Abstract:
Software development has several stages to be followed by developers, starting from planning to deployment and maintenance. From those stages, the design phase, which pro...Show MoreMetadata
Abstract:
Software development has several stages to be followed by developers, starting from planning to deployment and maintenance. From those stages, the design phase, which produces blueprint of a system, needs an expert work since it is a creative and difficult stage that determines the behavior of the software. Hence, to design a good architecture that exhibits the desired behaviors, we need to select an appropriate architectural pattern. Selecting an architectural pattern for software depends on features like Quality Attributes (QA), functional requirements, and constraints. Due to the discrepancy of selection features architects face difficulty in the selection of the right pattern for the system. We have used tactics as a selection feature owing to the fact that tactics are building blocks of architectural patterns. In this study, we have built a model that detects tactics implemented in single software and then using custom built algorithm to recommend architectural pattern. The proposed tactic classification model used Natural Language Processing (NLP) for pre-processing of the datasets. We used Term Frequency-Inverse Document Frequency (TF-IDF) and word2vec vectorization after preprocessing to convert the textual data format to vectorized form. Furthermore, for classification, we used three different machine learning algorithms i.e., Support Vector Machine, Decision Tree, and Naive Bayes. To reach out high performance, we ran six different combinations of experiments. We selected TF-IDF with SVM combination since it performed better than the others with the accuracy value of 94%. Finally, we used a custom-built algorithm for the recommendation of an architectural pattern based on the tactics identified from the model and the second dataset. In this study we had conducted two prototypic experiment to evaluate our model along with custom-built algorithm. From thus two experiments, we had got most precise recommendation of architectural pattern for the system having ...
Published in: 2022 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)
Date of Conference: 28-30 November 2022
Date Added to IEEE Xplore: 08 December 2022
ISBN Information: