| 000 | 04759nam a22006255i 4500 | ||
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| 001 | 978-3-030-59762-7 | ||
| 003 | DE-He213 | ||
| 005 | 20240423125319.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 200929s2020 sz | s |||| 0|eng d | ||
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| 024 | 7 |
_a10.1007/978-3-030-59762-7 _2doi |
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_aUMZ _2bicssc |
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_aSearch-Based Software Engineering _h[electronic resource] : _b12th International Symposium, SSBSE 2020, Bari, Italy, October 7–8, 2020, Proceedings / _cedited by Aldeida Aleti, Annibale Panichella. |
| 250 | _a1st ed. 2020. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
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| 300 |
_aXIV, 263 p. 86 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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| 490 | 1 |
_aProgramming and Software Engineering, _x2945-9168 ; _v12420 |
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| 505 | 0 | _aSearch-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 forMobile 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. | |
| 520 | _aThis 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. | ||
| 650 | 0 | _aSoftware engineering. | |
| 650 | 0 | _aAlgorithms. | |
| 650 | 0 | _aMicroprogramming . | |
| 650 | 0 | _aComputer networks . | |
| 650 | 0 | _aApplication software. | |
| 650 | 0 |
_aComputer science _xMathematics. |
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| 650 | 1 | 4 | _aSoftware Engineering. |
| 650 | 2 | 4 | _aAlgorithms. |
| 650 | 2 | 4 | _aControl Structures and Microprogramming. |
| 650 | 2 | 4 | _aComputer Communication Networks. |
| 650 | 2 | 4 | _aComputer and Information Systems Applications. |
| 650 | 2 | 4 | _aMathematics of Computing. |
| 700 | 1 |
_aAleti, Aldeida. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 700 | 1 |
_aPanichella, Annibale. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030597610 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783030597634 |
| 830 | 0 |
_aProgramming and Software Engineering, _x2945-9168 ; _v12420 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-59762-7 |
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