Non-deterministic Behavior Research Articles

Efficient parallel determinacy race detection for two-dimensional dags

A program is said to have a determinacy race if logically parallel parts of a program access the same memory location and one of the accesses is a write. These races are generally bugs in the program since they lead to non-deterministic program behavior --- different schedules of the program can lead to different results. Most prior work on detecting these races focuses on a subclass of programs with fork-join parallelism. This paper presents a race-detection algorithm, 2D-Order, for detecting races in a more general class of programs, namely programs whose dependence structure can be represented as planar dags embedded in 2D grids. Such dependence structures arise from programs that use pipelined parallelism or dynamic programming recurrences. Given a computation with T 1 work and T ∞ span, 2D-Order executes it while also detecting races in O ( T 1 / P + T ∞ ) time on P processors, which is asymptotically optimal. We also implemented PRacer, a race-detection algorithm based on 2D-Order for Cilk-P, which is a language for expressing pipeline parallelism. Empirical results demonstrate that PRacer incurs reasonable overhead and exhibits scalability similar to the baseline (executions without race detection) when running on multiple cores.

Consistency-Aware Scheduling for Weakly Consistent Programs

Modern geo-replicated data stores provide high availability by relaxing the underlying consistency requirements. Programs layered over such data stores are called weakly consistent programs. Due to the reduced consistency requirements, they exhibit highly nondeterministic behaviors, some of which might violate program invariants. Therefore, implementing correct weakly consistent programs and reasoning about them is challenging. In this paper, we present a systematic scheduling approach that is aware of the underlying consistency model. Our approach dynamically explores all possible program behaviors allowed by the used data store consistency model, and it evaluates program invariants during the exploration. We implement the approach in a prototype model checker for Antidote, which is a causally consistent key-value data store with convergent con ict handling. We evaluate our tool on several benchmarks. The results show that our approach is e effective in detecting buggy behaviors in weakly consistent programs.

Affective Algorithm for Controlling Emotional Fluctuation of Artificial Investors in Stock Markets

This paper presents the design of an affective algorithm for implementing autonomous decision-making systems that incorporate an emotional stabilizer mechanism for the use in the stock market domain. Emotions have a direct influence on human decision-making processes. Non-deterministic behavior in humans can be partially explained by emotions. In this sense, an artificial emotion can be implemented as a synthetic abstraction derived from the observation of human emotions. This paper presents studies related to emotional stability and emotional regulation. However, to the best of our knowledge, it is not possible to identify studies that define a relationship between the regulation of artificial emotions and the decision effectiveness of autonomous decision-making systems, specifically for the stock market domain. With the aim to improve investment results in the stock market domain, a mechanism based on artificial emotions is presented that was designed as a single layer of decision criteria defined by both rational and emotional perspectives. Along with the proposal of an emotional stabilizer mechanism, different values of emotional bandwidths and emotional update rates were tested, aiming to explore the degree of influence of these parameters on the effectiveness of investment decisions made by artificial investors. Our proposal considers the definition of an experimental scenario based on official data from the New York Stock Exchange. The results are promising and include a linear regression analysis. The test results suggest that the use of autonomous affective decision-making systems with emotional stabilization can improve the effectiveness of the decision made.

Supervisor Aware Service Composition Framework: An Implementation and Evaluation

In our previous work (Atampore et al., 2016b), we developed a novel supervisory control framework for automated composition of Web services. In the proposed framework, we modeled services that exchange messages and exhibit nondeterministic (runtime-dependent) behaviours based on runtime input. The objective is to synthesize a supervisor that interacts with a given set of Web services through messages to guarantee that a given specification is satisfied. The framework employs Labelled Transition Systems (LTSs) equipped with guards and data variables to model Web services and provides a technique to synthesize a controller. We modeled the interactions of services asynchronously and we used the guards and data variables to express certain preconditions which are then propagated from the system requirements through the overall composite service. In this paper, first, we present a prototype implementation of our automated web service composition framework proposed in our previous paper into a tool support: The implementation involves the following: (i) the translation of industrial Web service standard such as WS-BPEL in a formal language suitable for control synthesis; (ii) the implementation of all the proposed control synthesis algorithms in our previous work; (iii) the incorporation of runtime information into the supervisory control synthesis; and (iv) the translation of the formal language used in the synthesis back to its WS-BPEL equivalent. Second, we present the application and a preliminary evaluation of the proposed composition approach in terms of (i) its effectiveness for the generation of controllers for a composition problem and (ii) its applicability using two well-known small case studies.

