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Search-based software engineering12t...
~
(1998 :)
Search-based software engineering12th International Symposium, SSBSE 2020, Bari, Italy, October 7-8, 2020 : proceedings /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Search-based software engineeringedited by Aldeida Aleti, Annibale Panichella.
Reminder of title:
12th International Symposium, SSBSE 2020, Bari, Italy, October 7-8, 2020 : proceedings /
remainder title:
SSBSE 2020
other author:
Aleti, Aldeida.
corporate name:
Published:
Cham :Springer International Publishing :2020.
Description:
xiv, 263 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Search enginesCongresses.
Online resource:
https://doi.org/10.1007/978-3-030-59762-7
ISBN:
9783030597627$q(electronic bk.)
Search-based software engineering12th International Symposium, SSBSE 2020, Bari, Italy, October 7-8, 2020 : proceedings /
Search-based software engineering
12th International Symposium, SSBSE 2020, Bari, Italy, October 7-8, 2020 : proceedings /[electronic resource] :SSBSE 2020edited by Aldeida Aleti, Annibale Panichella. - Cham :Springer International Publishing :2020. - xiv, 263 p. :ill., digital ;24 cm. - Lecture notes in computer science,124200302-9743 ;. - Lecture notes in computer science ;4891..
Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone -- Automated Unit Test Generation for Python -- Do Quality Indicators Prefer Particular Multi-Objective Search Algorithms in Search-Based Software Engineering -- It is not Only About Control Dependent Nodes: Basic Block Coverage for Search-Based Crash Reproduction -- Search-based Testing for Scratch Programs -- Solving Schedulability as a Search Space Problem with Decision Diagrams -- Transforming Multi-Objective Interactive Metamodel/Model Co-Evolution into Mono-Objective Search via Designer's Preferences Extraction -- Evolutionary Grammar-Based Fuzzing -- Commonality-Driven Unit Test Generation -- Using a Genetic Algorithm to Optimize Configurations in a Data Driven Application -- Measuring and Maintaining Population Diversity in Search-based Unit Test Generation -- Search@Home: A Commercial Off-the-Shelf Environment for Investigating Optimization Problems -- Exploring The Use of Genetic Algorithm Clustering for Mobile App Categorisation -- Impact of Test Suite Coverage on Overfitting in Genetic Improvement of Software -- Bet and Run for Test Case Generation -- Bytecode-based Multiple Condition Coverage: An Initial Investigation -- An application of model seeding to search-based unit test generation for Gson -- Generating Diverse Test Suites for Gson Through Adaptive Fitness Function Selection -- Defects4J as a Challenge Case for the Search-Based Software Engineering Community.
This book constitutes the refereed proceedings of the 12th International Symposium on Search-Based Software Engineering, SSBSE 2020, held in Bari, Italy, in October 2020. The 13 research papers and 5 short papers presented together with 1 keynote were carefully reviewed and selected from 34 submissions. SBSE 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. Due to the Corona pandemic SSBSE 2020 was held as a virtual event.
ISBN: 9783030597627$q(electronic bk.)
Standard No.: 10.1007/978-3-030-59762-7doiSubjects--Topical Terms:
522545
Search engines
--Congresses.
LC Class. No.: TK5105.884 / .S43 2020
Dewey Class. No.: 025.04
Search-based software engineering12th International Symposium, SSBSE 2020, Bari, Italy, October 7-8, 2020 : proceedings /
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Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone -- Automated Unit Test Generation for Python -- Do Quality Indicators Prefer Particular Multi-Objective Search Algorithms in Search-Based Software Engineering -- It is not Only About Control Dependent Nodes: Basic Block Coverage for Search-Based Crash Reproduction -- Search-based Testing for Scratch Programs -- Solving Schedulability as a Search Space Problem with Decision Diagrams -- Transforming Multi-Objective Interactive Metamodel/Model Co-Evolution into Mono-Objective Search via Designer's Preferences Extraction -- Evolutionary Grammar-Based Fuzzing -- Commonality-Driven Unit Test Generation -- Using a Genetic Algorithm to Optimize Configurations in a Data Driven Application -- Measuring and Maintaining Population Diversity in Search-based Unit Test Generation -- Search@Home: A Commercial Off-the-Shelf Environment for Investigating Optimization Problems -- Exploring The Use of Genetic Algorithm Clustering for Mobile App Categorisation -- Impact of Test Suite Coverage on Overfitting in Genetic Improvement of Software -- Bet and Run for Test Case Generation -- Bytecode-based Multiple Condition Coverage: An Initial Investigation -- An application of model seeding to search-based unit test generation for Gson -- Generating Diverse Test Suites for Gson Through Adaptive Fitness Function Selection -- Defects4J as a Challenge Case for the Search-Based Software Engineering Community.
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This book constitutes the refereed proceedings of the 12th International Symposium on Search-Based Software Engineering, SSBSE 2020, held in Bari, Italy, in October 2020. The 13 research papers and 5 short papers presented together with 1 keynote were carefully reviewed and selected from 34 submissions. SBSE 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. Due to the Corona pandemic SSBSE 2020 was held as a virtual event.
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Computer Science (SpringerNature-11645)
based on 0 review(s)
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