Software engineering processes for self-adaptive systems

In this paper, we discuss how for self-adaptive systems some activities that traditionally occur at development-time are moved to run-time. Responsibilities for these activities shift from software engineers to the system itself, causing the traditional boundary between development-time and run-time to blur. As a consequence, we argue how the traditional software engineering process needs to be reconceptualized to distinguish both development-time and run-time activities, and to support designers in taking decisions on how to properly engineer such systems. Furthermore, we identify a number of challenges related to this required reconceptualization, and we propose initial ideas based on process modeling. We use the Software and Systems Process Engineering Meta-Model (SPEM) to specify which activities are meant to be performed off-line and on-line, and also the dependencies between them. The proposed models should capture information about the costs and benefits of shifting activities to run-time, since such models should support software engineers in their decisions when they are engineering self-adaptive systems

Document retrieval metrics for program understanding

The need for domain knowledge representation for program comprehension is now widely accepted in the program comprehension community. The so-called "concept assignment problem" represents the challenge to locate domain concepts in the source code of programs. The vast majority of attempts to solve it are based on static source code search for clues to domain concepts. In contrast, our approach is based on dynamic analysis using information retrieval (IR) metrics. First we explain how we modeled the domain concepts and their role in program comprehension. Next we present how some of the popular IR metrics could be adapted to the "concept assignment problem" and the way we implemented the search engine. Then we present our own metric and the performance of these metrics to retrieve domain concepts in source code. The contribution of the paper is to show how the IR metrics could be applied to the "concept assignment problem" when the "documents" to retrieve are domain concepts structured in an ontology

Software evolution and the staged model of the software lifecycle

The aim of this chapter is to describe the new staged model [5]. We provide a broad overview of the state of the art in software maintenance and evolution. The emphasis is mainly on process and methods, (rather than technology), since this is where the main developments have occurred, and is of most relevance to this chapter. There is much useful material available on software maintenance management, including very practical guides [6]. We start from the foundations established within the international standards community. We then briefly revisit previous research work, as an understanding of these results is essential. Program comprehension is identified as a key component; interestingly, very few textbooks on software engineering and even on software maintenance mention the term, so our review of the state of the art addresses the field to include this perspective. The new model and our view of research areas are influenced by program comprehension more than other aspects. The staged model is presented, and evidence drawn from case studies. Practical implications are then described, and finally, research directions are presented

Comparing Private and Public Sector on Information Systems Development and Maintenance Efficiency

Part 5: EvaluationInternational audienceThis paper provides a comparison between public and private organizations on key figures relative to the information systems support activities. Many have claimed that public sector has a less satisfactory conduct of information system support than private sector. In this article we present selected data from survey investigations performed among Norwegian organizations on how they conduct information systems development and maintenance. This investigation has earlier been compared with similar investigations of this sort. A major finding from the previous comparisons is that even if we witness large changes in the underlying implementation technology and approaches used, a number of aspects such as the overall percentage of time used for maintaining and evolving systems in production compared to time used for development is remarkably stable. When we compare public and private organizations in the last survey, we find a small difference on some variables, but these are not statistically significant, thus cannot be used to conclude that IT development and evolutions is conducted more poorly in public sector than in private sector