NLCHECK: Stata module to check linearity assumption after model estimation

nlcheck is a simple diagnostic tool that can be used after fitting a model to quickly check the linearity assumption for a given predictor. nlcheck categorizes the predictor into bins, refits the model including dummy variables for the bins, and then performs a joint Wald test for the added parameters. Alternative, nlcheck uses linear splines for the adaptive model. Support for discrete variables is also provided. Optionally, nlcheck also displays a graph of the adjusted linear predictions from the original model and the adaptive model

Null Check Analysis

Null dereferencing is one of the most frequent bugs in Java systems causing programs to crash due to the uncaught NullPointerException. Developers often fix this bug by introducing a guard (i.e., null check) on the potentially-null objects before using them. In this paper we investigate the null checks in 717 open-source Java systems to understand when and why developers introduce null checks. We find that 35 of the if-statements are null checks. A deeper investigation shows that 71 of the checked-for-null objects are returned from method calls. This indicates that null checks have a serious impact on performance and that developers introduce null checks when they use methods that return null.