Document Type



Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence



Publication Details

A dissertation submitted in partial filfilment of the requirements of Staffordshire University for the degree of M.Sc. and carried out in collaboration with the Technological University Dublin, April 1999.


This dissertation analyses the area of legacy systems and determines the effects that are exhibited in legacy systems, presenting them in a legacy effect determination framework, so that management can ascertain whether the system they have is a legacy system. An analysis of legacy causal criteria is carried out, resulting in a table of legacy causes. A new definition of legacy systems is put forward, by defining legacy status as a status held by a legacy system. “A system exhibits legacy status if it is deficient in terms of its suitability to the business, its platform suitability or application software quality, with the effect that its asset value diminishes, as does its ease of operation, maintenance, migration or evolution.” Legacy status is split into three dimensions, that of system suitability, platform suitability and software quality. These dimensions are analysed and practices shown that enable good quality within them. Solution strategies for handling legacy systems are analysed and broken down into components. These components are analysed in regard to their impact on the legacy causes. A mapping takes place between each strategy component and legacy cause. A legacy causal criteria framework enables management to assess their systems for possible legacy status. This framework can be used on current existing systems or on new proposed systems. This legacy causal criteria framework is cross-referenced to the legacy effect determination framework, allowing management to see the real or potential effects that a weakness in one of the legacy causes may have. These frameworks can be applied both to existing systems to evaluate their legacy status or to potential new systems to evaluate how they will behave in the future.