Analysis and Control of Dynamic Reconfiguration Processes of Manufacturing Systems

Dynamic reconfiguration techniques can greatly improve the flexibility and reliability of manufacturing systems. However, different from static reconfigurable systems, system behavior during dynamic reconfiguration processes is quite complex due to possible concurrence of system structure changes and events inside unaltered components. This increases the difficulty in designing and developing dynamic reconfigurable systems. The current paper deals with the analysis and control of dynamic reconfiguration process of manufacturing systems from the perspective of discrete event systems. To this end, the authors improve the reconfigurable timed net condition/event systems formalism by assigning reconfiguration functions with extra permeating time, action ranges, and concurrent decision functions. As a consequence, nondeterministic behavior of a dynamic reconfigurable system during dynamic reconfigurations can be specified, while the system correctness, coherence, and safety during reconfigurations can be guaranteed. A reconfigurable manufacturing plant is used as a running example to illustrate the contribution of this paper.

The symbiosis of concurrency and verification: teaching and case studies

Concurrency is beginning to be accepted as a core knowledge area in the undergraduate CS curriculum—no longer isolated, for example, as a support mechanism in a module on operating systems or reserved as an advanced discipline for later study. Formal verification of system properties is often considered a difficult subject area, requiring significant mathematical knowledge and generally restricted to smaller systems employing sequential logic only. This paper presents materials, methods and experiences of teaching concurrency and verification as a unified subject, as early as possible in the curriculum, so that they become fundamental elements of our software engineering tool kit—to be used together every day as a matter of course. Concurrency and verification should live in symbiosis. Verification is essential for concurrent systems as testing becomes especially inadequate in the face of complex non-deterministic (and, therefore, hard to repeat) behaviours. Concurrency should simplify the expression of most scales and forms of computer system by reflecting the concurrency of the worlds in which they operate (and, therefore, have to model); simplified expression leads to simplified reasoning and, hence, verification. Our approach lets these skills be developed without requiring students to be trained in the underlying formal mathematics. Instead, we build on the work of those who have engineered that necessary mathematics into the concurrency models we use (CSP, {pi} -calculus), the model checker (FDR) that lets us explore and verify those systems, and the programming languages/libraries (occam-{pi}, Go, JCSP, ProcessJ) that let us design and build efficient executable systems within these models. This paper introduces a workflow methodology for the development and verification of concurrent systems; it also presents and reflects on two open-ended case studies, using this workflow, developed at the authors’ two universities. Concerns analysed include safety (don’t do bad things), liveness (do good things) and low probability deadlock (that testing fails to discover). The necessary technical background is given to make this paper self-contained and its work simple to reproduce and extend.

Comparative modelling and verification of Pthreads and Dthreads

AbstractThe POSIX threads (Pthreads) library is a thread API for C/C++ to control parallel threads and spawn concurrent process flows. Programming in Pthreads usually suffers from undesirable deadlock, data race, and race condition problems due to the potential nondeterministic execution behaviors between parallel threads. Dthreads, as another multithreading model that re‐implements Pthreads, was proposed by Liu et al for efficient deterministic multithreading. They found out that, under specific test cases, Dthreads can effectively prevent data races. However, no comparison test has been made with Pthreads.To perform a formal comparison between Pthreads and Dthreads over deadlocks, data races, and race conditions, in this paper, we adopt CSP (communicating sequential processes) as a formal model for specifying part of API functions in Pthreads and Dthreads and illustrate the model construction using 4 classical example programs. By feeding the models into the model checker PAT (process analysis toolkit), we have verified that deadlocks and data races exist in Pthreads, but do not exist in Dthreads, for the considered programs. We have also found that neither of them can prevent race conditions. Our comparative modelling and verification of Pthreads and Dthreads show that though Dthreads cannot prevent all the deadlock situations, shown by verification results of another 2 example programs, Dthreads is better than Pthreads on eliminating data races and preventing deadlocks. Considering limited scalability of Dthreads, we have introduced a new programming model to support coarse granularity in bank transfer. Our modelling is also extended by covering the synchronization operations in Liu et al work.

