Platinum: Reusing Constraint Solutions in Bounded Analysis of Relational Logic

Alloy is a light weight specification language based on relational logic, with an analysis engine that relies on SAT solvers to automate bounded verifica- tion of specifications. In spite of its strengths, the reliance of the Alloy Analyzer on computationally heavy solvers means that it can take a significant amount of time to verify software properties, even within limited bounds. This challenge is exacerbated by the ever-evolving nature of complex software systems. This paper presents PLATINUM, a technique for efficient analysis of evolving Alloy specifications, that recognizes opportunities for constraint reduction and reuse of previously identified constraint solutions. The insight behind PLATINUM is that formula constraints recur often during the analysis of a single specification and across its revisions, and constraint solutions can be reused over sequences of anal- yses performed on evolving specifications. Our empirical results show that PLAT- INUM substantially reduces (by 66.4% on average) the analysis time required on specifications extracted from real-world software systems

Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks

In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO) algorithm for the dynamic alliance (DPSO-DA) with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm’s ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms

Bounded Exhaustive Search of Alloy Specification Repairs

The rising popularity of declarative languages and the hard to debug nature thereof have motivated the need for applicable, automated repair techniques for such languages. However, despite significant advances in program repair for imperative languages, there is a dearth of repair techniques for declarative languages. We present BeAFix, an automated repair technique for faulty models written in Alloy, a first-order relational logic language. BeAFix has a number of distinguishing features. Firstly, it supports any kind of oracle, including assertions typically found in formal specifications, as well as “specification tests”. This is important since unit tests, widely available for programs, are not typically found in formal specifications. Secondly, given a defined set of mutation operations, a set of suspicious expressions and a maximum number of mutations to apply per expression, BeAFix's bounded-exhaustive approach will either find a fix, or guarantee that such a fix is not possible, within the provided bounds. With respect to fault localization, BeAFix is not tightly integrated to any specific technique. In fact, our technique is independent of the fault localization technique used, and the fault localization is run only once before the repair process begins. To support a bounded-exhaustive approach while keeping repair times reasonable, sound state pruning techniques (i.e., those that guarantee that no valid fixes are removed) are introduced. When a faulty model has more than one suspicious expression, we use both syntactic analysis and dynamically generated scenario-based assertions to check the feasibility of a particular repair candidate. A failing check will determine that this candidate would never lead to a fully repaired model, allowing BeAFix to prune significant parts of the search space. We evaluated our technique on two Alloy benchmarks, including one previously used in a state-of-the-art technique for Alloy repair. The results show that BeAFix is able to repair thousands of real-world faulty models, corroborating its ability to effectively, and efficiently generate correct repairs while also being less prone to overfitting than previous techniques.Sociedad Argentina de Informática e Investigación Operativ

ATR: template-based repair for Alloy specifications

Automatic Program Repair (APR) is a practical research topic that studies techniques to automatically repair programs to fix bugs. Most existing APR techniques are designed for imperative programming languages, such as C and Java, and rely on analyzing correct and incorrect executions of programs to identify and repair suspicious statements. We introduce a new APR approach for software specifications written in the Alloy declarative language, where specifications are not “executed”, but rather converted into logical formulas and analyzed using backend constraint solvers, to find specification instances and counterexamples to assertions. We present ATR, a technique that takes as input an Alloy specification with some violated assertion and returns a repaired specification that satisfies the assertion. The key ideas are (i) analyzing the differences between counterexamples that do not satisfy the assertion and instances that do satisfy the assertion to guide the repair and (ii) generating repair candidates from specific templates and pruning the space of repair candidates using the counterexamples and satisfying instances.Experimental results using existing large Alloy benchmarks show that ATR is effective in generating complex repairs. ATR repairs 66.3% of 1974 fault specifications, including specification repairs that cannot be handled by existing Alloy repair techniques. ATR and all benchmarks are open-source and available in the following Github repository: https://github.com/guolong-zheng/atmprep. This work was accepted for publication at 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2022) on July 2022.Sociedad Argentina de Informática e Investigación Operativ

FLACK: Counterexample-Guided Fault Localization for Alloy Models

Alloy is a specification language that has been used in a wide range of applications, such as program verification, test case generation, IoT and Android security, etc. Unlike imperative languages, such as C or Java, Alloy is declarative, which describes the logic of a computation without describing its control flow and does not generate traces during the execution. Thus, traditional fault localization techniques developed for imperative programs based on analyzing the control flows of passing and failing tests do not directly apply to Alloy. To aid developers in debugging Alloy models, we develop FLACK, a tool to automatically localize Alloy buggy expressions. Given an Alloy model with violated assertions, FLACK automatically outputs a ranking list of expressions based on their spaciousness to the assertions violations. For each assertion, FLACK first queries the Alloy analyzer for counterexamples, i.e. instances of the model that violate the asserted property. FLACK then uses a Partial Max-SAT (PMAXSAT) solver to find instances that satisfy the asserted property and are most similar to the counterexamples. FLACK then identifies the relations and atoms that are different between the counterexamples and the satisfying instances. The differences illustrate how the counterexamples violate the assertion. The PMAXSAT solver guarantees that these differences are “minimal”, containing only essential information related to the assertion violation. By finding expressions most related to these differences, FLACK identifies the potential expressions causing the assertion violation. FLACK is different than the state of the art on Alloy fault localization in that it does not rely on unit tests which are not commonly found accompanying Alloy models. Instead, FLACK relies on assertions and constraint solvers to obtain counterexamples and satisfying instances, which are the main underlying technology in Alloy and commonly used by the Alloy developers.Sociedad Argentina de Informática e Investigación Operativ

Enhanced electrical and thermal conductivities of 3D-SiC(rGO, G x ) PDCs based on polycarbosilane-vinyltriethoxysilane-graphene oxide (PCS-VTES-GO) precursor containing graphene fillers

Abstract(#br)Lightweight 3D-SiC(rGO, G x ) PDCs were fabricated from polycarbosilane-vinyltriethoxysilane-graphene oxide (PCS-VTES-GO) precursor added by different amounts of graphene fillers via direct cold molding and pyrolysis at 1400 °C in an easy manner. Results reveal that SiC(rGO, G x ) PDCs consist of β-SiC nanocrystals homogeneously embedded within amorphous SiO x C y /C free , and graphene is well compatible with SiO x C y /C free for void-free bonded interface, efficiently delaying decomposition of SiO x C y phase into β-SiC. The nanocomposite structure provides an ingenious strategy for constructing complexes with good integrity, high ceramic yield, excellent thermal stability, high electrical and thermal conductivities. This improvement is primarily attributed to the presence of graphene with considerably increasing electric-charge carriers and wider phonon-channel. Such 3D-SiC(rGO, G 20% ) PDCs possess satisfying hardness (12.02 GPa), high electrical conductivity (23.82 S cm −1 ) and thermal conductivity (7.47 W m −1 K −1 ), which make them attractive candidates for microelectromechanical systems (MEMS) devices, energy storage/conversion systems and high precision components, etc