In the initial phase of two complementary studies of the relation of persistence behavior to the causal perception of failure, temporal persistence and resistance to extinction were found to be positively related to the attribution of failure to insufficient effort and negatively related to attributions to ability and task difficulty by both male and female sixth graders. In Phase 2, the male pupils who least frequently attributed failure to lack of effort were randomly allocated to a control group or a social reinforcement group or a token plus social reinforcement attribution retraining group. At immediate and delayed posttests, experimental subjects attributed success and failure on the training task and two independent transfer tasks to effort significantly more than did controls. A significant increase from pretest levels on both persistence indexes paralleled the attributional change of experimental subjects. No difference was evident in the effectiveness of the two experimental treatments. Despite some attenuation on the transfer tasks, there was evidence of durability of training effects, and generalization of effects to an independent tester at a further 4-month follow-up posttest. The results provided strong support for the attribution model of achievement motivation and provide an empirical foundation for the rationale of attribution retraining programs.

Much has been learned in the last decade about concurrent programming..This patmr identifies the major concepts of concurrent programming and describes some of the more importam language notations for writing concurrent programs. The roles of processes, communication, and synchronization are discussed. Language notations for expressing concurrent execution and for specifying process interaction are surveyed. Synchronization primitives based on shared variables and on message passing are described. Finally, three general classes of concurrent programming languages are identified and compared.

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A new approach to information flow in sequential and parallel programs is presented. Flow proof rules that capture the information flow semantics of a variety of statements are given and used to construct program flow proofs. The method is illustrated by examples. The applications of flow proofs to certifying information flow policies and to solving the confinement problem are considered. It is also shown that flow rules and correctness rules can be combined to form an even more powerful proof system.

Distributed computations are concurrent programs in which processes communicate by message passing. Such programs typically execute on network architectures such as networks of workstations ordistributed memory parallel machines (i. e , multicomputers such ashypercubes).Several paradigms-examples or models-for process interaction in distributed computations are described. These include networks of filters, clients, and servers, heartbeat algorithms, probe/echo algorithms, broadcast algorithms, token-passing algorithms, decentralized servers, and bags of tasks. These paradigms areapplicable tonumerous practical problems. They areillustrated by solving problems, including parallel sorting, file servers, computing the topology of a network, distributed termination detection, replicated databases, and parallel adaptive quadrature.Solutions toallproblems arederived inastep-wise fashion from a general specification of the problem to a concrete solution. The derivations illustrate techniques for developing distributed algorithms.