This paper presents an optimal constraint programming approach for the open-shop scheduling problem, which integrates recent constraint propagation and branching techniques with new upper bound heuristics. Randomized restart policies combined with nogood recording allow us to search diversification and learning from restarts. This approach is compared with the best-known metaheuristics and exact algorithms, and it shows better results on a wide range of benchmark instances.

To understand the behavior of a program, a maintainer reads some code, asks a question about this code, conjectures an answer, and searches the code and the documentation for confirmation of her conjecture. However, the confirmation of the conjecture can be error-prone and time-consuming because the maintainer has only static information at her disposal. She would benefit from dynamic information. In this paper, we present Caffeine, an assistant that helps the maintainer in checking her conjecture about the behavior of a Java program. Our assistant is a dynamic analysis tool that uses the Java platform debug architecture to generate a trace, i.e., an execution history, and a Prolog engine to perform queries over the trace. We present a usage scenario based on the n-queens problem, and two real-life examples based on the Singleton design pattern and on the composition relationship.

Design patterns ease the designing, understanding, and re-engineering of software. Achieving a well-designed piece of software requires a deep understanding and a good practice of design patterns. Understanding existing software relies on the ability to identify architectural forms resulting from the implementation of design patterns. Maintaining software involves spotting places that can be improved by using better design decisions, like those advocated by design patterns. Nevertheless, there is a lack of tools automatizing the use of design patterns to achieve well-designed pieces of software, to identify recurrent architectural forms, and to maintain software. We present a set of tools and techniques to help OO software practitioners design, understand, and re-engineer a piece of software using design-patterns. A first prototype tool, PATTERNS-BOX, provides assistance in designing the architecture of a new piece of software, while a second prototype tool, PTIDEJ, identifies design patterns used in an existing one. These tools, in combination, support maintenance by highlighting defects in an existing design, and by suggesting and applying corrections based on widely-accepted design pattern solutions.