On null encryption and automated documentation
Dear KV, While reviewing some encryption code in our product, I came across an option that allowed for null encryption. This means the encryption could be turned on, but the data would never be encrypted or decrypted. It would always be stored "in the clear." I removed the option from our latest source tree because I figured we didn't want an unsuspecting user to turn on encryption but still have data stored in the clear. One of the other programmers on my team reviewed the potential change and blocked me from committing it, saying that the null code could be used for testing. I disagreed with her, since I think that the risk of accidentally using the code is more important than a simple test. Which of us is right?
Use states to drive your tests
End-to-end testing of Web applications typically involves tricky interactions with Web pages by means of a framework such as Selenium WebDriver. The recommended method for hiding such Web-page intricacies is to use page objects, but there are questions to answer first: Which page objects should you create when testing Web applications? What actions should you include in a page object? Which test scenarios should you specify, given your page objects?
Old questions being answered with both AI and HCI
The fields of artificial intelligence (AI) and human-computer interaction (HCI) are influencing each other like never before. Widely used systems such as Google Translate, Facebook Graph Search, and RelateIQ hide the complexity of large-scale AI systems behind intuitive interfaces. But relations were not always so auspicious. The two fields emerged at different points in the history of computer science, with different influences, ambitions, and attendant biases. AI aimed to construct a rival, and perhaps a successor, to the human intellect. Early AI researchers such as McCarthy, Minsky, and Shannon were mathematicians by training, so theorem-proving and formal models were attractive research directions. In contrast, HCI focused more on empirical approaches to usability and human factors, both of which generally aim to make machines more useful to humans. Many of the attendees at the first CHI conference in 1983 were psychologists and engineers. Papers were presented with titles such as "Design principles for human-computer interfaces" and "Psychological issues in the use of icons in command menus," hardly appealing fare for most mainstream AI researchers.