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|a 9783030274559
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|a 10.1007/978-3-030-27455-9
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|a QA76.758
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|a Search-Based Software Engineering
|h [electronic resource] :
|b 11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 - September 1, 2019, Proceedings /
|c edited by Shiva Nejati, Gregory Gay.
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|a 1st ed. 2019.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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|a XIV, 191 p. 88 illus., 28 illus. in color.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Programming and Software Engineering ;
|v 11664
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|a Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone -- A Systematic Comparison of Search Algorithms for Topic Modelling -- A Study on Duplicate Bug Report Identification -- Constructing Search Spaces for SBST using Machine Learning -- A Review of Ten Years of the Symposium on Search-Based Software Engineering -- Does Diversity Improve the Test Suite Generation for Mobile Applications -- Detect Performance Regression by Combining Static and Dynamic metrics Using Evolutionary Algorithms -- General Program Synthesis using Guided Corpus Generation and Automatic Refactoring -- A Search-Based Approach to Generate MC/DC Test Data for OCL Constraints -- Bio-Inspired Optimization of Test Data Generation for Concurrent Programs -- Revisiting Hyper-Parameter Tuning for Search-based Software Testing -- Towards Automated Boundary Value Testing with Program Derivatives and Search -- Code Naturalness to Assist Search Space Exploration in Search-based Program Repair Methods -- Dorylus: An Ant Colony Based Tool for Automated Test Case Generation -- Software Improvement with Gin.
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|a This book constitutes the refereed proceedings of the 11th International Symposium on Search-Based Software Engineering, SSBSE 2019, held in Tallinn, Estonia, in August/September 2019. The 9 research papers and 3 short papers presented together with 1 keynote and 1 challenge paper were carefully reviewed and selected from 28 submissions. SSBSE is a research area focused on the formulation of software engineering problems as search problems, and the subsequent use of complex heuristic techniques to attain optimal solutions to such problems. A wealth of engineering challenges - from test generation, to design refactoring, to process organization - can be solved efficiently through the application of automated optimization techniques. SBSE is a growing field - sitting at the crossroads between AI, machine learning, and software engineering - and SBSE techniques have begun to attain human-competitive results.
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|a Software engineering.
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|a Programming languages (Electronic computers).
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|a Computer programming.
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|a Artificial intelligence.
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|a Algorithms.
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|a Software Engineering.
|0 http://scigraph.springernature.com/things/product-market-codes/I14029
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|a Programming Languages, Compilers, Interpreters.
|0 http://scigraph.springernature.com/things/product-market-codes/I14037
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|a Programming Techniques.
|0 http://scigraph.springernature.com/things/product-market-codes/I14010
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a Algorithm Analysis and Problem Complexity.
|0 http://scigraph.springernature.com/things/product-market-codes/I16021
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|a Nejati, Shiva.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Gay, Gregory.
|e editor.
|0 (orcid)0000-0001-6794-9585
|1 https://orcid.org/0000-0001-6794-9585
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783030274542
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|i Printed edition:
|z 9783030274566
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|a Programming and Software Engineering ;
|v 11664
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|u https://doi.org/10.1007/978-3-030-27455-9
|z Full Text via HEAL-Link
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|a ZDB-2-SCS
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|a ZDB-2-LNC
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|a Computer Science (Springer-11645)
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