KMi Seminars
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)

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Knowledge Management is...


Knowledge Management
Creating learning organisations hinges on managing knowledge at many levels. Knowledge can be provided by individuals or it can be created as a collective effort of a group working together towards a common goal, it can be situated as "war stories" or it can be generalised as guidelines, it can be described informally as comments in a natural language, pictures and technical drawings or it can be formalised as mathematical formulae and rules, it can be expressed explicitly or it can be tacit, embedded in the work product. The recipient of knowledge - the learner - can be an individual or a work group, professionals, university students, schoolchildren or informal communities of interest.
Our aim is to capture, analyse and organise knowledge, regardless of its origin and form and make it available to the learner when needed presented with the necessary context and in a form supporting the learning processes.