This paper advocates for the integration of environmental aspects in computing curricula, with a focus on higher education. We created knowledge-based curriculum specifications in order to help teachers who wish to add knowledge foundation on computing impacts. This document lists topics and references that can be integrated into curricula. We implemented it in several higher education institutions. This paper reports on our experience and feedback. We also discuss recommendations to overcome obstacles that, from our experience, are often faced when modifying computing curricula to integrate environmental challenges.

We present Logical Information Systems (LIS). A LIS can be viewed as a schema-less database whose objects are described by logical formulas. Objects are automatically organized according to their logical description, and logical formulas can be used for representing both queries and navigation links. The key feature of a LIS is that it answers a query with a set of navigation links expressed in the same logic as the query. As navigation links are dynamically computed from any query, and can be used as query increments, it follows that querying and navigation steps can be combined in any order.We then present LISFS, a file-system implementation of a LIS, where objects are files or parts of files. This has the benefit to make LIS features available right now to existing applications. This implementation can easily be extended and specialized through a plug-in mechanism.Finally, we present some applications in the field of personal databases (e.g., music, images, emails) and in the field of software engineering.

The current trend in debugging and testing is to cross-check information collected during several executions. Jones et al., for example, propose to use the instruction coverage of passing and failing runs in order to visualize suspicious statements. This seems promising but lacks a formal justification. In this paper, we show that the method of Jones et al. can be re-interpreted as a data mining procedure. More particularly, they define an indicator which characterizes association rules between data. With this formal framework we are able to explain intrinsic limitations of the above indicator.

The study of garbage collection for a logic programming language machine has exhibited fundamental differences with the more popular functional programming garbage collection. These differences yield behaviours that cannot be observed with classical models. We give two new models, (one is determistic and the other stochastic) which take into account these behaviours. We argue that the stochastic model is also suitable for more classical garbage collector, and that it overcomes deterministic models for the study of the real-time property for parallel garbage collector. Finally, we argue that the methodology used to build and solve the stochastic model can be applied to the stochastic modeling of other systems.