Scaling up algorithmic debugging with virtual execution trees

Declarative debugging is a powerful debugging technique that has been adapted to practically all programming languages. However, the technique suffers from important scalability problems in both time and memory. With realistic programs the huge size of the execution tree handled makes the debugging session impractical and too slow to be productive. In this work, we present a new architecture for declarative debuggers in which we adapt the technique to work with incomplete execution trees. This allows us to avoid the problem of loading the whole execution tree in main memory and solve the memory scalability problems. We also provide the technique with the ability to debug execution trees that are only partially generated. This allows the programmer to start the debugging session even before the execution tree is computed. This solves the time scalability problems. We have implemented the technique and show its practicality with several experiments conducted with real applications.Insa Cabrera, D.; Silva Galiana, JF. (2011). Scaling up algorithmic debugging with virtual execution trees. En Logic-Based Program Synthesis and Transformation. Springer Verlag (Germany). 6564:149-163. doi:10.1007/978-3-642-20551-4_10S1491636564Av-Ron, E.: Top-Down Diagnosis of Prolog Programs. PhD thesis, Weizmanm Institute (1984)Binks, D.: Declarative Debugging in Gödel. PhD thesis, University of Bristol (1995)Caballero, R.: A Declarative Debugger of Incorrect Answers for Constraint Functional-Logic Programs. In: Proc. of the 2005 ACM SIGPLAN Workshop on Curry and Functional Logic Programming (WCFLP 2005), pp. 8–13. ACM Press, New York (2005)Caballero, R.: Algorithmic Debugging of Java Programs. In: Proc. of the 2006 Workshop on Functional Logic Programming (WFLP 2006). Electronic Notes in Theoretical Computer Science, pp. 63–76 (2006)Caballero, R., Martí-Oliet, N., Riesco, A., Verdejo, A.: A declarative debugger for maude functional modules. Electronic Notes Theoretical Computer Science 238(3), 63–81 (2009)Davie, T., Chitil, O.: Hat-delta: One Right Does Make a Wrong. In: Seventh Symposium on Trends in Functional Programming, TFP 2006 (April 2006)Girgis, H., Jayaraman, B.: JavaDD: a Declarative Debugger for Java. Technical Report 2006-07, University at Buffalo (March 2006)Kokai, G., Nilson, J., Niss, C.: GIDTS: A Graphical Programming Environment for Prolog. In: Workshop on Program Analysis For Software Tools and Engineering (PASTE 1999), pp. 95–104. ACM Press, New York (1999)MacLarty, I.: Practical Declarative Debugging of Mercury Programs. PhD thesis, Department of Computer Science and Software Engineering, The University of Melbourne (2005)Sun Microsystems. Java Platform Debugger Architecture - JPDA (2010), http://java.sun.com/javase/technologies/core/toolsapis/jpda/Nilsson, H., Fritzson, P.: Algorithmic Debugging for Lazy Functional Languages. Journal of Functional Programming 4(3), 337–370 (1994)Shapiro, E.Y.: Algorithmic Program Debugging. MIT Press, Cambridge (1982)Silva, J.: An Empirical Evaluation of Algorithmic Debugging Strategies. Technical Report DSIC-II/10/09, UPV (2009), http://www.dsic.upv.es/~jsilva/research.htm#techsSilva, J.: Algorithmic debugging strategies. In: Proc. of International Symposium on Logic-based Program Synthesis and Transformation (LOPSTR 2006), pp. 134–140 (2006)Silva, J.: A Comparative Study of Algorithmic Debugging Strategies. In: Puebla, G. (ed.) LOPSTR 2006. LNCS, vol. 4407, pp. 143–159. Springer, Heidelberg (2007

On avoiding redundancy in inductive logic programming

ILP systems induce rst-order clausal theories performing asearch through very large hypotheses spaces containing redundant hypotheses.The generation of redundant hypotheses may prevent the systemsfrom nding good models and increases the time to induce them.In this paper we propose a classication of hypotheses redundancy andshow how expert knowledge can be provided to an ILP system to avoidit. Experimental results show that the number of hypotheses generatedand execution time are reduced when expert knowledge is used to avoidredundancy

Operation and performance of the ATLAS semiconductor tracker

The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74±0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, δ-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations

The performance of the jet trigger for the ATLAS detector during 2011 data taking

The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction

Measurements of fiducial cross-sections for t\bart production with one or two additional b-jets in pp collisions at √s =8 TeVusing the ATLAS detector

Fiducial cross-sections for $t\bar{t}$ production with one or two additional $b$-jets are reported, using an integrated luminosity of 20.3 fb$^{-1}$ of proton--proton collisions at a centre-of-mass energy of 8 TeV at the Large Hadron Collider, collected with the ATLAS detector. The cross-section times branching ratio for $t\bar{t}$ events with at least one additional $b$-jet is measured to be 950 $\pm$ 70 (stat.) $^{+240}_{-190}$ (syst.) fb in the lepton-plus-jets channel and 50 $\pm$ 10 (stat.) $^{+15}_{-10}$ (syst.) fb in the $e \mu$ channel. The cross-section times branching ratio for events with at least two additional $b$-jets is measured to be 19.3 $\pm$ 3.5 (stat.) $\pm$ 5.7 (syst.) fb in the dilepton channel ($e \mu$,\,$\mu\mu$, and \,$ee$) using a method based on tight selection criteria, and 13.5 $\pm$ 3.3 (stat.) $\pm$ 3.6 (syst.) fb using a looser selection that allows the background normalisation to be extracted from data. The latter method also measures a value of 1.30 $\pm$ 0.33 (stat.) $\pm$ 0.28 (syst.)\% for the ratio of $t\bar{t}$ production with two additional $b$-jets to $t\bar{t}$ production with any two additional jets. All measurements are in good agreement with recent theory predictions.Comment: 41 pages plus author list + cover page (58 total), 9 Figures, 16 tables, submitted to EPJC, all figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/TOPQ-2014-10