During the life span of large software projects, developers often apply the same code changes to different code locations in slight variations. Since the application of these changes to all locations is time-consuming and error-prone, tools exist that learn change patterns from input examples, search for possible pattern applications, and generate corresponding recommendations. In many cases, the generated recommendations are syntactically or semantically wrong due to code movements in the input examples. Thus, they are of low accuracy and developers cannot directly copy them into their projects without adjustments.We present the Accurate REcommendation System (ARES) that achieves a higher accuracy than other tools because its algorithms take care of code movements when creating patterns and recommendations. On average, the recommendations by ARES have an accuracy of 96% with respect to code changes that developers have manually performed in commits of source code archives. At the same time ARES achieves precision and recall values that are on par with other tools.

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Software repositories that provide a basis for software comprehension or reengineering tools usually have to represent a huge number of documents of different types bound into a web of many kinds of relationships. The flexibility and the structural properties of a software repository are crucial for its use.This paper presents a repository approach that allows to set up, fill and update a software repository where the documents are represented as a highly integrated structure. The repository schema is described by a user defined, object based conceptual model. The integration of new documents into the existing repository is described by declarative rules. The repository was implemented as part of the GUPRO project.

Bit-vector-based program synthesis is an important building block of state-of-the-art techniques in computer programming. Some of these techniques do not only rely on a synthesizer's ability to return an appropriate program if it exists but also require a synthesizer to detect if there is no such program at all in the entire search space (i.e., the problem is infeasible), which is a computationally demanding task.In this paper, we propose an approach to quickly identify some synthesis problems as infeasible. We observe that a specification function encodes dependencies between input and output bits that a correct program must satisfy. To exploit this fact, we present approximate analyses of essential bits and use them in two novel algorithms to check if a synthesis problem is infeasible. Our experiments show that adding our technique to applications of bit vector synthesis can save up to 33% of their time.