Empirical evaluation of the effects of experience on code quality and programmer productivity: an exploratory study

被引:37
|
作者
Dieste, Oscar [1 ]
Aranda, Alejandrina M. [1 ]
Uyaguari, Fernando [1 ]
Turhan, Burak [2 ]
Tosun, Ayse [3 ]
Fucci, Davide [2 ]
Oivo, Markku [2 ]
Juristo, Natalia [1 ,2 ]
机构
[1] Univ Politecn Madrid, Escuela Tecn Super Ingenieros Informat, Campus Montegancedo, Boadilla Del Monte 28660, Spain
[2] Univ Oulu, Dept Informat Proc Sci, POB 3000, Oulu 90014, Finland
[3] Istanbul Tech Univ, Fac Comp & Informat, TR-34469 Maslakistanbul, Turkey
关键词
Experience; Industry; Academy; Programming; Iterative test-last development; External quality; Productivity; Performance; SOFTWARE-DESIGN; EXPERT; NOVICE; PERFORMANCE; ACQUISITION; SIZE; TASK;
D O I
10.1007/s10664-016-9471-3
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
There is a widespread belief in both SE and other branches of science that experience helps professionals to improve their performance. However, cases have been reported where experience not only does not have a positive influence but sometimes even degrades the performance of professionals. Determine whether years of experience influence programmer performance. We have analysed 10 quasi-experiments executed both in academia with graduate and postgraduate students and in industry with professionals. The experimental task was to apply ITLD on two experimental problems and then measure external code quality and programmer productivity. Programming experience gained in industry does not appear to have any effect whatsoever on quality and productivity. Overall programming experience gained in academia does tend to have a positive influence on programmer performance. These two findings may be related to the fact that, as opposed to deliberate practice, routine practice does not appear to lead to improved performance. Experience in the use of productivity tools, such as testing frameworks and IDE also has positive effects. Years of experience are a poor predictor of programmer performance. Academic background and specialized knowledge of task-related aspects appear to be rather good predictors.
引用
收藏
页码:2457 / 2542
页数:86
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