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Testing Software and Systems

Overview of attention for book
Cover of 'Testing Software and Systems'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Checking Experiments for Finite State Machines with Symbolic Inputs
  3. Altmetric Badge
    Chapter 2 Using Multiple Adaptive Distinguishing Sequences for Checking Sequence Generation
  4. Altmetric Badge
    Chapter 3 Model-Based Testing from Input Output Symbolic Transition Systems Enriched by Program Calls and Contracts
  5. Altmetric Badge
    Chapter 4 Graph Methods for Generating Test Cases with Universal and Existential Constraints
  6. Altmetric Badge
    Chapter 5 Reducing the Cost of Grammar-Based Testing Using Pattern Coverage
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    Chapter 6 Automated Test Design for Boundaries of Product Line Variants
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    Chapter 7 Guiding Testers’ Hands in Monitoring Tools: Application of Testing Approaches on SIP
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    Chapter 8 Testing for Distinguishing Repair Candidates in Spreadsheets – the Mussco Approach
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    Chapter 9 Novel Insights on Cross Project Fault Prediction Applied to Automotive Software
  11. Altmetric Badge
    Chapter 10 Inferring Finite State Machines Without Reset Using State Identification Sequences
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    Chapter 11 mu2: A Refactoring-Based Mutation Testing Framework for Erlang
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    Chapter 12 A Survey on Testing for Cyber Physical System
  14. Altmetric Badge
    Chapter 13 Test-Data Generation for Testing Parallel Real-Time Systems
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    Chapter 14 Selective Test Generation Approach for Testing Dynamic Behavioral Adaptations
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    Chapter 15 Heuristics for Deriving Adaptive Homing and Distinguishing Sequences for Nondeterministic Finite State Machines
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    Chapter 16 Genetic Algorithm Application for Enhancing State-Sensitivity Partitioning
  18. Altmetric Badge
    Chapter 17 A Negative Input Space Complexity Metric as Selection Criterion for Fuzz Testing
  19. Altmetric Badge
    Chapter 18 A Practical Evaluation Method of Network Traffic Load for Capacity Planning
Attention for Chapter 13: Test-Data Generation for Testing Parallel Real-Time Systems
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
7 Mendeley
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Chapter title
Test-Data Generation for Testing Parallel Real-Time Systems
Chapter number 13
Book title
Testing Software and Systems
Published in
Lecture notes in computer science, November 2015
DOI 10.1007/978-3-319-25945-1_13
Book ISBNs
978-3-31-925944-4, 978-3-31-925945-1
Authors

Muhammad Waqar Aziz, Syed Abdul Baqi Shah

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 57%
Student > Master 3 43%
Readers by discipline Count As %
Computer Science 6 86%
Engineering 1 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 February 2017.
All research outputs
#4,208,412
of 22,953,506 outputs
Outputs from Lecture notes in computer science
#989
of 8,133 outputs
Outputs of similar age
#58,471
of 286,495 outputs
Outputs of similar age from Lecture notes in computer science
#16
of 193 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,133 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 286,495 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 193 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.