DocumentCode :
3444389
Title :
Practical automated process and product metric collection and analysis in a classroom setting: lessons learned from Hackystat-UH
Author :
Johnson, Philip M. ; Kou, Hongbing ; Agustin, Joy M. ; Zhang, Qin ; Kagawa, Aaron ; Yamashita, Takuya
Author_Institution :
Dept. of Inf. & Comput. Sci., Hawaii Univ., Honolulu, HI, USA
fYear :
2004
fDate :
19-20 Aug. 2004
Firstpage :
136
Lastpage :
144
Abstract :
Measurement definition, collection, and analysis is an essential component of high quality software engineering practice, and is thus an essential component of the software engineering curriculum. However, providing students with practical experience with measurement in a classroom setting can be so time-consuming and intrusive that it\´s counter-productive-teaching students that software measurement is "impractical" for many software development contexts. In this research, we designed and evaluated a very low-overhead approach to measurement collection and analysis using the Hackystat system with special features for classroom use. We deployed this system in two software engineering classes at the University of Hawaii during Fall, 2003, and collected quantitative and qualitative data to evaluate the effectiveness of the approach. Results indicate that the approach represents substantial progress toward practical, automated metrics collection and analysis, though issues relating to the complexity of installation and privacy of user data remain.
Keywords :
computer science education; software metrics; software quality; software tools; teaching; Hackystat system; Hackystat-UH; University of Hawaii; classroom setting; counter-productive-teaching students; installation complexity; measurement analysis; measurement collection; measurement definition; product metric analysis; product metric collection; software development; software engineering; software measurement; Collaborative software; Computer hacking; Educational products; Educational programs; Information analysis; Laboratories; Programming; Software engineering; Software measurement; Software metrics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Empirical Software Engineering, 2004. ISESE '04. Proceedings. 2004 International Symposium on
Print_ISBN :
0-7695-2165-7
Type :
conf
DOI :
10.1109/ISESE.2004.1334901
Filename :
1334901
Link To Document :
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