A visualised software library: a software self-organising map

This paper presents an approach to self-structuring software libraries. The authors developed a representation scheme to construct a feature space over a collection of software assets. The feature space is self-organised by an unsupervised neural network. The self-organising map (SOM). The high-dimensional feature space is then protected onto the two-dimensional SOM output layer that makes the most important distance relationships among the software assets geometrically explicit. This approach has been applied to a real case, where a visualised library containing a set of UNIX commands is constructed. The results obtained from a retrieval experiment based on the library demonstrated great potential.