Raimund L. Feldmann

A Snapshot of the State of Practice in Software Development for Medical Devices

The medical device industry is a constantly growing domain which makes use of more and more software products. Given the importance to this industry of dependable software components, rigorous software engineering techniques would seem to have an important role to play. However, in a recent survey of the industry we found a lower than expected rate of adoption of certain sound software engineering practices. To ensure and improve the quality of developed software products, whether they are standalone applications or embedded in complex systems, both the medical device industry as well as software engineers have to take action. Our survey is a first step in this direction and may help in identifying appropriate programs and future research topics.

Defect categorization: making use of a decade of widely varying historical data

This paper describes our experience in aggregating a number of historical datasets containing inspection defect data using different categorization schemes. Our goal was to make use of the historical data by creating models to guide future development projects. We describe our approach to reconciling the different choices used in the historical datasets to categorize defects, and the challenges we faced. We also present a set of recommendations for others involved in classifying defects.

Building Theories from Multiple Evidence Sources

As emphasized in other chapters of this book, useful results in empirical software engineering require a variety of data to be collected through different studies - focusing on a single context or single metric rarely tells a useful story. But, in each study, the requirements of the local context are liable to impose different con- straints on study design, the metrics to be collected, and other factors. Thus, even when all the studies focus on the same phenomenon (say, software quality), such studies can validly collect a number of different measures that are not at all com- patible (say, number of defects required to be fixed during development, number of problem reports received from the customer, total amount of effort that needed to be spent on rework). Can anything be done to build a useful body of knowledge from these disparate pieces? This chapter addresses strategies that have been applied to date to draw conclu- sions from across such varied but valid data sets. Key approaches are compared and the data to which they are best suited are identified. Our analysis together with associated lessons learned provide decision support for readers interested in choos- ing and using such approaches to build up useful theories.

Fully employing software inspections data

Software inspections provide a proven approach to quality assurance for software products of all kinds, including requirements, design, code, test plans, among others. Common to all inspections is the aim of finding and fixing defects as early as possible, and thereby providing cost savings by minimizing the amount of rework necessary later in the life cycle. Measurement data, such as the number and type of found defects and the effort spent by the inspection team, provide not only direct feedback about the software product to the project team, but are also valuable for process improvement activities. In this paper, we discuss NASA’s use of software inspections and the rich set of data that has resulted. In particular, we present results from analysis of inspection data that illustrate the benefits of fully utilizing that data for process improvement at several levels. Examining such data across multiple inspections or projects allows team members to monitor and trigger cross project improvements. Such improvements may focus on the software development processes of the whole organization as well as improvements to the applied inspection process itself.

Decision Support with EMPEROR

Selecting the right practice or technology for a given task should be based on the project goals and context. The selection process should be supported by empirical evidence and experiences with the practice in similar contexts [1]. Practitioners, however, usually do not have the time to search for existing empirical studies and to evaluate them in detail. A more centralized and practice-oriented approach is necessary to provide the required information in a convenient way. EMPEROR (experience management portal using empirical results as organizational resources) was developed to address this issue.