The systematic interaction of software developers with the business domain experts that are usually no software developers is crucial to software system maintenance and creation and has surfaced as the big challenge of modern software engineering. Existing frameworks promoting the typical programming languages with artificial syntax are suitable to be processed by computers but do not cater to domain experts, who are used to documents written in natural language as a means of interaction. Other frameworks that claim to be fully automated, such as those using natural language processing, are too imprecise to handle the typical requirements documents written in heterogeneous natural language flavours. In this thesis, a framework is proposed that can support the specification of business rules that is, on the one hand, understandable for nonprogrammers and on the other hand semantically founded, which enables computer processability. This is achieved by the novel language Adaptive Business Process and Rule Integration Language (APRIL). Specifications in APRIL can be written in a style close to natural language and are thus suitable for humans, which was empirically evaluated with a representative group of test persons. A useful and uncommon feature of APRIL is the ability to define reusable abstract mixfix operators as sentence patterns, that can mimic natural language. The semantic underpinning of the mixfix operators is achieved by customizable atomic formulas, allowing to tailor APRIL to specific domains. Atomic formulas are underpinned by a denotational semantics, which is based on Tempura (executable subset of Interval Temporal Logic (ITL)) to describe behaviour and the Object Constraint Language (OCL) to describe invariants and pre- and postconditions. APRIL statements can be used as the basis for automatically generating test code for software systems. An additional aspect of enhancing the quality of specification documents comes with a novel formal method technique (ISEPI) applicable to behavioural business rules semantically based on Propositional Interval Temporal Logic (PITL) and complying with the newly discovered 2-to-1 property. This work discovers how the ISE subset of ISEPI can be used to express complex behavioural business rules in a more concise and understandable way. The evaluation of ISE is done by an example specification taken from the car industry describing system behaviour, using the tools MONA and PITL2MONA. Finally, a methodology is presented that helps to guide a continuous transformation starting from purely natural language business rule specification to the APRIL specification which can then be transformed to test code. The methodologies, language concepts, algorithms, tools and techniques devised in this work are part of the APRIL-framework.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:738503 |
| Date | January 2017 |
| Creators | Roettenbacher, Christian Wolfgang |
| Publisher | De Montfort University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2086/15326 |
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