Better Science Through Benchmarking: Lessons for Software Engineering
This event took place on Friday 04 June 2004 at 14:30
Susan Elliott Sim
Benchmarking has been used to compare the performance of a variety of technologies, including computer systems, information retrieval systems, and database management systems. In these and other research areas, benchmarking has caused the science to leap forward. Until now, research disciplines have enjoyed these benefits without a good understanding of how they were achieved. In this talk, I present a process model and a theory of benchmarking to account for these effects. These were developed by examining case histories of existing benchmarks and my own experience with community-wide tool evaluations in software reverse engineering. According to the theory, the tight relationship between a benchmark and the scientific paradigm of a discipline is responsible for the leap forward. A benchmark operationalizes a scientific paradigm; it takes an abstract concept and turns it into a guide for research. Application of this theory will be illustrated using an example from reverse engineering: the C++ Extractor Test Suite (CppETS), a benchmark for comparing fact extractors for the C++ programming language. This talk will conclude with a discussion of how insights from studying benchmarking can improve the science in software engineering and collaboration in scientific communities more broadly.
(No replay available due to a shortage of technical staff to record event on the day)
This event took place on Friday 04 June 2004 at 14:30
Benchmarking has been used to compare the performance of a variety of technologies, including computer systems, information retrieval systems, and database management systems. In these and other research areas, benchmarking has caused the science to leap forward. Until now, research disciplines have enjoyed these benefits without a good understanding of how they were achieved. In this talk, I present a process model and a theory of benchmarking to account for these effects. These were developed by examining case histories of existing benchmarks and my own experience with community-wide tool evaluations in software reverse engineering. According to the theory, the tight relationship between a benchmark and the scientific paradigm of a discipline is responsible for the leap forward. A benchmark operationalizes a scientific paradigm; it takes an abstract concept and turns it into a guide for research. Application of this theory will be illustrated using an example from reverse engineering: the C++ Extractor Test Suite (CppETS), a benchmark for comparing fact extractors for the C++ programming language. This talk will conclude with a discussion of how insights from studying benchmarking can improve the science in software engineering and collaboration in scientific communities more broadly.
(No replay available due to a shortage of technical staff to record event on the day)
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Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
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