In spite of the use of standard Web security measures (SSL/TLS), users enter sensitive information such as passwords into fake Web sites. Such fake sites cause substantial damages to individuals and corporations. In this work, we identify several vulnerabilities of browsers, focusing on security and identification indicators.We present improved security and identification indicators, as we implemented in TrustBar, a browser extension we developed. With TrustBar, users can assign a name or logo to identify SSL/TLS-protected sites; if users did not assign a name or logo, TrustBar identifies protected sites by the name or logo of the site, and by the certificate authority (CA) who identified the site.We present usability experiments which compared TrustBar's indicators to the basic indicators available in most browsers (padlock, URL, and https prefix), and some relevant secure-usability principles.
It is naturally easier to comprehend simple code relative to complicated code. Regrettably, there is little agreement on how to effectively measure code complexity. As a result simple generalpurpose metrics are often used, such as lines of code (LOC), McCabe's cyclomatic complexity (MCC), and Halstead's metrics. But such metrics just count syntactic features, and ignore details of the code's global structure, which may also have an effect on understandability. In particular, we suggest that code regularity-where the same structures are repeated time after time-may significantly reduce complexity, because once one figures out the basic repeated element it is easier to understand additional instances. We demonstrate this by controlled experiments where subjects perform cognitive tasks on different versions of the same basic function. The results indicate that versions with significant regularity lead to better comprehension, while taking similar time, despite being longer and having higher MCC. These results indicate that regularity is another attribute of code that should be taken into account in the context of studying the code's complexity and comprehension. Moreover, the fact that regularity may compensate for LOC and MCC demonstrates that complexity cannot be decomposed into independently addable contributions by individual attributes.
Abstract-McCabe's Cyclomatic Complexity (MCC) is a widely used metric for the complexity of control flow. Common usage decrees that functions should not have an MCC above 50, and preferably much less. However, the Linux kernel includes more than 800 functions with MCC values above 50, and over the years 369 functions have had an MCC of 100 or more. Moreover, some of these functions undergo extensive evolution, indicating that developers are successful in coping with the supposed high complexity. We attempt to explain this by analyzing the structure of such functions and showing that in many cases they are in fact well-structured. At the same time, we observe cases where developers indeed refactor the code in order to reduce complexity. These observations highlight the need to define more holistic notions of complexity, rather than using simple syntactic code metrics.
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