Faster Algorithms for Weighted Recursive State Machines

Pushdown systems (PDSs) and recursive state machines (RSMs), which are linearly equivalent, are standard models for interprocedural analysis. Yet RSMs are more convenient as they (a) explicitly model function calls and returns, and (b) specify many natural parameters for algorithmic analysis, e.g., the number of entries and exits. We consider a general framework where RSM transitions are labeled from a semiring and path properties are algebraic with semiring operations, which can model, e.g., interprocedural reachability and dataflow analysis problems. Our main contributions are new algorithms for several fundamental problems. As compared to a direct translation of RSMs to PDSs and the best-known existing bounds of PDSs, our analysis algorithm improves the complexity for finite-height semirings (that subsumes reachability and standard dataflow properties). We further consider the problem of extracting distance values from the representation structures computed by our algorithm, and give efficient algorithms that distinguish the complexity of a one-time preprocessing from the complexity of each individual query. Another advantage of our algorithm is that our improvements carry over to the concurrent setting, where we improve the best-known complexity for the context-bounded analysis of concurrent RSMs. Finally, we provide a prototype implementation that gives a significant speed-up on several benchmarks from the SLAM/SDV project

Graph-Based Shape Analysis Beyond Context-Freeness

We develop a shape analysis for reasoning about relational properties of data structures. Both the concrete and the abstract domain are represented by hypergraphs. The analysis is parameterized by user-supplied indexed graph grammars to guide concretization and abstraction. This novel extension of context-free graph grammars is powerful enough to model complex data structures such as balanced binary trees with parent pointers, while preserving most desirable properties of context-free graph grammars. One strength of our analysis is that no artifacts apart from grammars are required from the user; it thus offers a high degree of automation. We implemented our analysis and successfully applied it to various programs manipulating AVL trees, (doubly-linked) lists, and combinations of both

Illness Beliefs Predict Mortality in Patients with Diabetic Foot Ulcers

Background - Patients’ illness beliefs have been associated with glycaemic control in diabetes and survival in other conditions. Objective - We examined whether illness beliefs independently predicted survival in patients with diabetes and foot ulceration. Methods - Patients (n = 169) were recruited between 2002 and 2007. Data on illness beliefs were collected at baseline. Data on survival were extracted on 1st November 2011. Number of days survived reflected the number of days from date of recruitment to 1st November 2011. Results - Cox regressions examined the predictors of time to death and identified ischemia and identity beliefs (beliefs regarding symptoms associated with foot ulceration) as significant predictors of time to death. Conclusions - Our data indicate that illness beliefs have a significant independent effect on survival in patients with diabetes and foot ulceration. These findings suggest that illness beliefs could improve our understanding of mortality risk in this patient group and could also be the basis for future therapeutic interventions to improve survival

