Automated software quality visualisation using fuzzy logic techniques

In the past decade there has been a concerted effort by the software industry to improve the quality of its products. This has led to the inception of various techniques with which to control and measure the process involved in software development. Methods like the Capability Maturity Model have introduced processes and strategies that require measurement in the form of software metrics. With the ever increasing number of software metrics being introduced by capability based processes, software development organisations are finding it more difficult to understand and interpret metric scores. This is particularly problematic for senior management and project managers where analysis of the actual data is not feasible. This paper proposes a method with which to visually represent metric scores so that managers can easily see how their organisation is performing relative to quality goals set for each type of metric. Acting primarily as a proof of concept and prototype, we suggest ways in which real customer needs can be translated into a feasible technical solution. The solution itself visualises metric scores in the form of a tree structure and utilises Fuzzy Logic techniques, XGMML, Web Services and the .NET Framework. Future work is proposed to extend the system from the prototype stage and to overcome a problem with the masking of poor scores

A software service supporting software quality forecasting

Software repositories such as source control, defect tracking systems and project management tools, are used to support the progress of software projects. The exploitation of such data with techniques like forecasting is becoming an increasing need in several domains to support decision-making processes. However, although there exist several statistical tools and languages supporting forecasting, there is a lack of friendly approaches that enable practitioners to exploit the advantages of creating and using such models in their dashboard tools. Therefore, we have developed a modular and flexible forecasting service allowing the interconnection with different kinds of databases/data repositories for creating and exploiting forecasting models based on methods like ARIMA or ETS. The service is open source software, has been developed in Java and R and exposes its functionalities through a REST API. Architecture details are provided, along with functionalities’ description and an example of its use for software quality forecasting.Peer ReviewedPostprint (author's final draft

Training, Quality Assurance Factors, and Tools Investigation: a Work Report and Suggestions on Software Quality Assurance

Previously, several research tasks have been conducted, some observations were obtained, and several possible suggestions have been contemplated involving software quality assurance engineering at NASA Johnson. These research tasks are briefly described. Also, a brief discussion is given on the role of software quality assurance in software engineering along with some observations and suggestions. A brief discussion on a training program for software quality assurance engineers is provided. A list of assurance factors as well as quality factors are also included. Finally, a process model which can be used for searching and collecting software quality assurance tools is presented

Integrating automated support for a software management cycle into the TAME system

Software managers are interested in the quantitative management of software quality, cost and progress. An integrated software management methodology, which can be applied throughout the software life cycle for any number purposes, is required. The TAME (Tailoring A Measurement Environment) methodology is based on the improvement paradigm and the goal/question/metric (GQM) paradigm. This methodology helps generate a software engineering process and measurement environment based on the project characteristics. The SQMAR (software quality measurement and assurance technology) is a software quality metric system and methodology applied to the development processes. It is based on the feed forward control principle. Quality target setting is carried out before the plan-do-check-action activities are performed. These methodologies are integrated to realize goal oriented measurement, process control and visual management. A metric setting procedure based on the GQM paradigm, a management system called the software management cycle (SMC), and its application to a case study based on NASA/SEL data are discussed. The expected effects of SMC are quality improvement, managerial cost reduction, accumulation and reuse of experience, and a highly visual management reporting system

Measuring the Pro-Activity of Software Agents

Despite having well-defined characteristics, software agents do not have a developed set of measures defining their quality. Attempts at evaluating software agent quality have focused on some agent aspects, like the development process, whereas others focusing on the agent as a software product have basically adopted measures associated with other software paradigms, like procedural and object-oriented concepts. Here we propose a set of measures for evaluating software agent pro-activity, the software agent's goal-driven behavioral ability to take the initiative and satisfy its goal