Departures from optimality: understanding human analyst's information foraging in assisted requirements tracing

  • Authors:
  • Nan Niu;Anas Mahmoud;Zhangji Chen;Gary Bradshaw

  • Affiliations:
  • Mississippi State University, USA;Mississippi State University, USA;Mississippi State University, USA;Mississippi State University, USA

  • Venue:
  • Proceedings of the 2013 International Conference on Software Engineering
  • Year:
  • 2013

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Abstract

Studying human analyst's behavior in automated tracing is a new research thrust. Building on a growing body of work in this area, we offer a novel approach to understanding requirements analyst's information seeking and gathering. We model analysts as predators in pursuit of prey --- the relevant traceability information, and leverage the optimality models to characterize a rational decision process. The behavior of real analysts with that of the optimal information forager is then compared and contrasted. The results show that the analysts' information diets are much wider than the theory's predictions, and their residing in low-profitability information patches is much longer than the optimal residence time. These uncovered discrepancies not only offer concrete insights into the obstacles faced by analysts, but also lead to principled ways to increase practical tool support for overcoming the obstacles.