A framework for table driven testing of Java classes

With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.

Input-driven Language Learning

Input-driven models provide an explicit and readily testable account of language learning. Although we share Ellis's view that the statistical structure of the linguistic environment is a crucial and, until recently, relatively neglected variable in language learning, we also recognize that the approach makes three assumptions about cognition and language learning that are not universally shared. The three assumptions concern (a) the language learner as an intuitive statistician, (b) the constraints on what constitute relevant surface cues, and (c) the redescription problem faced by any system that seeks to derive abstract grammatical relations from the frequency of co-occurring surface forms and functions. These are significant assumptions that must be established if input-driven models are to gain wider acceptance. We comment on these issues and briefly describe a distributed, instance-based approach that retains the key features of the input-driven account advocated by Ellis but that also addresses shortcomings of the current approaches.

In situ characterization of stickiness of sugar-rich foods using a linear actuator driven stickiness testing device

A stickiness testing device based on the probe tack test has been designed and tested. It was used to perform in situ characterization of drying hemispherical drops with an initial radius 3.5 mm. Tests were carried out in two drying temperatures, 63 and 95 degreesC. Moisture and temperature histories of the drying drops of fructose, honey, sucrose, maltodextrin and sucrose-maltodextrin mixtures were determined. The rates of moisture evaporation of the fructose solution was the fastest while those of the maltodextrin solution was the lowest. A profile reversal was observed when the temperature profiles of these materials were compared. Different modes of failure were observed during the stickiness tests. Pure fructose and honey solutions remained completely sticky and failed cohesively until the end of drying. Pure sucrose solution remained sticky and failed cohesively until complete crystallization occurred. The surface of the maltodextrin drops formed a skin shortly after the start of drying. It exhibited adhesive failure and reached a state of non-adhesion. Addition of maltodextrin significantly altered the stickiness of sucrose solution. (C) 2002 Elsevier Science Ltd. All rights reserved.