This article proposes a model for identifying quality requirements based on three different views of quality. By specifying quality requirements in this manner, the framework establishes quailty requirements that can be quanitfied and measured as part of an overall quality assurance program. This results in two levels of quality: one at the system level that ensures a quality software product a...

In model-based development, the development effort is centered around a formal description of the proposed software system—the “model”. This model is derived from some high-level requirements describing the expected behavior of the software. For validation and verification purposes, this model can then be subjected to various types of analysis, for example, completeness and consistency analysis...

This paper introduces a structured goal-oriented agent-based process modelling framework, where advanced requirements engineering techniques are combined with software quality modelling approaches, to provide an environment within which the stakeholders and the analysts can easily cooperate to discover, verify and validate the new IT system requirements. It forces and assists the stakeholders, ...

In requirements engineering, properties of the environment and assumptions about it, called domain knowledge, need to be captured in addition to exploring the requirements. Despite the recognition of the significance of capturing and using the required domain knowledge, it might be missing, left implicit, or be captured inadequately during the software development. This results in an incorrect ...

Information Quality (IQ) is particularly important for the efficient performance of any system. Despite this, most of the Requirements Engineering (RE) frameworks either ignore IQ needs, or they deal with them as mere technical issues, i.e., they do not consider the social and organizational aspects that underlie such needs. This paper summarizes the experience of the authors in modeling and an...

The quality of data is often defined as “fitness for use”, i.e., the ability of a data collection to meet user requirements. The assessment of data quality dimensions should consider the degree to which data satisfy users’ needs. User expectations are clearly related to the selected information and at the same time the information can have different utilities depending on the type of user that ...

THIS ISSUE’S COLUMN reports on a presentation and papers from the 23rd International Working Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 17). REFSQ aims to foster the creation of a strong European requirementsengineering community across industry and academia. Feedback and suggestions are welcome. In addition, if you try or adopt any of the practices included ...

Data is considered as fundamental asset for organizations, its strategic value leads to reconsider the importance of maintaining adequate levels of quality in data that is managed by applications. However, within the context of Web applications development, no mechanisms to adequately control Data Quality (DQ) requirements have been still proposed. This proposal is grounded on the idea of antic...

quality of products and services is considered as a key factor for customer satisfaction. quality function deployment (qfd) is known as a critical tool for translating voice of customers to prioritize technical requirements of a production. the level of this satisfaction depends on the number of fulfilled requirements. it should be noted that this level varies according to the possible constrai...