Input-dependency analysis for hard real-time software

The execution time of soft-ware for hard real-time systems must be predictable. Further safe and not overly pessimistic bounds for the worst-case execution time (WCET) must be computable. We conceived a programming strategy called WCET-oriented programming and a code transformation strategy, the single-path conversion, that aid programmers in producing code that meets these requirements. These strategies avoid respectively eliminate input-data dependencies in the code. The paper describes the formal analysis, based on abstract interpretation, that identifies input-data dependencies in the code and thus forms the basis for the strategies provided for hard real-time code development

Consumers' experiences and values in conventional and alternative medicine paradigms: a problem detection study (PDS)

Background: This study explored consumer perceptions of complementary and alternative medicine (CAM) and relationships with CAM and conventional medicine practitioners. A problem detection study (PDS) was used. The qualitative component to develop the questionnaire used a CAM consumer focus group to explore conventional and CAM paradigms in healthcare. 32 key issues, seven main themes, informed the questionnaire (the quantitative PDS component - 36 statements explored using five-point Likert scales.

Code analysis for temporal predictability

The execution time of software for hard real-time systems must be predictable. Further, safe and not overly pessimistic bounds for the worst-case execution time (WCET) must be computable. We conceived a programming strategy called WCET-oriented programming and a code transformation strategy, the single-path conversion, that aid programmers in producing code that meets these requirements. These strategies avoid and eliminate input-data dependencies in the code. The paper describes the formal analysis, based on abstract interpretation, that identifies input-data dependencies in the code and thus forms the basis for the strategies provided for hard real-time code development.Peer reviewe

Development of Parallel Algorithms in Data Field Haskell

. Data fields provide a flexible and highly general model for indexed collections of data. Data Field Haskell is a dialect of the functional language Haskell which provides an instance of data fields. We describe Data Field Haskell and exemplify how it can be used in the early phase of parallel program design. 1 Introduction Many computing applications require indexed data structures. The canonical indexed data structure is the array. However, for sparse, distributed applications, other, more dynamic indexed data structures are needed. It is desirable to develop such algorithms on a high level first, in order to get them right, since the low level data representations can be intricate. Data Field Haskell provides an instance of data fields -- a data type for general indexed structures. This Haskell dialect can be used for rapid prototyping of parallel computational algorithms which may involve sparse structures. Various versions of the data field model have been described elsew..