A Classification of Faults Covering the Human-Computer Interaction Loop

  • Philippe PalanqueEmail author
  • Andy Cockburn
  • Carl Gutwin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12234)


The operator is one of the main sources of vulnerability in command and control systems; for example, 79% of fatal accidents in aviation are attributed to “human error.” Following Avizienis et al.’s classification system for faults human error at operation time can be characterized as the operator’s failure to deliver services while interacting with the command and control system. However, little previous work attempts to separate out the many different origins of faults that set the operator in an error mode. This paper proposes an extension to the Avizienis et al. taxonomy in order to more fully account for the human operator, making explicit the faults, error states, and failures that cause operators to deviate from correct service delivery. Our new taxonomy improves understanding and identification of faults, and provides systematic insight into ways that human service failures could be avoided or repaired. We present multiple concrete examples, from aviation and other domains, of faults affecting operators and fault-tolerant mechanisms, covering the critical aspects of the operator-side of the Human-Computer Interaction Loop.


Human error Failures Human-computer interaction loop 


  1. 1.
    Geske, R.: The Nall Report: General Aviation Accidents in 2015. AOPA Air Safety Institute (2015) Google Scholar
  2. 2.
    Boeing Corp.: Statistical Summary of Commercial Jet Airplane Accidents, Worldwide Operations 1959-2018Google Scholar
  3. 3.
    Sheikh Bahaei, S., Gallina, B., Laumann, K., Skogstad, M.R.: Effect of augmented reality on faults leading to human failures in socio-technical systems. In: 2019 4th International Conference on System Reliability and Safety (ICSRS), pp. 236–245. IEEE (2019)Google Scholar
  4. 4.
    Sheikh Bahaei, S., Gallina, B.: Augmented reality-extended humans: towards a taxonomy of failures – focus on visual technologies. In: European Safety and Reliability Conference (ESREL). Research Publishing, Singapore (2019)Google Scholar
  5. 5.
    Sheikh Bahaei, S., Gallina, S.: Towards assessing risk of safety-critical socio-technical systems while augmenting reality. In: International Symposium on Model-Based Safety and Assessment (IMBSA) (2019). ( Scholar
  6. 6.
    Avizienis, A., Laprie, J.C., Randell, B., Landwehr, C.: Basic concepts and taxonomy of dependable and secure computing. IEEE Trans. Dependable Secure Comput. 1(1), 11–33 (2004)CrossRefGoogle Scholar
  7. 7.
    International Standard Organization: “ISO 9241–11” Ergonomic requirements for office work with visual display terminals (VDT) – Part 11 Guidance on Usability (1996)Google Scholar
  8. 8.
    ISO 9241–210 Ergonomics of Human-System Interaction Ergonomics of human-system interaction – Part 210: Human-centred design for interactive systems (2010)Google Scholar
  9. 9.
    W3C Web Accessibility Initiative. Web Content Accessibility Guidelines (WCAG) Overview. Web Accessibility Initiative (WAI).
  10. 10.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)CrossRefGoogle Scholar
  11. 11.
    ISO/IEC 13407: Human-Centred Design Processes for Interactive Systems now integrated in ISO 9241 part 210 [8] (1999)Google Scholar
  12. 12.
    Gulliksen, J., Göransson, B., Boivie, I., Blomkvist, S., Persson, J., Cajander, Å.: Key principles for user-centred systems design. Behav. Inf. Technol. 22(6), 397–409 (2003)CrossRefGoogle Scholar
  13. 13.
    Gray, J.N.: Dependability in the Internet Era. In: High Dependability Computing Consortium Conference, Santa Cruz, CA, 7 May 2001Google Scholar
  14. 14.
    CS-25 – Amendment 17 - Certification Specifications and Acceptable Means of Compliance for Large Aeroplanes. EASA (2015)Google Scholar
  15. 15.
