The purpose of this study was to examine the relation between stimulus equivalence (briefly, networks of relations among stimuli) and the extension of stimulus function (briefly, spread of effect across network) more closely than has been possible before. The traditional view of this relation suggests that equivalence classes mediate the extension of stimulus function and are, therefore, necessary for any extension to occur. This study used a preparation in which the conditional discriminations required for the development of equivalence classes and the simple discriminations required for the extension of function were trained or tested simultaneously. Results suggest that equivalence are not necessary for the extension of stimulus function though they may be sufficient.

This thesis focuses upon how to calculate local components of Weil differentials of an elliptic function field. Because Weil differentials constitute a one-dimension vector space then one Weil differential is fixed. An algorithm calculating a local component is developed for the fixed one. The first algorithm computes local components of places of degree one. It is based upon elementary properties of local components. The definition of the Weil differential does not say enough about why it is defined in this way and about why it is useful. Thus there is the relationship between the Weil differential and some objects from complex analysis like the Laurent series and the residue. It provides a better understanding of properties of the Weil differential. The result of this thesis are other two algorithms calculating local components of Weil differentials. The algorithms employ the residue. 1