Data Driven Testing of Open Source Software

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• 作者：Inbal Yahav (17)
  Ron S. Kenett (18) (19) (20)
  Xiaoying Bai (21)
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8803
• 期：1
• 页码：309-321
• 全文大小：878 KB
• 参考文献：1. Kenett, R.S., Baker, E.: Process Improvement and CMMI for Systems and Software. CRC Press (2010)
  2. Franch, X., Susi, A., Annosi, M.C., Ayala, C., Glott, R., Gross, D., Kenett, R., Mancinelli, F., Pop Ramsamy, C.T., Ameller, D., et al.: Managing risk in open source software adoption. In: Proc. 8th Int. Conf. on Software Engineering and Applications (ICSOFT-EA 2013). SciTePress (2013)
  3. Bai, X., Kenett, R.S., Yu, W.: Risk assessment and adaptive group testing of semantic web services. International Journal of Software Engineering and Knowledge Engineering聽22(05), 595鈥?20 (2012) ss="external" href="http://dx.doi.org/10.1142/S0218194012500167" target="_blank" title="It opens in new window">CrossRef
  4. Harel, A., Kenett, R.S., Ruggeri, F.: Modeling web usability diagnostics on the basis of usage statistics. In: Statistical Methods in eCommerce Research, pp. 131鈥?72 (2008)
  5. Kenett, R.S., Harel, A., Ruggeri, F.: Controlling the usability of web services. International Journal of Software Engineering and Knowledge Engineering聽19(05), 627鈥?51 (2009) ss="external" href="http://dx.doi.org/10.1142/S0218194009004362" target="_blank" title="It opens in new window">CrossRef
  6. Clauset, A., Newman, M.E., Moore, C.: Finding community structure in very large networks. Physical Review E聽70(6), 066111 (2004)
  7. Nagappan, N., Ball, T., Zeller, A.: Mining metrics to predict component failures. In: Proceedings of the 28th International Conference on Software Engineering (ICSE 2006), pp. 452鈥?61. ACM, New York (2006)
  8. Hata, H., Mizuno, O., Kikuno, T.: Bug prediction based on fine-grained module histories. In: Proceedings of the 2012 International Conference on Software Engineering (ICSE 2012), pp. 200鈥?10. IEEE Press, Piscataway (2012) ss="external" href="http://dx.doi.org/10.1109/ICSE.2012.6227193" target="_blank" title="It opens in new window">CrossRef
  9. Kim, S., Whitehead Jr., E.J., Zhang, Y.: Classifying Software Changes: Clean or Buggy? IEEE Trans. Softw. Eng.聽34(2), 181鈥?96 (2008) ss="external" href="http://dx.doi.org/10.1109/TSE.2007.70773" target="_blank" title="It opens in new window">CrossRef
  
• 作者单位：Inbal Yahav (17)
  Ron S. Kenett (18) (19) (20)
  Xiaoying Bai (21)
  
  17. Graduate School of Business Administration, Bar Ilan University, Israel
  18. The KPA Group, Israel
  19. Univ. of Torino, Italy
  20. NYU-Poly, NY, USA
  21. Dept. of Comp. Science and Technology, Tsinghua University, China
  
• ISSN：1611-3349

文摘

The increasing adoption of open source software (OSS) components in software systems introduces new quality risks and testing challenges. OSS components are developed and maintained by open communities and the fluctuation of community members and structures can result in instability of the software quality. Hence, an investigation is necessary to analyze the impact open community dynamics and the quality of the OSS, such as the level and trends in internal communications and content distribution. The analysis results provide inputs to drive selective testing for effective validation and verification of OSS components. The paper suggests an approach for monitoring community dynamics continuously, including communications like email and blogs, and repositories of bugs and fixes. Detection of patterns in the monitored behavior such as changes in traffic levels within and across clusters can be used in turn to drive testing efforts. Our proposal is demonstrated in the case of the XWiki OSS, a Java-based environment that allows for the storing of structured data and the execution of server side scripts within the wiki interface. We illustrate our concepts, methods and approach behind this approach for risk based testing of OSS.