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Event-driven web application testing based on model-based mutation testing
Affiliation:1. School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, People''s Republic of China;2. Cyclotron Institute and Department of Physics and Astronomy, Texas A&M University, College Station, TX, 77843, USA and Department of Physics and Astronomy,Texas A& M University, College Station, TX, 77843, USA;3. Department of Physics and Astronomy, Wayne State University, Detroit, MI, 48201, USA;4. Instituto Galego de Física de Altas Enerxías IGFAE, Universidade de Santiago de Compostela, E-15782 Galicia-Spain;5. Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, China;6. Nuclear Science Division MS 70R0319, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States of America;7. Physics Department, University of California, Berkeley, CA 94720, United States of America;2. Department of Engineering Sustainability, University of Guglielmo Marconi, Via Plinio 44 - 00193 Rome, Italy
Abstract:ContextEvent-Driven Software (EDS) is a class of software whose behavior is driven by incoming events. Web and desktop applications that respond to user-initiated events on their Graphical User Interface (GUI), or embedded software responding to events and signals received from the equipment in its operating environment are examples of EDS. Testing EDS poses great challenges to software testers. One of these challenges is the need to generate a huge number of possible event sequences that could sufficiently cover the EDS’s state space.ObjectiveIn this paper, we introduce a new six-stage testing procedure for event-driven web applications to overcome EDS testing challenges.MethodThe stages of the testing procedure include dividing the application based on its structure, creating functional graphs for each section, creating mutants from functional graphs, choosing coverage criteria to produce test paths, merging event sequences to make longer ones, and deriving and running test cases. We have analyzed our proposed testing procedure with the help of four metrics consisting of Fault Detection Density (FDD), Fault Detection Effectiveness (FDE), Mutation Score, and Unique Fault.ResultsUsing this procedure, we have prepared prioritized test cases and also discovered a list of unique faults by running the suggested test cases on a sample real-world web application called Academic E-mail System.ConclusionWe propose that our suggested testing procedure has some advantages such as creating functional graphs with requirements document, resolving the problem of removing infeasible test cases with these graphs and conditions on the “add edge” operator before creating mutants. But the suggested testing procedure, like any other method, had some drawbacks. Because most of the stages in the approach were performed manually, the testing time was increased.
Keywords:Event-driven software  Web application  Event  Test case generation  Functional graph  Mutation analysis
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