Plug & Test at System Level via Testable TLM Primitives

With the evolution of Electronic System Level (ESL) design methodologies, we are experiencing an extensive use of Transaction-Level Modeling (TLM). TLM is a high-level approach to modeling digital systems where details of the communication among modules are separated from the those of the implementation of functional units. This paper represents a first step toward the automatic insertion of testing capabilities at the transaction level by definition of testable TLM primitives. The use of testable TLM primitives should help designers to easily get testable transaction level descriptions implementing what we call a "Plug & Test" design methodology. The proposed approach is intended to work both with hardware and software implementations. In particular, in this paper we will focus on the design of a testable FIFO communication channel to show how designers are given the freedom of trading-off complexity, testability levels, and cos

Self-testable components: from pragmatic tests to design-for-testability methodology

International audienceTesting is a key aspect of software development, because of its cost and impact on final product reliability. Classical views on testing and their associated testing models, based on the waterfall model, are not well-suited to an OO development process. The standardization of semi-formal modeling methods, such as UML, reveals this trend: testing can no longer be separated from specification/design/code stages. A test approach integrated with the OO process must be defined with an associated testing philosophy. The approach presented in this paper aims at providing a consistent framework for building trust into components. By measuring the quality of test cases, we seek to build trust in a component passing those test cases. We present a pragmatic approach for linking design and test of classes, seen as basic unit test components. Components are self-testable by enhancing them with embedded test sequences and test oracles. Self-testable components serve as building blocks for performing systematic integration and non-regression testing. The main contribution presented in this paper consists of using component self-tests to systematically exercise main system structural dependencies. This approach has been implemented in the Eiffel, Java, Perl and C++ languages. Since it is simpler, due to the direct support for Design-by-Contract TM in the language, the Eiffel implementation is detailed here

Developing an IS-impact decision tool: A literature based design science roadmap

This paper derives from research-in-progress intending both Design Research (DR) and Design Science (DS) outputs; the former a management decision tool based in IS-Impact (Gable et al. 2008) kernel theory; the latter being methodological learnings deriving from synthesis of the literature and reflection on the DR ‘case study’ experience. The paper introduces a generic, detailed and pragmatic DS ‘Research Roadmap’ or methodology, deriving at this stage primarily from synthesis and harmonization of relevant concepts identified through systematic archival analysis of related literature. The scope of the Roadmap too has been influenced by the parallel study aim to undertake DR applying and further evolving the Roadmap. The Roadmap is presented in attention to the dearth of detailed guidance available to novice Researchers in Design Science Research (DSR), and though preliminary, is expected to evolve and gradually be substantiated through experience of its application. A key distinction of the Roadmap from other DSR methods is its breadth of coverage of published DSR concepts and activities; its detail and scope. It represents a useful synthesis and integration of otherwise highly disparate DSR-related concepts

A Cognitive Science Based Machine Learning Architecture

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, humanlike learning mechanisms:\ud 1) perceptual learning, the learning of new objects, categories, relations, etc.,\ud 2) episodic learning of events, the what, where, and when,\ud 3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence