A systematic review on regression test selection techniques
摘要 本文是一篇綜述，總結了27篇paper中36個empirical studies，21個實驗和15個case studies。 評價了共28個RTS技術 1. 緒論 迴歸測試用例選擇需要權衡重跑測試的開銷和遺漏變更導致的風險 已有的研究主要包括基於代碼變更和規範變更的測試用例選擇方法，評價選擇技術，變更影響分析和不同應用中的迴歸測試（數據庫應用，GUI應用），測試自動化和測試流程增強 迴歸測
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相關文章
- 1. A Study of Regression Test Selection in Continuous Integration Environments
- 2. A Review on Deep Learning Techniques Applied to Semantic Segmentation
- 3. Feature Selection for Classification: A Review（二）
- 4. 綜述論文翻譯：A Review on Deep Learning Techniques Applied to Semantic Segmentation
- 5. A Review on Deep Learning Techniques Applied to Semantic Segmentation 閱讀筆記
- 6. "A Review of Medical Image Classification Techniques-2011"筆記
- 7. TEST DESIGN TECHNIQUES: AN OVERVIEW
- 8. Paper reading (三十)：A review on machine learning principles for multi-view biological data integratio
- 9. [初讀筆記] Cloud Migration Research: A Systematic Review (TCC, 2013)
- 10. R programming for feature selection and regression