    Fayollas, C., Martinie, C., Palanque, P., Deleris, Y., Fabre, J., Navarre, D.: An approach for assessing the impact of dependability on usability: application to interactive cockpits. In: 2014 Tenth European Dependable Computing Conference, pp. 198–209 (2014)Google Scholar
  16. 16.
    Canny, A., Bouzekri, E., Martinie, C., Palanque, P.: Rationalizing the need of architecture-driven testing of interactive systems. In: Bogdan, C., Kuusinen, K., Lárusdóttir, M.K., Palanque, P., Winckler, M. (eds.) HCSE 2018. LNCS, vol. 11262, pp. 164–186. Springer, Cham (2019). Scholar
  17. 17.
    Bass, L., et al.: The arch model: Seeheim revisited. In: User Interface Developers’ Workshop (1991)Google Scholar
  18. 18.
    Cockburn, A., Masson, D., Gutwin, C., Palanque, P., Goguey, A., Yung, M., Trask, C.: Design and evaluation of brace touch for touchscreen input stabilisation. Int. J. Hum. Comput. Stud. 122(21–37), 7 (2019)Google Scholar
  19. 19.
    Navarre, D., Palanque, P., Basnyat, S.: A formal approach for user interaction reconfiguration of safety critical interactive systems. In: Harrison, M.D., Sujan, M.A. (eds.) SAFECOMP 2008. LNCS, vol. 5219, pp. 373–386. Springer, Heidelberg (2008). Scholar
  20. 20.
    Tankeu-Choitat, A., Navarre, D., Palanque, P., Deleris, Y., Fabre, J.-C., Fayollas, C.: Self-checking components for dependable interactive cockpits using formal description techniques. In: IEEE Pacific Rim Dependable Computing Conference, pp. 164–173 (2011)Google Scholar
  21. 21.
    Reason, J.: Human Error. Cambridge University Press, Cambridge (1990)CrossRefGoogle Scholar
  22. 22.
    Card, S.K., Moran, T.P., Newell, A.: The model human processor: an engineering model of human performance. In: Handbook of Perception and Human Performance. Vol. 2: Cognitive Processes and Performance, pp. 1–35 (1986)Google Scholar
  23. 23.
    Cockburn, A., et al.: Turbulent touch: touchscreen input for cockpit flight displays. In: CHI, pp. 6742–6753 (2017)Google Scholar
  24. 24.
    Norman, D.A., Draper, S.W. (eds.): User-Centered System Design: New Perspectives on Human-Computer Interaction. Lawrence Earlbaum Associates, Hillsdale (1986)Google Scholar
  25. 25.
    Gould, I.D., Lewis, C.: Designing for usability: key principles and what designers think. Commun. ACM 28(3), 300–311 (1985)CrossRefGoogle Scholar
  26. 26.
    Cronel, M., Dumas, B., Palanque, P., Canny, A.: MIODMIT: a generic architecture for dynamic multimodal interactive systems. In: Bogdan, C., Kuusinen, K., Lárusdóttir, M.K., Palanque, P., Winckler, M. (eds.) HCSE 2018. LNCS, vol. 11262, pp. 109–129. Springer, Cham (2019). Scholar
  27. 27.
    Feiler, P.H., Gluch, D.P., Hudak, J.J.: The architecture analysis & design language (AADL): An introduction (No. CMU/SEI-2006-TN-011). CMU Software Engineering Inst. (2006)Google Scholar
  28. 28.
    Albinsson, P.A., Zhai, S.: High precision touch screen interaction. In: Proceedings ACM CHI Conference, pp. 105–112 (2003)Google Scholar
  29. 29.
    Olwal, A., Feiner, S.: Rubbing the fisheye: precise touch-screen interaction with gestures and fisheye views. In: Conference Supplement of UIST, pp. 83–84 (2003)Google Scholar
  30. 30.
    Diaper, D., Stanton, N.: The Handbook of Task Analysis for Human-Computer Interaction. Lawrence Erlbaum Associates, Mahwah (2003). ISBN 0-8058-4432-5CrossRefGoogle Scholar
  31. 31.
    Fitt, P.M.: The information capacity of the human motor system in controlling the amplitude of movement. J. Exp. Psychol. 47, 381–391 (1954)CrossRefGoogle Scholar
  32. 32.
    Soukoreff, W., MacKenzie, S.: Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts’ law research in HCI. IJHCS 61(6), 751–789 (2004)Google Scholar
  33. 33.
    Beaudouin-Lafon, M., Mackay, W.: Prototyping tools and techniques. In: The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications, pp. 1006–1031. L. Erlbaum Associates Inc., Mahwah (2002)Google Scholar
  34. 34.
