Titlebook: Reuse and Software Quality; 21st International C Achilleas Achilleos,Lidia Fuentes,George Angelos P Conference proceedings 2024 The Editor(

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書目名稱Reuse and Software Quality影響因子(影響力)




書目名稱Reuse and Software Quality影響因子(影響力)學科排名




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書目名稱Reuse and Software Quality網(wǎng)絡(luò)公開度學科排名




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書目名稱Reuse and Software Quality被引頻次學科排名




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書目名稱Reuse and Software Quality年度引用學科排名




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978-3-031-66458-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Conference proceedings 2024rus, during June 19–20, 2024...The 9 full papers presented together with 2 short papers were carefully reviewed and selected from 25 submissions. They focus on the following topics:?artificial intelligence and reuse;?variability and reuse; adaptation and reuse; and code reuse..

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The Unexpected Blocking of?Code Understanding in?AI-Based Code Summarization: Observations and?Conceith BLEU scores over 50% lower, while ROUGE and METEOR scores are over 30% lower on cross-project test sets. Current models may rely more on project-specific than generic code features to understand code. We link this to the model’s performance on different code channels. It is suggested that the mo

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Complexity of?In-Code Variability: Emergence of?Detachable Decoratorsar code construct with a predefined naming convention and no effects on code. The study was conducted on a software product line aimed at graphical applications we developed for evaluation purposes. We came to a range of interesting findings, such as that the detachable decorator version of introduc

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Assessing Reflection Usage with?Mutation Testing Augmented Analysiswing the information it reveals. We evaluate our approach on a selection of five projects by comparing its performance against static analysis. We show that out of five projects, RAPIM disambiguates more potentially reflective call-sites than the static analysis. When the code coverage is good, the

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Using Energy Consumption for Self-adaptation in?FaaSot only capable of detecting variations in the energy consumption of the functions, but it does so taking into account the variability in the measurements that each function may present. Our experiments showcase proper integration in a self-adaptive system, showing a reduction up to 5% in energy con