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Synergies Between Artificial Intelligence and Software Engineering: Evolution and Trends

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Handbook on Artificial Intelligence-Empowered Applied Software Engineering

Part of the book series: Artificial Intelligence-Enhanced Software and Systems Engineering ((AISSE,volume 2))

Abstract

Artificial intelligence (AI) is expected to change the way software engineers deal with the tasks of the software process lifecycle. Recently, we have experienced a growth in proposals based on the different branches of AI, given rise to novel areas of research and opening new possibilities to industrial practices. For example, search-based software engineering provides algorithms to search for better or optimised solutions to complex tasks in the software development process. Also, software analytics applies machine learning and mining techniques to discover knowledge from code repositories, developers’ forums or technical documentation, among other sources. Natural language processing and automatic reasoning are other AI areas whose techniques are serving to model and infer knowledge from software artefacts and documentation. In short, professionals have more resources now, but still need to understand the scope of AI methods for their effective use, and how they fit into their problems. In this chapter, we present a study of current AI trends in software engineering research, focused on the techniques more applicable to distinct aspects of the software process. Our analysis makes special emphasis on the innovative applications that integrate different AI perspectives, and the tools available to facilitate progress in AI-enhanced software engineering.

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Notes

  1. 1.

    https://clarivate.com/webofsciencegroup/solutions/journal-citation-reports/ (Last accessed: July 12, 2021).

  2. 2.

    http://scie.lcc.uma.es/gii-grin-scie-rating/ (Last accessed: July 12, 2021).

  3. 3.

    https://www.ieee.org/content/dam/ieee-org/ieee/web/org/pubs/ieee-taxonomy.pdf (Last accessed: July 12, 2021).

  4. 4.

    https://www.uco.es/grupos/kdis/sbse/aise.

  5. 5.

    The full list of authors is available from: https://www.uco.es/grupos/kdis/sbse/aise.

  6. 6.

    The full list of keywords is available from: https://www.uco.es/grupos/kdis/sbse/aise.

  7. 7.

    Notice that general keywords referring to research areas (e.g., ML or SBSE) are not included in Table 2.5, which is focused on types of techniques.

  8. 8.

    https://www.uco.es/grupos/kdis/sbse/aise.

  9. 9.

    https://www.uco.es/grupos/kdis/sbse/aise.

  10. 10.

    https://www.cs.waikato.ac.nz/ml/weka/ (Last accessed: July 12, 2021).

  11. 11.

    https://scikit-learn.org/ (Last accessed: July 12, 2021).

  12. 12.

    https://jmetal.github.io/jMetal/ (Last accessed: July 12, 2021).

  13. 13.

    http://sentistrength.wlv.ac.uk/ (Last accessed: July 12, 2021).

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Acknowledgements

This work was supported by Spanish Ministry of Science and Innovation (projects PID2020-115832GB-I00 and RED2018-102472-T), and the Andalusian Regional Government by means of the European Social Fund (postdoctoral grant DOC_00944).

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Authors and Affiliations

  1. Department Computer Science and Numerical Analysis, University of Córdoba, Córdoba, Spain

    Aurora Ramírez & José Raúl Romero

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  1. Aurora Ramírez
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  2. José Raúl Romero
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Correspondence to Aurora Ramírez .

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Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Maria Virvou

  2. Department of Informatics, University of Piraeus, Piraeus, Greece

    George A. Tsihrintzis

  3. College of Engineering and Computer Science, Wright State University, Joshi Research, Dayton, OH, USA

    Nikolaos G. Bourbakis

  4. KES International, Shoreham-by-Sea, UK

    Lakhmi C. Jain

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Ramírez, A., Romero, J.R. (2022). Synergies Between Artificial Intelligence and Software Engineering: Evolution and Trends. In: Virvou, M., Tsihrintzis, G.A., Bourbakis, N.G., Jain, L.C. (eds) Handbook on Artificial Intelligence-Empowered Applied Software Engineering. Artificial Intelligence-Enhanced Software and Systems Engineering, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-031-08202-3_2

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