Automatic Re-engineering of Software Using Genetic Programming

By Conor Ryan. 1999

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Citations in the corpus

Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers (2016, background): “It contains eight basic types of objects, namely Booleans, numbers, strings, names, arrays, dictionaries, streams and the null objects.”
Search Based Software Engineering: Techniques, Taxonomy, Tutorial (2010, unknown): “This is a very well studied area of SBSE [21, 29, 30, 52, 75, 85], dating back to the work of Ryan and Williams [83, 104] on auto-parallelisation transformations.”
Search-based software engineering: Trends, techniques and applications (2012, unknown): “is single objective (combining all metrics into a single fitness value) [O’Keeffe and Ó Cinnéide 2006, 2007, 2008a,b; Ryan 2000; Seng et al. 2005, 2006; Williams 1998] or multiobjective (using Pareto optimality to separately optimize each metric) [Harman and Tratt 2007].”
The Current State and Future of Search Based Software Engineering (2007, methodology): “Ryan [74] worked on using search techniques to automate parallelization for supercomputers.”
Genetic programming for Reverse Engineering (2013, background): “formation tended to focus on improving program execution time (through parallelisation) [72], [81], [91] and size [24].”
Search Based Software Engineering: A Comprehensive Analysis and Review of Trends Techniques and Applications (2009, methodology): “The work can also be categorized according whether the approach followed is single objective (combining all metrics into a single fitness value) [373, 374, 375, 376, 402, 422, 423, 490] multi objective (using Pareto optimality to separately optimise each metric) [222].”