Haruka Nakao

Ove Armbrust, Masafumi Katahira, Yuko Miyamoto et al.

Defining process standards by integrating, harmonizing, and standardizing heterogeneous and often implicit processes is an important task, especially for large development organizations. However, many challenges exist, such as limiting the scope of process standards, coping with different levels of process model abstraction, and identifying relevant process variabilities to be included in the standard. On the one hand, eliminating process variability by building more abstract models with higher degrees of interpretation has many disadvantages, such as less control over the process. Integrating all kinds of variability, on the other hand, leads to high process deployment costs. This article describes requirements and concepts for determining the scope of process standards based on a characterization of the potential products to be produced in the future, the projects expected for the future, and the respective process capabilities needed. In addition, the article sketches experience from determining the scope of space process standards for satellite software development. Finally, related work with respect to process model scoping, conclusions, and an outlook on future work are presented.

Michael Kläs, Haruka Nakao, Frank Elberzhager et al.

Planning quality assurance (QA) activities in a systematic way and controlling their execution are challenging tasks for companies that develop software or software-intensive systems. Both require estimation capabilities regarding the effectiveness of the applied QA techniques and the defect content of the checked artifacts. Existing approaches for these purposes need extensive measurement data from historical projects. Due to the fact that many companies do not collect enough data for applying these approaches (especially for the early project lifecycle), they typically base their QA planning and controlling solely on expert opinion. This article presents a hybrid method that combines commonly available measurement data and context-specific expert knowledge. To evaluate the method's applicability and usefulness, we conducted a case study in the context of independent verification and validation activities for critical software in the space domain. A hybrid defect content and effectiveness model was developed for the software requirements analysis phase and evaluated with available legacy data. One major result is that the hybrid model provides improved estimation accuracy when compared to applicable models based solely on data. The mean magnitude of relative error (MMRE) determined by cross-validation is 29.6% compared to 76.5% obtained by the most accurate data-based model.