Open Access
Search-based test case generation for object-oriented Java software using strongly-typed genetic programming
José Carlos Bregieiro Ribeiro
- 01 Jul 2008
- pp 1819-1822
34
TL;DR: The focus of the on-going work is on employing evolutionary algorithms for the structural unit-testing of object-oriented Java programs, and the introduction of novel methodologies for automation, search guidance and input domain reduction.
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Abstract: In evolutionary testing, meta-heuristic search techniques are used to generate high-quality test data. The focus of our on-going work is on employing evolutionary algorithms for the structural unit-testing of object-oriented Java programs.Test cases are evolved using the Strongly-Typed Genetic Programming technique. Test data quality evaluation includes instrumenting the test object, executing it with the generated test cases, and tracing the structures traversed in order to derive coverage metrics. The strategy for efficiently guiding the search process towards achieving full structural coverage involves favouring test cases that exercise problematic structures and control-flow paths. Static analysis and instrumentation is performed solely with basis on the information extracted from the test objects' Java Bytecode.Relevant contributions include the introduction of novel methodologies for automation, search guidance and input domain reduction, and the presentation of the eCrash automated test case generation tool.
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Citations
Whole Test Suite Generation
Gordon Fraser,Andrea Arcuri +1 more
TL;DR: This work proposes a novel paradigm in which whole test suites are evolved with the aim of covering all coverage goals at the same time while keeping the total size as small as possible, and implemented this novel approach in the EvoSuite tool.
Parameter tuning or default values? An empirical investigation in search-based software engineering
Andrea Arcuri,Gordon Fraser +1 more
TL;DR: This paper carries out the largest empirical analysis so far on parameter tuning in search-based software engineering using the EvoSuite tool and results show that tuning does indeed have impact on the performance of a search algorithm.
On parameter tuning in search based software engineering
Andrea Arcuri,Gordon Fraser +1 more
- 10 Sep 2011
TL;DR: The largest empirical analysis on parameter tuning in SBSE to date is performed, collecting and statistically analysing data from more than a million experiments and giving guidelines on how to handle parameter tuning.
Evolutionary Generation of Whole Test Suites
Gordon Fraser,Andrea Arcuri +1 more
- 13 Jul 2011
TL;DR: EvoSuite is presented, a search-based approach that optimizes whole test suites towards satisfying a coverage criterion, rather than generating distinct test cases directed towards distinct coverage goals.
A detailed investigation of the effectiveness of whole test suite generation
TL;DR: It is found that keeping an archive of already covered goals along with the tests covering them and focusing the search on uncovered goals overcomes this small drawback on larger classes, leading to an improved overall effectiveness of whole test suite generation.
References
Soot: a Java bytecode optimization framework
Raja Vallée-Rai,Phong Co,Etienne Gagnon,Laurie Hendren,Patrick Lam,Vijay Sundaresan +5 more
- 01 Nov 2010
TL;DR: Soot, a framework for optimizing Java* bytecode, is implemented in Java and supports three intermediate representations for representing Java bytecode: Baf, a streamlined representation of bytecode which is simple to manipulate; Jimple, a typed 3-address intermediate representation suitable for optimization; and Grimp, an aggregated version of Jimple suitable for decompilation.
Strongly typed genetic programming
TL;DR: Strongly typed genetic programming (STGP) is an enhanced version of genetic programming that enforces data-type constraints and whose use of generic functions and generic data types makes it more powerful than other approaches to type-constraint enforcement.
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Whole Test Suite Generation
Gordon Fraser,Andrea Arcuri +1 more
TL;DR: This work proposes a novel paradigm in which whole test suites are evolved with the aim of covering all coverage goals at the same time while keeping the total size as small as possible, and implemented this novel approach in the EvoSuite tool.
Parameter tuning or default values? An empirical investigation in search-based software engineering
Andrea Arcuri,Gordon Fraser +1 more
TL;DR: This paper carries out the largest empirical analysis so far on parameter tuning in search-based software engineering using the EvoSuite tool and results show that tuning does indeed have impact on the performance of a search algorithm.
On parameter tuning in search based software engineering
Andrea Arcuri,Gordon Fraser +1 more
- 10 Sep 2011
TL;DR: The largest empirical analysis on parameter tuning in SBSE to date is performed, collecting and statistically analysing data from more than a million experiments and giving guidelines on how to handle parameter tuning.