System dependence graphs in sequential Erlang

The system dependence graph (SDG) is a data structure used in the imperative paradigm for different static analysis, and particularly, for program slicing. Program slicing allows us to determine the part of a program (called slice) that influences a given variable of interest. Thanks to the SDG, we can produce precise slices for interprocedural programs. Unfortunately, the SDG cannot be used in the functional paradigm due to important features that are not considered in this formalism (e.g., pattern matching, higher-order, composite expressions, etc.). In this work we propose the first adaptation of the SDG to a functional language facing these problems. We take Erlang as the host language and we adapt the algorithms used to slice the SDG to produce precise slices of Erlang interprocedural programs. As a proof-of-concept, we have implemented a program slicer for Erlang based on our SDGs.This work has been partially supported by the Spanish Ministerio de Ciencia e Innovaci´on under grant TIN2008-06622-C03-02 and by the Generalitat Valenciana under grant PROMETEO/2011/052. Salvador Tamarit was partially supported by the Spanish MICINN under FPI grant BES-2009-015019Silva Galiana, JF.; Tamarit Muñoz, S.; Tomás Franco, C. (2012). System dependence graphs in sequential Erlang. En Fundamental Approaches to Software Engineering. Springer Verlag (Germany). 486-500. https://doi.org/10.1007/978-3-642-28872-2_33S486500Agrawal, H., Horgan, J.R.: Dynamic program slicing. In: Programming Language Design and Implementation (PLDI), pp. 246–256 (1990)Brown, C.: Tool Support for Refactoring Haskell Programs. PhD thesis, School of Computing, University of Kent, Canterbury, Kent, UK (2008)Cheda, D., Silva, J., Vidal, G.: Static slicing of rewrite systems. Electron. Notes Theor. Comput. Sci. 177, 123–136 (2007)Ferrante, J., Ottenstein, K.J., Warren, J.D.: The Program Dependence Graph and Its Use in Optimization. ACM Transactions on Programming Languages and Systems 9(3), 319–349 (1987)Field, J., Ramalingam, G., Tip, F.: Parametric program slicing. In: Proceedings of the 22nd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL 1995, pp. 379–392. ACM, New York (1995)Horwitz, S., Reps, T., Binkley, D.: Interprocedural slicing using dependence graphs. ACM Transactions Programming Languages and Systems 12(1), 26–60 (1990)Korel, B., Laski, J.: Dynamic Program Slicing. Information Processing Letters 29(3), 155–163 (1988)Larsen, L., Harrold, M.J.: Slicing object-oriented software. In: Proceedings of the 18th International Conference on Software Engineering, ICSE 1996, pp. 495–505. IEEE Computer Society, Washington, DC (1996)Liang, D., Harrold, M.J.: Slicing objects using system dependence graphs. In: Proceedings of the International Conference on Software Maintenance, ICSM 1998, pp. 358–367. IEEE Computer Society, Washington, DC (1998)Lindahl, T., Sagonas, K.F.: Typer: a type annotator of erlang code. In: Sagonas, K.F., Armstrong, J. (eds.) Erlang Workshop, pp. 17–25. ACM (2005)Lindahl, T., Sagonas, K.F.: Practical type inference based on success typings. In: Bossi, A., Maher, M.J. (eds.) PPDP, pp. 167–178. ACM (2006)Ochoa, C., Silva, J., Vidal, G.: Dynamic slicing based on redex trails. In: Proceedings of the 2004 ACM SIGPLAN Symposium on Partial Evaluation and Semantics-Based Program Manipulation, PEPM 2004, pp. 123–134. ACM, New York (2004)Reps, T., Turnidge, T.: Program Specialization via Program Slicing. In: Danvy, O., Thiemann, P., Glück, R. (eds.) Dagstuhl Seminar 1996. LNCS, vol. 1110, pp. 409–429. Springer, Heidelberg (1996)Rodrigues, N.F., Barbosa, L.S.: Component identification through program slicing. In: Proc. of Formal Aspects of Component Software (FACS 2005). Elsevier ENTCS, pp. 291–304. Elsevier (2005)Tip, F.: A survey of program slicing techniques. Journal of Programming Languages 3(3), 121–189 (1995)Tóth, M., Bozó, I., Horváth, Z., Lövei, L., Tejfel, M., Kozsik, T.: Impact Analysis of Erlang Programs Using Behaviour Dependency Graphs. In: Horváth, Z., Plasmeijer, R., Zsók, V. (eds.) CEFP 2009. LNCS, vol. 6299, pp. 372–390. Springer, Heidelberg (2010)Walkinshaw, N., Roper, M., Wood, M., Roper, N.W.M.: The java system dependence graph. In: Third IEEE International Workshop on Source Code Analysis and Manipulation, p. 5 (2003)Weiser, M.: Program Slicing. In: Proceedings of the 5th International Conference on Software Engineering, pp. 439–449. IEEE Press (1981)Widera, M.: Flow graphs for testing sequential erlang programs. In: Proceedings of the 2004 ACM SIGPLAN Workshop on Erlang, ERLANG 2004, pp. 48–53. ACM, New York (2004)Widera, M., Informatik, F.: Concurrent erlang flow graphs. In: Proceedings of the Erlang/OTP User Conference (2005)Zhao, J.: Slicing aspect-oriented software. In: Proceedings of the 10th International Workshop on Program Comprehension, IWPC 2002, pp. 251–260. IEEE Computer Society, Washington, DC (2002

Interprocedural shape analysis for effectively cutpoint-free programs

Abstract. We present a framework for local interprocedural shape analysis that computes procedure summaries as transformers of procedure-local heaps (the parts of the heap that the procedure may reach). A main challenge in procedurelocal shape analysis is the handling of cutpoints, objects that separate the input heap of an invoked procedure from the rest of the heap, which-from the viewpoint of that invocation-is non-accessible and immutable. In this paper, we limit our attention to effectively cutpoint-free programsprograms in which the only objects that separate the callee's heap from the rest of the heap, when considering live reference fields, are the ones pointed to by the actual parameters of the invocation. This limitation (and certain variations of it, which we also describe) simplifies the local-reasoning about procedure calls because the analysis needs not track cutpoints. Furthermore, our analysis (conservatively) verifies that a program is effectively cutpoint-free

Cell Migration in the Immune System: the Evolving Inter-Related Roles of Adhesion Molecules and Proteinases

