Software engineering using metaheuristic innovative algorithms: workshop report
Introduction
The first International Workshop on Software Engineering using Metaheuristic Innovative Algorithms aimed to broaden awareness within the software engineering community of metaheuristic algorithms and their application to Software Engineering problems [4]. It brought together researchers and practitioners in Software Engineering and metaheuristics, building upon the embryonic community, which currently occupies the intersection of the two fields.
Prior to the workshop, initial work on metaheuristics for Software Engineering had been conducted in the areas of testing [5], [6], [7], [9], [11], [12] and cost estimation [2], [3]. The workshop aimed to facilitate the extension of metaheuristic techniques into other areas of Software Engineering research and practice. The workshop included two sessions: a special session on the application of metaheuristics to software testing and a general session on the application of metaheuristics to the wider Software Engineering field.
The workshop attracted 26 participants from five countries with representation from academia and industry and with work presented on theory, practice and evaluation of search-based Software Engineering. There were two keynote talks, and five paper presentations, and a lively discussion of the issues. Papers presented at the workshop are available on the workshop website at
This report briefly summarises (in Section 2) the talks presented and (in Section 3) the discussion of issues which took place.
Details of future workshops and conferences on the application of metaheuristic search techniques to Software Engineering problems can be found on the SEMINAL2 website at
Section snippets
Keynote: an overview of genetic algorithms
This talk was given by Darrell Whitley, Computer Science Department, Colorado State University, USA.
Dr Whitley's talk provided an overview of Genetic Algorithms, indicating many useful and important theoretical results which software engineers seeking to exploit these techniques need to be aware of. He highlighted the issues involved in representation and selection operators, indicating that results which show binary encoding a poor second to real-number encoding can be misleading; grey coding
Issues raised in discussion
The idea of genetic programming as a possible way forward was discussed at some length. Software engineers, and in particular those with extensive experience of software maintenance issues were concerned that the code created would present significant comprehension and maintenance challenges.
There was a discussion of issues in evolutionary testing. Joachim Wegener described the approach adopted by DaimlerChrysler, indicating that results always outperformed random testing on every execution and
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A grammar-guided genetic programming framework configured for data mining and software testing
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2023, Proceedings - International Conference on Software EngineeringMetaheuristics and Software Engineering: Past, Present, and Future
2021, International Journal of Software Engineering and Knowledge EngineeringApplication-Aware Intrusion Detection: A Systematic Literature Review, Implications for Automotive Systems, and Applicability of AutoML
2021, Frontiers in Computer Science
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