Software product line engineering is an efficient means to generate a set of tailored software products from a common implementation. However, adopting a product-line approach poses a major challenge and significant risks, since typically legacy code must be migrated toward a product line. Our aim is to lower the adoption barrier by providing semi-automatic tool support—called variability mining —to support developers in locating, documenting, and extracting implementations of product-line features from legacy code. Variability mining combines prior work on concern location, reverse engineering, and variability-aware type systems, but is tailored specifically for the use in product lines. Our work pursues three technical goals: (1) we provide a consistency indicator based on a variability-aware type system, (2) we mine features at a fine level of granularity, and (3) we exploit domain knowledge about the relationship between features when available. With a quantitative study, we demonstrate that variability mining can efficiently support developers in locating features.

Enterprise systems (ES) can be understood as the de facto standard for holistic operational and managerial support within an organization. Most commonly ES are offered as commercial off-the-shelf packages, requiring customization in the user organization. This process is a complex and resource-intensive task, which often prevents small and midsize enterprises (SME) from undertaking configuration projects. Especially in the SME market independent software vendors provide pre-configured ES for a small customer base. The problem of ES configuration is shifted from the customer to the vendor, but remains critical. We argue that the yet unexplored link between process configuration and business document configuration must be closer examined as both types of configuration are closely tied to one another

The common presupposition of enterprise systems (ES) is that they lead to significant efficiency gains. However, this is only the case for well-implemented ES that are well-aligned with the organisation. The list of ES implementation failures is significant which is partly attributable to the insufficiently addressed fundamental problem of adapting an ES efficiently. As long as it is not intuitively possible to configure an ES, this problem will prevail because organisations have a non-generic character. A solution to this problem consists in re-thinking current practices of ES provision. This paper proposes a new approach based on configurable process models, which reflect ES functionalities. We provide in this paper a taxonomy of situations that can occur from a business perspective during process model configuration. This taxonomy is represented via so-called semantic configuration patterns. In the next step, we discuss so-called syntactic configuration patterns. This second type of configuration patterns implements the semantic configuration patterns for specific modelling techniques. We chose two popular process modelling languages in order to illustrate our approach.