AutoFlow: An automatic debugging tool for AspectJ software

Aspect-oriented programming (AOP) is gaining popu-larity with the wider adoption of languages such as As-pectJ. During AspectJ software evolution, when regression tests fail, it may be tedious for programmers to find out the failure-inducing changes by manually inspecting all code editing. To eliminate the expensive effort spent on debug-ging, we developed AutoFlow, an automatic debugging tool for AspectJ software. AutoFlow integrates the potential of delta debugging algorithm with the benefit of change im-pact analysis to narrow down the search for faulty changes. It first uses change impact analysis to identify a subset of re-sponsible changes for a failed test, then ranks these changes according to our proposed heuristic (indicating the likeli-hood that they may have contributed to the failure), and finally employs an improved delta debugging algorithm to determine a minimal set of faulty changes. The main fea-ture of AutoFlow is that it can automatically reduce a large portion of irrelevant changes in an early phase, and then locate faulty changes effectively.

Testing the Accuracy of Query Optimizers

ABSTRACT The accuracy of a query optimizer is intricately connected with a database system performance and its operational cost: the more accurate the optimizer's cost model, the better the resulting execution plans. Database application programmers and other practitioners have long provided anecdotal evidence that database systems differ widely with respect to the quality of their optimizers, yet, to date no formal method is available to database users to assess or refute such claims. In this paper, we develop a framework to quantify an optimizer's accuracy for a given workload. We make use of the fact that optimizers expose switches or hints that let users influence the plan choice and generate plans other than the default plan. Using these implements, we force the generation of multiple alternative plans for each test case, time the execution of all alternatives and rank the plans by their effective costs. We compare this ranking with the ranking of the estimated cost and compute a score for the accuracy of the optimizer. We present initial results of an anonymized comparisons for several major commercial database systems demonstrating that there are in fact substantial differences between systems. We also suggest ways to incorporate this knowledge into the commercial development process

Scaling of pressure-induced and doping-induced superconductivity in the Ca10(PtnAs8)(Fe2As2)5 arsenides

The Ca10(PtnAs8)(Fe2As2)5 (n=3,4) compounds are a new type of iron pnictide superconductor whose structures consist of stacking Ca-PtnAs8-Ca-Fe2As2 layers in a unit cell. When n=3 (the 10-3-8 phase), the undoped compound is an antiferromagnetic (AFM) semiconductor, while, when n=4 (the 10-4-8 phase), the undoped compound is a superconductor (Tc=26K), a difference that has been attributed to the electronic character of the PtnAs8 intermediary layers. Here we report high-pressure studies on 10-3-8 and 10-4-8, using a combination of in-situ resistance, magnetic susceptibility, Hall coefficient and X-ray diffraction measurements. We find that the AFM order in undoped 10-3-8 is suppressed completely at 3.5 GPa and that superconductivity then appears in the 3.5-7 GPa pressure range with a classic dome-like behavior. In contrast, Tc in the 10-4-8 phase displays a monotonic decrease with increasing pressure. Our results allow for the establishment of a unique correspondence between pressure-induced and doping-induced superconductivity in the high-Tc iron pnictides, and also points the way to an effective strategy for finding new high-Tc superconductors.Comment: 25 pages, 5 figure

The role of 245 phase in alkaline iron selenide superconductors revealed by high pressure studies

Here we show that a pressure of about 8 GPa suppresses both the vacancy order and the insulating phase, and a further increase of the pressure to about 18 GPa induces a second transition or crossover. No superconductivity has been found in compressed insulating 245 phase. The metallic phase in the intermediate pressure range has a distinct behavior in the transport property, which is also observed in the superconducting sample. We interpret this intermediate metal as an orbital selective Mott phase (OSMP). Our results suggest that the OSMP provides the physical pathway connecting the insulating and superconducting phases of these iron selenide materials.Comment: 32 pages, 4 figure