Impact of Solvent Quality on the Density Profiles of Looped Triblock Copolymer Brushes by Neutron Reflectivity Measurements

Preferential adsorption of poly(2-vinylpyridine)-deuterated polystyrene-poly(2-vinylpyridine) (PVP-dPS-PVP) triblock copolymers from toluene onto silicon leads to the formation of dPS loops tethered by the PVP end blocks. Using neutron reflectometry, we have determined the segment density profiles of these looped polymer brushes in toluene, a good solvent for the dPS block, and in cyclohexane at 20 °C (poor solvent), 32 °C, (near-Θ solvent), and 50 °C (marginal solvent). While the swelling behavior qualitatively agrees with that observed for singly grafted brushes, there are interesting differences in the local structural details: In a good solvent, the segment density profiles are composed of an inner parabolic region and a long, extended tail. In cyclohexane, the profiles are described by exponential decays. We ascribe these features to a novel polydispersity effect that arises due to tethering the PS loops by both ends. The results also show that the less dense layers undergo more significant changes in swollen height as solvent quality is changed and that the looped brushes of different molecular weight, asymmetry, and tethering density adhere to scaling relationships derived for lightly cross-linked polymer gels.

The Impact of Software Evolution on Code Coverage Information

Many tools and techniques for addressing software maintenance problems rely on code coverage information. Often, this coverage information is gathered for a specific version of a software system, and then used to perform analyses on subsequent versions of that system without being recalculated. As a software system evolves, however, modifications to the software alter the software’s behavior on particular inputs, and code coverage information gathered on earlier versions of a program may not accurately reflect the coverage that would be obtained on later versions. This discrepancy may affect the success of analyses dependent on code coverage information. Despite the importance of coverage information in various analyses, in our search of the literature we find no studies specifically examining the impact of software evolution on code coverage information. Therefore, we conducted empirical studies to examine this impact. The results of our studies suggest that even relatively small modifications can greatly affect code coverage information, and that the degree of impact of change on coverage may be difficult to predict.