Chunking Complexity Measurement for Requirements Quality Knowledge Representation

In order to obtain a most effective return on a software project investment, then at least one requirements inspection shall be completed. A formal requirement inspection identifies low quality knowledge representation content in the requirements document. In software development projects where natural language requirements are produced, a requirements document summarizes the results of requirements knowledge analysis and becomes the basis for subsequent software development. In many cases, the knowledge content quality of the requirements documents dictates the success of the software development. The need for determining knowledge quality of requirements documents is particularly acute when the target applications are large, complicated, and mission critical. The goal of this research is to develop knowledge content quality indicators of requirements statements in a requirements document prior to informal inspections. To achieve the goal, knowledge quality properties of the requirements statements are adopted to represent the quality of requirements statements. A suite of complexity metrics for requirements statements is used as knowledge quality indicators and is developed based upon natural language knowledge research of noun phrase (NP) chunks. A formal requirements inspection identifies low quality knowledge representation content in the requirements document. The knowledge quality of requirements statements of requirements documents is one of the most important assets a project must inspect. An application of the metrics to improve requirements understandability and readability during requirements inspections can be built upon the metrics shown and suggested to be taken into account.