    Irgens-Hansen, K., Gundersen, H., et al.: Noise exposure and cognitive performance: a study on personnel on board Royal Norwegian Navy vessels. Noise Health 17(78), 320–327 (2015)CrossRefGoogle Scholar
  35. 35.
    Ando, S., Yamada, Y., Kokubu, M.: Reaction time to peripheral visual stimuli during exercise under hypoxia. J. Appl. Physiol. 108(5), 1210–1216 (2012)CrossRefGoogle Scholar
  36. 36.
    Winder, R., Borrill, J.: Fuels for memory: the role of oxygen and glucose in memory enhancement. Psychopharmacology 136(4), 349–356 (1998)CrossRefGoogle Scholar
  37. 37.
    Goncalves, J., et al.: Tapping task performance on smartphones in cold temperature. Interact. Comput. 29(3), 355–367 (2017)Google Scholar
  38. 38.
    Palakkamanil, M.M., Fielden, M.P.: Effects of malicious ocular laser exposure in commercial airline pilots. Can. J. Ophthalmol. 50(6), 429–432 (2015)CrossRefGoogle Scholar
  39. 39.
    Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47(4), 263–291 (1979)MathSciNetCrossRefGoogle Scholar
  40. 40.
    Wickens, C., Alexander, A.: Attentional tunneling and task management in synthetic vision displays. Int. J. Aviat. Psychol. 19, 182–199 (2009)CrossRefGoogle Scholar
  41. 41.
    The cognitive biases codex: 175 cognitive biases, 29 February 2020.
  42. 42.
    Sarter, N., Woods, D.: How in the world did we ever get into that mode? Mode error and awareness in supervisory control. Hum. Factors 37, 5–19 (1995)CrossRefGoogle Scholar
  43. 43.
    Johnson, C.W.: The role of night vision equipment in military incidents and accidents. In: Johnson, C.W., Palanque, P. (eds.) Human Error, Safety and Systems Development. IIFIP, vol. 152, pp. 1–16. Springer, Boston, MA (2004). Scholar
  44. 44.
    Carney, D., et al.: Cognitive de-biasing strategies: a faculty development workshop for clinical teachers in emergency medicine. MedEdPORTAL J. Teach. Learn. Resour. 13, 10646 (2017)Google Scholar
  45. 45.
    Carretta, T., Ree, M.: Pilot Candidate Selection Methods (PCSM): sources of validity. Int. J. Aviat. Psychol. 1994(4), 103–117 (2000)Google Scholar
  46. 46.
    Wason, P.C.: Reasoning. In: Foss, B. (ed.) New Horizons in Psychology, pp. 135–151. Penguin Books, Harmondsworth (1966)Google Scholar
  47. 47.
    Griggs, R., Cox, J.: The elusive thematic-materials effect in Wason’s selection task. Br. J. Psychol. 73, 407–420 (1982)CrossRefGoogle Scholar
  48. 48.
    Palanque, P., Cockburn, A., Désert-Legendre, L., Gutwin, C., Deleris, Y.: Brace touch: a dependable, turbulence-tolerant, multi-touch interaction technique for interactive cockpits. In: Romanovsky, A., Troubitsyna, E., Bitsch, F. (eds.) SAFECOMP 2019. LNCS, vol. 11698, pp. 53–68. Springer, Cham (2019). Scholar
  49. 49.
    Aircraft Accident Investigation Bureau Interim Report Interim Investigation Report of accident 737–8 MAX ET-AVJ, ET-302 (2020).
  50. 50.
    Reason, J.: Generic Error-Modeling System (GEMS): a cognitive framework for locating common human error forms. New Technol. Hum. Error 63, 63–83 (1987)Google Scholar
  51. 51.
    Norman, D.: Errors in human performance. University of California, San Diego, Report 8004, pp. 46 (1980)Google Scholar
  52. 52.
    Rasmussen, J.: Human errors. A taxonomy for describing human malfunction in industrial installations. J. Occup. Accid. 4(2–4), 311–333 (1982)CrossRefGoogle Scholar
  53. 53.
    Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-Oriented Domain Analysis (FODA) Feasibility Study. Technical Report CMU/SEI-90-TR-21 - ESD-90-TR-222. Carnegie-Mellon Univ Pittsburgh Pa Software Engineering Inst. (1990)Google Scholar
  54. 54.
    Hansman, S.: A taxonomy of network and computer attack methodologies. Comput. Secur. 24, 31–43 (2003)CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.ICS-IRITUniversité Paul Sabatier Toulouse 3ToulouseFrance
  2. 2.Computer ScienceUniversity of CanterburyChristchurchNew Zealand
  3. 3.Computer ScienceUniversity of SaskatchewanSaskatoonCanada

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