Search Based Software Engineering

By G. Ruhe. Lecture Notes in Computer Science, 2013

587 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/9e4699c0f566e009a79dbe6482f0e169e8b085e1

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In Computer Networks and Communications

In Information Systems

Citations in the corpus

A Systematic Review of the Application and Empirical Investigation of Search-Based Test Case Generation (2010, unknown): “A systematic review synthesizes the existing work in a systematic, comprehensive, and unbiased manner.”
Machine Learning Testing: Survey, Landscapes and Horizons (2019, methodology): “For example, the literature uses the terms ‘statebased testing’ [16] and ‘search-based testing’ [17], [18] to refer to testing techniques that make use of concepts of state and search space, whereas we use the terms ‘GUI testing’ [19] and ‘unit testing’ [20] to refer to test techniques that tackle c”
Search Based Software Engineering: Techniques, Taxonomy, Tutorial (2010, unknown): “The term SBSE was coined by Harman and Jones [45] in 2001, which was the first paper to advocate Search Based Optimisation as a general approach to Software Engineering, though there were other authors who had previously applied search based optimisation to aspects of Software Engineering.”
An orchestrated survey of methodologies for automated software test case generation (2013, methodology): “SBST is a branch of Search-Based Software Engineering (SBSE) (Harman and Jones, 2001), in which optimisation algorithms are used to automate the search for test data that maximises the achievement of test goals, while minimising testing costs.”
Genetic programming for Reverse Engineering (2013, background): “offs and tensions between the objectives, something often advocated as an advantage of SBSE [42], [34].”
Large Language Models for Software Engineering: Survey and Open Problems (2023, methodology): “To address this issue, we can refer to the well-established literature on software repair [45], [142], grounded in over two decades of the development of search-based approaches to software engineering [11], [143].”
Search-Based Software Testing: Past, Present and Future (2011, methodology): “Searchbased approaches have also been applied to problems in the wider area of software engineering, leading Harman and Jones to coin the phrase 'Search-Based Software Engineering' [20] in 2001.”
Search-Based Procedural Content Generation: A Taxonomy and Survey (2011, methodology): “Finally, the term search-based for a similar range of techniques is established within search-based software engineering [21], [22].”
Guided GUI testing of android apps with minimal restart and approximate learning (2013, methodology): “To resolve this, we would need to combine existing GUI test generation techniques with symbolic execution [61] or search-based testing techniques [48, 49], in the sense that hybrid concolic testing [72] combines random testing and concolic execution [33].”
The Impact of Automated Parameter Optimization on Defect Prediction Models (2018, methodology): “[47], we add a random search technique [10], and two evolutionary algorithms that”
A survey of the use of crowdsourcing in software engineering (2017, methodology): “The model can also be employed in organising broadly accessible software engineering contests (Cleland-Huang et al., 2012) such as Predictive Models in Software Engineering (PROMISE), Mining of Software Repositories (MSR) and Search Based Software1480 Engineering (Harman and Jones, 2001) (SBSE) chal”
A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search (2010, unknown): “D.2.5 [Software Engineering]: Testing and Debugging – Testing Tools ; I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search – Heuristic Methods General Terms.”