Implementing metrics for process improvement

There is increasing interest in the use of metrics to control the software development process, to demonstrate productivity and value, and to identify areas for process improvement. Research work completed to date is based on the implementation of metrics in a 'standard' software development environment, and follows either a top-down or bottom-up approach. With the advent of further European unity, many companies are producing localised products, ie products which are translated and adapted to suit each European country. Metrics systems need to be customised to the processes and environment of each company. This thesis describes a 12-step process for metrics implementation, using an optimum approach which is a combination of top-down and bottom-up approaches, with a set of applicable metrics, covering the software development process, which can be adapted for any development environment. For the case study, a software localisation company, the suggested implementation process is followed, and relevant measures are adapted to suit the different environment, with a particular emphasis on quality metrics. This thesis also demonstrates that a metrics system is itself subject to continuous improvement, and rather than being a once-off implementation, it is an evolutionary process, changing as the software development process comes under control

Reengineering

In Theorie und Praxis der betrieblichen Datenverarbeitung gewinnen Projekte zur systematischen Überarbeitung von (insbesondere alten) Anwendungssystemen immer mehr an Bedeutung. Als Bezeichnung für das entsprechende Wissens-/Forschungsgebiet hat sich der Begriff Reengineering etabliert. Der vorliegende Arbeitsbericht motiviert das Reengineering und weist auf seinen möglichen Nutzen hin. Darüber hinaus wird eine Übersicht einerseits über Anforderungen an Reengineering-Werkzeuge und andererseits über die zur Verfügung stehenden Tools gegeben. Außerdem werden zwei erfolgreiche Reengineering-Projekte vorgestellt

The Critical Success Factors of Quality Assurance and Measurement Practice in the Software Industry

In this thesis I analyse how QA and measurement programmes are implemented in the software industry. My thesis is that, contrary to popular belief, how companies implement QA and measurement is as important to the ultimate success of a programme as what QA and measurement tools and techniques are implemented. I have combined input from over 300 software developers and managers in 26 different companies, with the analysis of all the relevant publicly available information on companies’ experiences to produce a definitive study into implementing QA and measurement in the software industry. In this study I: • identify those QA and measurement practices considered to be state-of-the-art; • quantify the penetration of state-of-the-art practices; • report on the state-of-the-practice; • assess the effectiveness of the state-of-the-practice; • present guidelines for improved practice. I tested a variety of hypotheses about implementing QA and measurement programmes. My key findings about these hypotheses include: • Some companies have a large gap between what is officially said to be implemented and what is actually implemented. • Practitioners had a significant impact on the success of programmes. Furthermore, I confirmed my hypotheses about managers and developers having different attitudes to QA and measurement. However, I was unable to find convincing evidence to confirm that the demographics of practitioners affected their attitudes. • Many of my hypotheses about the implementation process were confirmed. In particular I found that doing background research was related to success, but that very few companies did research. However, I was unable to find convincing evidence to confirm the importance of feedback to practitioners. Overall my study reveals that the quality of the implementation process across the software industry is, in practice, very poor. Indeed, I show that the gap between state-of-the-art and state-of-the practice is large. I conclude that until the software industry puts as much effort into developing strategies for implementing QA and measurement as it does into developing tools and techniques, then effective and optimised programmes will remain rare