This report summarizes the findings of a retrospective analysis of coding errors in a major software system produced by a large Canadian software engineering firm. The code-base of the system is approximately 1.7 million lines of C++ integrated with third party RDBMS and GIS products. The safety related nature of the system and the size of its code base make it an ideal candidate for an investigation of software related defects referred to as ' memory leaks.' A ' memory leak' results from the failure to return previously allocated heap memory. The distribution of memory leaks is analyzed and a two-part memory leak classification scheme is described. A secondary focus of the investigation is the influence of decision complexity on system safety. This investigation yielded two statistically significant findings. The first is a relationship between programmer experience and memory leak creation. The second is a correlation between subsystem complexity and memory leak density. The impact of software process improvement measures are also discussed.--Page iii.
This thesis presents a new theory of information modelling in natural language processing that attempts to resolve anaphoric references, while also addressing the problem of knowledge complexity. A modular model of semantic representation is introduced that addresses the deficiencies of existing representations, as well as the drawbacks associated with expanding these semantic representations. Rather than using a single semantic representation to model human knowledge and the knowledge within a sentence, the theory proposes a modular, multi-level model which is based around a semantic network. The behaviour of the model uses theories on the nature of working and long-term memory from cognitive psychology. Two methods of artificial neuron activation and decay were implemented - the ACT-R model and the Thompson model. Maximum success rates of 54.10% and 83.61% were achieved for The Three Brothers corpus, and maximum success rates of 56.00% and 86.67% were achieved for the Rumpelstiltskin corpus.