Top-Down Composition of Software Architectures

This paper discusses an approach for top-down composition of software architectures. First, an architecture is derived that addresses functional requirements only. This architecture contains a number of variability points which are next filled in to address quality concerns. The quality requirements and associated architectural solution fragments are captured in a so-called Feature-Solution (FS) graph. The solution fragments captured in this graph are used to iteratively compose an architecture. Our versatile composition technique allows for pre- and post-refinements, and refinements that involve multiple variability points. In addition, the usage of the FS graph supports Aspect-Oriented Programming (AOP) at the architecture level

Measurements Should Generate Value, Rather than Data,

Success factors for measurement programs as identified in the literature typically focus on the `internals' of the measurement program: incremental implementation, support from management, a well-planned metrics framework, and so on. However, for a measurement program to be successful within its larger organizational context, it has to generate value for the organization. This implies that attention should also be given to the proper mapping of some identifiable organizational problem onto the measurement program, as well as the translation back of measurement results to organizational actions. In this paper, we present a generic process model for measurement-based improvement, which does cover the latter issues as well. We describe a number of common uses for measurement programs in software organizations, from which we derive additional `external' success factors. In addition, we propose a number of activities that organizations can use to implement value-generating measurement programs

owards Mature Measurement Programs

Many organizations are using measurement as a means to improve their software development and maintenance processes. A reasonable consensus has been reached about the main success factors for measurement programs. However, no comprehensive approach has so far been published for the processes that need to be in place to ensure effective and efficient measurement. We propose a capability maturity model for measurement that can be used to both assess the measurement capability of software organizations and to identify directions for improvement of their measurement capability. This `Measurement-CMM' originates from our efforts to establish measurement programs in a variety of settings. These efforts had mixed results, and our analysis thereof showed widely different measurement capabilities amongst the organizations involved. A measurement maturity scale similar to that of the Software-CMM allowed us to explain many of the differences observed. At the same time, it suggests ways to impro..

redicting Maintenance Effort with Function Points

Function Point Analysis (FPA) is a well-known method to measure the functionality of a system, from the user's point of view. Both Albrecht's original model and a local variant we studied assume that effort is primarily related to the size of a change. Analysis of data gathered on a major system over a period of 18 months does not confirm this relation. Rather, our data suggests that the size of the component to be changed has a much larger impact on effort than the size of the change itself. Furthermore, the various corrective factors of the function point model do not help to improve effort estimates in the environment we studied. Finally, we found that expert estimates outperform the function point estimates, while analogy-based estimates slightly outperform the expert estimates