Directed Graph Exploration

Förster, Klaus-Tycho; Wattenhofer, Roger

doi:10.1007/978-3-642-35476-2_11

Cited by 12 publications

(3 citation statements)

References 40 publications

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“…If s = s, the ABM is updated (Lines 7-17): First, if s ∈ ABM k .S, s is added to the ABM, the plug-ins are notified, and for each tuple (α, ς v , ε) ∈ s \ s 0 , a new action (α, ς v + (click, l ε , null) ) is added to A(s ) (Lines [8][9][10][11][12][13]. Second, a new transition t is added to the ABM and the plug-ins are notified (Lines [15][16][17].…”

Section: Methodsmentioning

confidence: 99%

“…Between Steps 1 and 3, the customer may • click the add link in the shopping cart, select a gift wrap and a greeting card via radio button and click the Apply button. 16. To execute the action, PROCRAWL would need to provide the submission id displayed after submitting the paper, as well as the password provided in the submission form.…”

Section: Study 2: Oxid Eshop Orderingmentioning

confidence: 99%

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Mining Workflow Models from Web Applications

Schur

Röth

Zeller

2015

IIEEE Trans. Software Eng.

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Modern business applications predominantly rely on web technology, enabling software vendors to efficiently provide them as a service, removing some of the complexity of the traditional release and update process. While this facilitates shorter, more efficient and frequent release cycles, it requires continuous testing. Having insight into application behavior through explicit models can largely support development, testing and maintenance. Model-based testing allows efficient test creation based on a description of the states the application can be in and the transitions between these states. As specifying behavior models that are precise enough to be executable by a test automation tool is a hard task, an alternative is to extract them from running applications. However, mining such models is a challenge, in particular because one needs to know when two states are equivalent, as well as how to reach that state. We present ProCrawl (Process Crawler), a tool to mine behavior models from web applications that support multi-user workflows. ProCrawl incrementally learns a model by generating program runs and observing the application behavior through the user interface. In our evaluation on several real-world web applications, ProCrawl extracted models that concisely describe the implemented workflows and can be directly used for model-based testing.

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Section: Methodsmentioning

confidence: 99%

Section: Study 2: Oxid Eshop Orderingmentioning

confidence: 99%

Mining Workflow Models from Web Applications

Schur

Röth

Zeller

2015

IIEEE Trans. Software Eng.

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“…We would like to thank the anonymous reviewers of the 16th International Conference on Principles of Distributed Systems (OPODIS) for their helpful comments on our preliminary extended abstract [37]. The first author would also like to thank Cristina Pérez Arranz for supplying him with a copy of [15].…”

Section: Acknowledgementsmentioning

confidence: 99%

Lower and upper competitive bounds for online directed graph exploration

Foerster

Wattenhofer

2016

Theoretical Computer Science

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We study the problem of exploring all nodes of an unknown directed graph. A searcher has to construct a tour that visits all nodes, but only has information about the parts of the graph it already visited. Analogously to the travelling salesman problem, the goal is to minimize the cost of such a tour. In this article, we present upper and lower bounds for the competitive ratio of both the deterministic and the randomized online version of exploring all nodes of directed graphs. Our bounds are sharp or sharp up to a small constant, depending on the specific model. As it turns out, restricting the diameter, the incoming/outgoing degree, or randomly choosing a starting point does not improve lower bounds beyond a small constant factor. Even supplying the searcher in a planar euclidean graph with the nodes' coordinates does not help. Essentially, exploring a directed graph has a multiplicative overhead linear in the number of nodes. Furthermore, if one wants to search for a specific node in unweighted directed graphs, a greedy algorithm with quadratic multiplicative overhead can only be improved by a small constant factor as well.

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