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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Using Datalog and Boolean Equation Systems for Program Analysis

This paper describes a powerful, fully automated method to evaluate Datalog queries by using Boolean Equation Systems (Bess), and its application to object-oriented program analysis. Datalog is used as a specification language for expressing complex interprocedural program analyses involving dynamically created objects. In our methodology, Datalog rules encoding a particular analysis together with a set of constraints (Datalog facts that are automatically extracted from program source code) are dynamically transformed into a Bes, whose local resolution corresponds to the demand-driven evaluation of the program analysis. This approach allows us to reuse existing general purpose verification toolboxes, such as Cadp, providing local Bes resolutions with linear-time complexity. Our evaluation technique has been implemented and successfully tested on several Java programs and Datalog analyses that demonstrate the feasibility of our approach

Decreasing sedentary behaviours in pre-adolescents using casual exergames at school

There are risks to too much sedentary behaviour, regardless of a person's level of physical activity, particularly for children. As exercise habits instilled during childhood are strong predictors of healthy lifestyles later in life, it is important that schools break up long sedentary periods with short periods of physical activity. Casual exergames are an appealing option for schools who wish to engage adolescents, and have been shown to provide exertion levels at recommended values, even when played for only 10 minutes. In this paper we describe a preliminary survey with teachers of a local school that informed the deployment of a casual exergame with a group of preadolescent students from the same school. We show that students preferred the game to traditional exercise, that the game was able to generate appropriate levels of exertion in pre-adolescents, and that students have a sophisticated understanding of the role of exercise in their lives. Overall, we establish the feasibility of casual exergames for combating sedentary behavior in preteen classrooms. © 2014 ACM

Using Datalog with binary decision diagrams for program analysis

Many problems in program analysis can be expressed naturally and concisely in a declarative language like Datalog. This makes it easy to specify new analyses or extend or compose existing analyses. However, previous implementations of declarative languages perform poorly compared with traditional implementations. This paper describes bddbddb, a BDD-Based Deductive DataBase, which implements the declarative language Datalog with stratified negation, totally-ordered finite domains and comparison operators. bddbddb uses binary decision diagrams (BDDs) to efficiently represent large relations. BDD operations take time proportional to the size of the data structure, not the number of tuples in a relation, which leads to fast execution times. bddbddb is an effective tool for implementing a large class of program analyses. We show that a context-insensitive points-to analysis implemented with bddbddb is about twice as fast as a carefully hand-tuned version. The use of BDDs also allows us to solve heretofore unsolved problems, like context-sensitive pointer analysis for large programs

.QL: Object-Oriented Queries Made Easy

These notes are an introduction to.QL, an object-oriented query language for any type of structured data. We illustrate the use of.QL in assessing software quality, namely to find bugs, to compute metrics and to enforce coding conventions. The class mechanism of.QL is discussed in depth, and we demonstrate how it can be used to build libraries of reusable queries