Search-Based Software Engineering

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.

Inhalt

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 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.