Heuristics for Scalable Dynamic Test Generation

By Jacob Burnim, Koushik Sen. 2008 23rd IEEE/ACM International Conference on Automated Software Engineering, 2008

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Automatic Grading and Feedback using Program Repair for Introductory Programming Courses (2017, unknown): “3 Automated testsuite generation tools [4, 5] can be used to improve the coverage of testsuite and improve the grading for programs that compile successfully.”
Symbolic execution for software testing: three decades later (2013, methodology): “As another example, heuristics based on random exploration have also proved successful [7, 8].”
Symbolic execution for software testing in practice: preliminary assessment (2011, methodology): “CREST is an extensible platform for building and experimenting with heuristics for selecting which paths to test for programs with far too many executions paths to exhaustively explore.”
Concolic Testing for Deep Neural Networks (2018, methodology): “is the heuristics used to select the next execution path. While there are simple approaches such as random search and depth-rst search, more carefully designed heuristics can achieve better coverage [23,24]. Automated generation of search heuristics for concolic testing is an active area of research”