@inproceedings{d295047c1ab24d7d9ba4ef488d39e16c,
title = "SENSA: Sensitivity analysis for quantitative change-impact prediction",
abstract = "Sensitivity analysis determines how a system responds to stimuli variations, which can benefit important software-engineering tasks such as change-impact analysis. We present SENSA, a novel dynamic-analysis technique and tool that combines sensitivity analysis and execution differencing to estimate the dependencies among statements that occur in practice. In addition to identifying dependencies, SENSA quantifies them to estimate how much or how likely a statement depends on another. Quantifying dependencies helps developers prioritize and focus their inspection of code relationships. To assess the benefits of quantifying dependencies with SENSA, we applied it to various statements across Java subjects to find and prioritize the potential impacts of changing those statements. We found that SENSA predicts the actual impacts of changes to those statements more accurately than static and dynamic forward slicing. Our SENSA prototype tool is freely available for download.",
keywords = "Change-impact prediction, dependence analysis, execution differencing, sensitivity analysis",
author = "Haipeng Cai and Siyuan Jiang and Raul Santelices and Zhang, \{Ying Jie\} and Yiji Zhang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 14th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2014 ; Conference date: 28-09-2014 Through 29-09-2014",
year = "2014",
month = dec,
day = "4",
doi = "10.1109/SCAM.2014.25",
language = "English",
series = "Proceedings - 2014 14th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "165--174",
booktitle = "Proceedings - 2014 14th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2014",
address = "United States",
}