A Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic

The Bernays-Sch\"onfinkel first-order logic fragment over simple linear real arithmetic constraints BS(SLR) is known to be decidable. We prove that BS(SLR) clause sets with both universally and existentially quantified verification conditions (conjectures) can be translated into BS(SLR) clause sets over a finite set of first-order constants. For the Horn case, we provide a Datalog hammer preserving validity and satisfiability. A toolchain from the BS(LRA) prover SPASS-SPL to the Datalog reasoner VLog establishes an effective way of deciding verification conditions in the Horn fragment. This is exemplified by the verification of supervisor code for a lane change assistant in a car and of an electronic control unit for a supercharged combustion engine

A Sorted Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic

International audienceAbstract In a previous paper, we have shown that clause sets belonging to the Horn Bernays-Schönfinkel fragment over simple linear real arithmetic (HBS(SLR)) can be translated into HBS clause sets over a finite set of first-order constants. The translation preserves validity and satisfiability and it is still applicable if we extend our input with positive universally or existentially quantified verification conditions (conjectures). We call this translation a Datalog hammer. The combination of its implementation in SPASS-SPL with the Datalog reasoner VLog establishes an effective way of deciding verification conditions in the Horn fragment. We verify supervisor code for two examples: a lane change assistant in a car and an electronic control unit of a supercharged combustion engine. In this paper, we improve our Datalog hammer in several ways: we generalize it to mixed real-integer arithmetic and finite first-order sorts; we extend the class of acceptable inequalities beyond variable bounds and positively grounded inequalities; and we significantly reduce the size of the hammer output by a soft typing discipline. We call the result the sorted Datalog hammer. It not only allows us to handle more complex supervisor code and to model already considered supervisor code more concisely, but it also improves our performance on real world benchmark examples. Finally, we replace the before file-based interface between SPASS-SPL and VLog by a close coupling resulting in a single executable binary

A Sorted Datalog Hammer for Supervisor Verification Conditions Modulo Simple Linear Arithmetic

In a previous paper, we have shown that clause sets belonging to the HornBernays-Sch\"onfinkel fragment over simple linear real arithmetic (HBS(SLR))can be translated into HBS clause sets over a finite set of first-orderconstants. The translation preserves validity and satisfiability and it isstill applicable if we extend our input with positive universally orexistentially quantified verification conditions (conjectures). We call thistranslation a Datalog hammer. The combination of its implementation inSPASS-SPL with the Datalog reasoner VLog establishes an effective way ofdeciding verification conditions in the Horn fragment. We verify supervisorcode for two examples: a lane change assistant in a car and an electroniccontrol unit of a supercharged combustion engine. In this paper, we improve ourDatalog hammer in several ways: we generalize it to mixed real-integerarithmetic and finite first-order sorts; we extend the class of acceptableinequalities beyond variable bounds and positively grounded inequalities; andwe significantly reduce the size of the hammer output by a soft typingdiscipline. We call the result the sorted Datalog hammer. It not only allows usto handle more complex supervisor code and to model already consideredsupervisor code more concisely, but it also improves our performance on realworld benchmark examples. Finally, we replace the before file-based interfacebetween SPASS-SPL and VLog by a close coupling resulting in a single executablebinary.<br

The use of mesenchymal stem cells for cartilage repair and regeneration: a systematic review.

BACKGROUND: The management of articular cartilage defects presents many clinical challenges due to its avascular, aneural and alymphatic nature. Bone marrow stimulation techniques, such as microfracture, are the most frequently used method in clinical practice however the resulting mixed fibrocartilage tissue which is inferior to native hyaline cartilage. Other methods have shown promise but are far from perfect. There is an unmet need and growing interest in regenerative medicine and tissue engineering to improve the outcome for patients requiring cartilage repair. Many published reviews on cartilage repair only list human clinical trials, underestimating the wealth of basic sciences and animal studies that are precursors to future research. We therefore set out to perform a systematic review of the literature to assess the translation of stem cell therapy to explore what research had been carried out at each of the stages of translation from bench-top (in vitro), animal (pre-clinical) and human studies (clinical) and assemble an evidence-based cascade for the responsible introduction of stem cell therapy for cartilage defects. This review was conducted in accordance to PRISMA guidelines using CINHAL, MEDLINE, EMBASE, Scopus and Web of Knowledge databases from 1st January 1900 to 30th June 2015. In total, there were 2880 studies identified of which 252 studies were included for analysis (100 articles for in vitro studies, 111 studies for animal studies; and 31 studies for human studies). There was a huge variance in cell source in pre-clinical studies both of terms of animal used, location of harvest (fat, marrow, blood or synovium) and allogeneicity. The use of scaffolds, growth factors, number of cell passages and number of cells used was hugely heterogeneous. SHORT CONCLUSIONS: This review offers a comprehensive assessment of the evidence behind the translation of basic science to the clinical practice of cartilage repair. It has revealed a lack of connectivity between the in vitro, pre-clinical and human data and a patchwork quilt of synergistic evidence. Drivers for progress in this space are largely driven by patient demand, surgeon inquisition and a regulatory framework that is learning at the same pace as new developments take place