Reconstruction of an execution architecture view by identifying mapping rules for connectors
•To our knowledge, this is the first method that focuses on connectors for the reconstruction of an execution view.•We developed the tools that automate the steps of the method, which can handle large volumes of input data.•To evaluate our proposed method, we conducted three real-world case studies....
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Published in: | The Journal of systems and software Vol. 220; p. 112268 |
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Abstract | •To our knowledge, this is the first method that focuses on connectors for the reconstruction of an execution view.•We developed the tools that automate the steps of the method, which can handle large volumes of input data.•To evaluate our proposed method, we conducted three real-world case studies.•Our case studies demonstrated that the proposed approach reconstructs an execution architecture with more than 86 % F1-score and less than 13.9 person-hours.•The tools and evaluation results are available at our GitHub repository.
An execution architecture view plays a crucial role in depicting the structure of a software system at runtime and analyzing its execution aspects, such as concurrency and performance. However, such execution views are frequently missing in real-world practices. Therefore, researchers have endeavored to reconstruct execution architecture views from software systems. However, existing approaches either require domain experts’ knowledge or are applicable only to systems with particular architecture styles. In this paper, we propose a systematic approach to reconstructing an execution architecture view, without prior knowledge of the components and connectors in the target system. With the proposed approach, by defining a candidate set of execution view connectors and mapping rules from source code to execution view connectors, developers can reconstruct an execution view. To evaluate the proposed approach, we applied it to three real-world software systems. Our evaluation results show that the proposed approach reconstructs an execution architecture with a higher than 86 % F1-score and less than 13.9 person-hours. |
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AbstractList | •To our knowledge, this is the first method that focuses on connectors for the reconstruction of an execution view.•We developed the tools that automate the steps of the method, which can handle large volumes of input data.•To evaluate our proposed method, we conducted three real-world case studies.•Our case studies demonstrated that the proposed approach reconstructs an execution architecture with more than 86 % F1-score and less than 13.9 person-hours.•The tools and evaluation results are available at our GitHub repository.
An execution architecture view plays a crucial role in depicting the structure of a software system at runtime and analyzing its execution aspects, such as concurrency and performance. However, such execution views are frequently missing in real-world practices. Therefore, researchers have endeavored to reconstruct execution architecture views from software systems. However, existing approaches either require domain experts’ knowledge or are applicable only to systems with particular architecture styles. In this paper, we propose a systematic approach to reconstructing an execution architecture view, without prior knowledge of the components and connectors in the target system. With the proposed approach, by defining a candidate set of execution view connectors and mapping rules from source code to execution view connectors, developers can reconstruct an execution view. To evaluate the proposed approach, we applied it to three real-world software systems. Our evaluation results show that the proposed approach reconstructs an execution architecture with a higher than 86 % F1-score and less than 13.9 person-hours. |
ArticleNumber | 112268 |
Author | Ahn, Hwi Lee, Seonah Kang, Sungwon |
Author_xml | – sequence: 1 givenname: Hwi surname: Ahn fullname: Ahn, Hwi email: ahnhwi@kaist.ac.kr organization: School of Computing, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea – sequence: 2 givenname: Sungwon orcidid: 0000-0001-7947-8741 surname: Kang fullname: Kang, Sungwon email: sungwon.kang@kaist.ac.kr organization: School of Computing, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea – sequence: 3 givenname: Seonah orcidid: 0000-0002-2004-2924 surname: Lee fullname: Lee, Seonah email: saleese@gnu.ac.kr organization: Department of AI Convergence Engineering Department of Aerospace and Software Engineering, Gyeongsang National University, Jinju 52828, South Korea |
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Keywords | Software architecture reconstruction Execution architecture Architecture connector Software engineering |
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