We employed a context-based teaching strategy using personal robots in an introductory computer science course. The purpose of this paper is twofold. First we describe our experiences using the IPRE (Institute for Personal Robots in Education) program to teach CS1. We then present our results from an initial study of its effectiveness. We compare the same course taught with and without the use of robots. We found that students in the robot section spent extra time on class-related work that was not required. This work was self-directed and demonstrates increased intrinsic motivation and interest.

This paper examines the past, present, and future of the programming languages course as reflected by its textbooks.

Abstract Mutation analysis is a powerful technique for testing software systems. The Mothra software testing project uses mutation analysis as the basis for an integrated software testing environment. Mutation analysis requires executing many slightly differing versions of the same program to evaluate the quality of the data used to test the program. The current version of Mothra includes a complete language system that translates a program to be tested into intermediate code so that it and its mutated versions can be executed by an interpreter. In this paper, we discuss some of the unique requirements of a language system used in a mutation‐based testing environment. We then describe how these requirements affected the design and implementation of the Fortran 77 version of the Mothra system. We also describe the intermediate language used by Mothra and the features of the language system that are needed for software testing. The appendices contain a full description of the intermediate language and the mutation operators used by Mothra. The design and implementation techniques that were developed for Mothra are applicable for constructing not just software testing systems, but any type of program analysis system or language system for a special‐purpose application. In particular, we discuss decisions made and techniques developed by the Mothra team that can be useful in such applications as debuggers, program measurement tools, software development environments and other types of program analysis systems.

We examine three ways of restricting the size (and shape) of the accepting computation trees of alternating Turing machines. We continue study by examining bounds on the number of leaves in the tree (Section 3), the 'width' of the tree (Section 4), and the number of nodes at any level of the tree (Section 5). Each of these measures can be interpreted as a limit on the amount of parallelism permitted the computation.