Quadratic Time Algorithms Appear to be Optimal for Sorting Evolving Data

MLA

Besa, Juan Jose, et al. Quadratic Time Algorithms Appear to Be Optimal for Sorting Evolving Data. 2018. EBSCOhost, widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsarx&AN=edsarx.1805.05443&authtype=sso&custid=ns315887.

APA

Besa, J. J., Devanny, W. E., Eppstein, D., Goodrich, M., & Johnson, T. (2018). Quadratic Time Algorithms Appear to be Optimal for Sorting Evolving Data.

Chicago

Besa, Juan Jose, William E. Devanny, David Eppstein, Michael Goodrich, and Timothy Johnson. 2018. “Quadratic Time Algorithms Appear to Be Optimal for Sorting Evolving Data.” http://widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsarx&AN=edsarx.1805.05443&authtype=sso&custid=ns315887.