Search-Based Software Engineering: 11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 – September 1, 2019, Proceedings: Lecture Notes in Computer Science, cartea 11664
Editat de Shiva Nejati, Gregory Gayen Limba Engleză Paperback – 3 aug 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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Specificații
ISBN-13: 9783030274542
ISBN-10: 3030274543
Pagini: 191
Ilustrații: XIV, 191 p. 88 illus., 28 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.3 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Programming and Software Engineering
Locul publicării:Cham, Switzerland
ISBN-10: 3030274543
Pagini: 191
Ilustrații: XIV, 191 p. 88 illus., 28 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.3 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Programming and Software Engineering
Locul publicării:Cham, Switzerland
Cuprins
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.