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Search-based software engineering = 11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 - September 1, 2019 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Search-based software engineering/ edited by Shiva Nejati, Gregory Gay.
其他題名:	11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 - September 1, 2019 : proceedings /
其他題名:	SSBSE 2019
其他作者:	Nejati, Shiva.
團體作者:	SSBSE (Symposium)
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xiv, 191 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Computer science - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-030-27455-9
ISBN:	9783030274559

Search-based software engineering = 11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 - September 1, 2019 : proceedings /
Search-based software engineering11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 - September 1, 2019 : proceedings /[electronic resource] :SSBSE 2019edited by Shiva Nejati, Gregory Gay. - Cham :Springer International Publishing :2019. - xiv, 191 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,116640302-9743 ;. - Lecture notes in computer science ;11664..

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.

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.

ISBN: 9783030274559

Standard No.: 10.1007/978-3-030-27455-9doiSubjects--Topical Terms:

606819
Computer science
--Congresses.

LC Class. No.: QA76.758 / .S73 2019

Dewey Class. No.: 005.1

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