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Programming Language Selection in Software Engineering: Results from an Adapted MLR Focused on Go, Haskell, Python and Rust软件工程中的编程语言选择：针对Go、Haskell、Python和Rust的适应性多元线性回归结果
Collins, Zoe; Di Paolo, Luigi; O'Grady, Cathal; Ryan, Niall; Marks, Gerard; Yilmaz, Murat; Clarke, Paul M.; McCarren, Andrew.png)
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收藏 Inner Source, Outer Source, Low Code, and No Code: Pros, Cons and Contexts - Results from an MLR内部源码、外部源码、低代码和无代码：优缺点及适用场景——多元线性回归分析结果Pitkevics, Georgijs; Dubey, Lakshita; Choa, Chee Hin; Koleva, Yana; Yilmaz, Murat; Clarke, Paul M.; McCarren, Andrew 分享 收藏 Interpretations of Automotive SPICE Generic Practices on Level 2汽车SPICE通用实践在Level 2中的解释Povirnaru, Elena-Flavia; Ekert, Damjan; Norimatsu, So; Mayer, Ralf; Glasbrenner, Sascha; Feulner, Alexander; Kurz-Griessnig, Brigitte; Lindermuth, Peter; Stolfa, Svatopluk; Michael, Mary Roselind; Franzitta, Valeria; Schumacher, Vanessa; Dreves, Rainer; Gasch, Andreas; Messnarz, Richard 分享 收藏 Current AI-Based Software Engineering, Strengths and Weaknesses - Results from a MLR当前基于AI的软件工程，优势与劣势——来自MLR的结果Walshe, Jed; Maloney, Robert; Grant, Evun; Conde, Carlos; Marks, Gerard; Yilmaz, Murat; Messnarz, Richard; Clarke, Paul M.; McCarren, Andrew 分享 收藏 
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