Leukocyte extravasation into perivascular tissue during inflammation and lymphocyte homing to lymphoid organs involve transient adhesion to the vessel endothelium, followed by transmigration through the endothelial cell (EC) layer and establishment of residency at the tissue site for a period of time. In these processes, leukocytes undergo multiple attachments to, and detachments from, the vessel-lining endothelial cells, prior to transendothelial cell migration. Transmigrating leukocytes must traverse a subendothelial basement membrane en route to perivascular tissues and utilize enzymes known as matrix metalloproteinases to make selective clips in the extracellular matrix components of the basement membrane. This review will focus on the evidence for a link between adhesion of leukocytes to endothelial cells, the induction of matrix metalloproteinases mediated by engagement of adhesion receptors on leukocytes, and the ability to utilize these matrix metalloproteinases to facilitate leukocyte invasion of tissues. Leukocytes with invasive phenotypes express high levels of MMPs, and expression of MMPs enhances the migratory and invasive properties of these cells. Furthermore, MMPs may be used by lymphocytes to proteolytically cleave molecules such as adhesion receptors and membrane bound cytokines, increasing their efficiency in the immune response. Engagement of leukocyte adhesion receptors may modulate adhesive (modulation of integrin affinities and expression), synthetic (proteinase induction and activation), and surface organization (clustering of proteolyric complexes) behaviors of invasive leukocytes. Elucidation of these pathways will lead to better understanding of controlling mechanisms in order to develop rational therapeutic approaches in the areas of inflammation and autoimmunity

Software Model Checking with Explicit Scheduler and Symbolic Threads

In many practical application domains, the software is organized into a set of threads, whose activation is exclusive and controlled by a cooperative scheduling policy: threads execute, without any interruption, until they either terminate or yield the control explicitly to the scheduler. The formal verification of such software poses significant challenges. On the one side, each thread may have infinite state space, and might call for abstraction. On the other side, the scheduling policy is often important for correctness, and an approach based on abstracting the scheduler may result in loss of precision and false positives. Unfortunately, the translation of the problem into a purely sequential software model checking problem turns out to be highly inefficient for the available technologies. We propose a software model checking technique that exploits the intrinsic structure of these programs. Each thread is translated into a separate sequential program and explored symbolically with lazy abstraction, while the overall verification is orchestrated by the direct execution of the scheduler. The approach is optimized by filtering the exploration of the scheduler with the integration of partial-order reduction. The technique, called ESST (Explicit Scheduler, Symbolic Threads) has been implemented and experimentally evaluated on a significant set of benchmarks. The results demonstrate that ESST technique is way more effective than software model checking applied to the sequentialized programs, and that partial-order reduction can lead to further performance improvements.Comment: 40 pages, 10 figures, accepted for publication in journal of logical methods in computer scienc

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data

Background and objective: As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code). Methods: We show step-by-step how to implement the analytics pipeline for the question: ‘In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?’. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA. Results: Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Conclusion: Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world.</p

Datalog-Based program analysis with BES and RWL

This paper describes two techniques for Datalog query evaluation and their application to object-oriented program analysis. The first technique transforms Datalog programs into an implicit Boolean Equation System (Bes) that can then be solved by using linear-time complexity algorithms that are available in existing, general purpose verification toolboxes such as Cadp. In order to improve scalability and to enable analyses involving advanced meta-programming features, we develop a second methodology that transforms Datalog programs into rewriting logic (Rwl) theories. This method takes advantage of the preeminent features and facilities that are available within the high-performance system Maude, which provides a very efficient implementation of Rwl. We provide evidence of the practicality of both approaches by reporting on some experiments with a number of real-world Datalog-based analyses. © 2011 Springer-Verlag.This work has been partially supported by the eu(feder), the Spanish mec/micinn under grants tin2007-68093-C02 and tin2010-21062-C02-02, and the Generalitat Valenciana under grant Emergentes gv/2009/024. M.A.Feliu was partially supported by the Spanish mec fpu grant AP2008-00608.Alpuente Frasnedo, M.; Feliú Gabaldón, MA.; Joubert, C.; Villanueva García, A. (2011). Datalog-Based program analysis with BES and RWL. En Datalog Reloaded. Springer Verlag (Germany). 6702:1-20. https://doi.org/10.1007/978-3-642-24206-9_1S1206702Afrati, F.N., Ullman, J.D.: Optimizing joins in a map-reduce environment. In: Manolescu, I., Spaccapietra, S., Teubner, J., Kitsuregawa, M., Léger, A., Naumann, F., Ailamaki, A., Özcan, F. (eds.) EDBT. ACM International Conference Proceeding Series, vol. 426, pp. 99–110. 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