [50] Schram A, Anderson KM. MySQL to NoSQL data modeling challenges in supporting scalability. In: 3rd Annual Conference on Systems, Programming, and Applications: Software for Humanity; Tucson, AZ, USA; 2012. pp. 191-202.
• [51] Barrenechea M, Jambi S, Aydin AA, Hakeem M, Anderson KM. Getting the query right for crisis informatics design issues for web-based analysis environments. Journal of Web Engineering 2017; 16 (5): 399-432.
• [52] Barrenechea M, Anderson KM, Aydin AA, Hakeem M, Jambi S. Getting the query right: user interface design of analysis platforms for crisis research. In: 15th International Conference on Web Engineering; Rotterdam, the Netherlands; 2015. pp. 663-666.
• [53] Baykara M, Daş R. Softswitch: A centralized honeypot-based security approach using software-defined switching for secure management of VLAN networks. Turkish Journal of Electrical Engineering and Computer Sciences 2019; 27 (5): 3309–3325. doi: 10.3906/elk-1812-86
• [54] Reuter C, Kaufhold MA. Fifteen years of social media in emergencies: a retrospective review and future directions for crisis informatics. Journal of Contingencies and Crisis Management 2018; 26 (1): 41-57. doi: 10.1111/1468- 5973.12196
• [55] Garlan D, Shaw M. An Introduction to Software Architecture. Advances in Software and Knowledge Engineering. Pittsburgh, PA, USA: World Scientific Publishing Company, 1993.
• [56] Kadadi A, Agrawal R, Nyamful C, Atiq R. Challenges of data integration and interoperability in big data. In: IEEE International Conference on Big Data; Washington, DC, USA; 2014. pp. 38-40