Abstract
Software maintenance is a widely studied area of software engineering that it is particularly important in safety-critical and mission-critical applications where defects may have huge impact and code needs to be checked carefully through the analysis of data collected using a number of tools developed to investigate specific aspects. However, such tools are often not available to practitioners preventing them from applying the most recent and advanced approaches to industrial projects. This paper is an initial investigation about code analysis tools used to perform research studies on software maintenance prediction. We focus on the identification of tools that are available and can be used by practitioners to apply the same maintenance approaches described in published academic papers.
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Lenarduzzi, V., Sillitti, A., Taibi, D. (2020). A Survey on Code Analysis Tools for Software Maintenance Prediction. In: Ciancarini, P., Mazzara, M., Messina, A., Sillitti, A., Succi, G. (eds) Proceedings of 6th International Conference in Software Engineering for Defence Applications. SEDA 2018. Advances in Intelligent Systems and Computing, vol 925. Springer, Cham. https://doi.org/10.1007/978-3-030-14687-0_15
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DOI: https://doi.org/10.1007/978-3-030-14687-0_15
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