ICST.Table 1: Difference between revisions
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| '''H8.''' In WordPress, more of the lines of code that were changed due to security issues were hotspots. | | '''H8.''' In WordPress, more of the lines of code that were changed due to security issues were hotspots. | ||
| colspan=2 | True (Chi-Square, p<0.00001) | | colspan=2 | True (Chi-Square, p<0.00001) | ||
|- | |||
| style="border-style: solid; border-width: 0 1px 1px 0" | *This finding is consistent with the report from SANS (see Section 1) that indicates that the most popular types of web application attacks are input validation vulnerabilities. | |||
† Please note that we use the term "hypothesis" in this table with respect to scientific hypotheses and not statistical hypotheses. | |||
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Revision as of 22:31, 24 August 2013
| WordPress | WikkaWiki | |
|---|---|---|
| Releases Analysed | Nine | Six |
| Security issue reports analyzed | 97 | 61 |
| Vulnerable files (over project's history) | 26% (85 / 326) | 29% (44 / 209) |
| Average number of hotspots (over project's history | 255 | 92 |
| Average percent of files having at least one hotspot | 14.2% | 8.42% |
| Hypotheses about files | ||
| H1. The more hotspots a file contains per line of code, the more likely it is that the file contains any web application vulnerability. | True (Logistic Regression, p<0.05) | True (Logistic Regression, p<0.05) |
| H2. The more hotspots a file contains, the more times that file was changed due to any kind of vulnerability (not just input validation vulnerabilities). | True (Simple Linear Regression, p<0.0001, Adjusted R2 = 0.4208) | True (Simple Linear Regression, p<0.0001, Adjusted R2 = 0.3802) |
| Hypotheses about issue reports | ||
| H3. Input validation vulnerabilities result in a higher number average repository revisions than any other type of vulnerability*. | True (MWW, p<0.05) | True (MWW, p<0.05) |
| Hypotheses about prediction | ||
| H4. Hotspots can be used to predict files that will contain any type of web application vulnerability in the current release. | True (Predictive Modeling, see Table 2) | True (Predictive Modeling, see Table 3) |
| H5. The more hotspots a file contains, the more likely that file will be vulnerable in the next release. | True (Positive Coefficient on Predictive Models) | True (Positive Coefficient on Predictive Models) |
| Hypotheses comparing projects | ||
| H6. The average number of hotspots per file is more variable in WordPress than in WikkaWikki. | True (F-test, p<0.000001) | |
| H7. WordPress suffered a higher proportion of input validation vulnerabilities than WikkaWiki. | True (Chi-Squared, p=0.0692) | |
| H8. In WordPress, more of the lines of code that were changed due to security issues were hotspots. | True (Chi-Square, p<0.00001) | |
| *This finding is consistent with the report from SANS (see Section 1) that indicates that the most popular types of web application attacks are input validation vulnerabilities.
† Please note that we use the term "hypothesis" in this table with respect to scientific hypotheses and not statistical hypotheses. | ||