Energy-Efficient Computing With Probabilistic Magnetic Bits—Performance Modeling and Comparison Against Probabilistic CMOS Logic

This paper focuses on the design, performance modeling, and evaluation of probabilistic logic using superparamagnetic nanomagnets for which there exists a strong interplay between deterministic dynamics and intrinsic thermal noise. The switching element in the spin domain is chosen as the giant spin-Hall effect (GSHE) device that operates based on the dipolar coupling phenomenon in a two-magnet system to achieve low-energy ( $\approx ~1.3$ fJ/b) and low-power ( $\approx ~0.5~\mu $ W) switching characteristics. The use of spin currents on the order of a few tens of mA/ $\mu $ m2 in the subcritical regime to operate the GSHE device yields nondeterministic switching behavior with probability of correctness less than 100%. Therefore, the proposed technique allows us to trade off circuit accuracy for tremendous reduction in energy and power dissipation. In this paper, we identify the required dimensions and material parameters of the read–write units to ensure robust magnetic dipolar coupling for reliable operation of the GSHE switch. Then, through Monte Carlo simulations, we evaluate the probabilistic switching behavior of the GSHE switch as a function of the input spin current amplitude and pulsewidth for various orientations of the magnetization vectors. The delay of the GSHE switch is quantified using a probability distribution function owing to the randomness imparted to the dynamics by intrinsic thermal noise of the nanomagnets. The relationship between the probability of correctness and the energy dissipation of the GSHE switch is quantified. The results are extended to evaluate the performance and circuit error rate of complex logic gates, such as NAND and NOR, constructed using the GSHE switch. It is shown that unlike the probabilistic CMOS (PCMOS) logic, the circuit error rate in the GSHE logic becomes a function of the input vector combination and the prior state of the switch. These nuances are captured in the compact model of the circuit error rate of multiple-input GSHE logic developed in this paper. The performance of the probabilistic GSHE logic is compared with that of PCMOS logic at the 14 nm technology node. Since the noise generation process in PCMOS logic has a limited bandwidth of tens of megahertz and consumes tens of microwatt power, the peripheral circuitry becomes prohibitive. By utilizing the inherent thermal stochasticity, nanomagnets provide a clear advantage to implement probabilistic computing platform targeted toward error-tolerant applications such as those from the image processing and machine learning domains.

Modified stretched exponential model of computer system resources management limitations—The case of cache memory

In this paper we present some preliminary results in the field of computer systems management with relation to Tsallis thermostatistics and the ubiquitous problem of hardware limited resources. In the case of systems with non-deterministic behaviour, management of their resources is a key point that guarantees theirs acceptable performance and proper working. This is very wide problem that stands for many challenges in financial, transport, water and food, health, etc. areas. We focus on computer systems with attention paid to cache memory and propose to use an analytical model that is able to connect non-extensive entropy formalism, long-range dependencies, management of system resources and queuing theory. Obtained analytical results are related to the practical experiment showing interesting and valuable results.

Hybrid Algorithm Edge Detected DICOM Image Enhancement and Analysis based on Genetic Algorithm for Evolution and Best Fit Value

The segmentation of a DICOM standard medical image is a necessary technique which is essential for feature extraction, object edge detection and classification of the segments of the image. The DICOM image is partitioned based on the Hybrid ACO-CPM algorithm, based on the edges in the image, for analysis. The edges are seen as the boundaries within the image which differentiates different regions in the image. The factors that links to the boundary discontinuities that co-exists between the pixels of DICOM image, like texture, intensity and gradient are rendered redundant and are taken care with the application of the Hybrid ACO-CPM algorithm. DICOM image features correspond to that of meta-heuristic characteristics, which are considered during the application of Hybrid ACO-CPM algorithm. The results obtained from this non-deterministic behavior needs to be optimized over a large space called as the search space, wherein the lists of all possible solutions are provided. Each solution is to be marked as a value fit to be termed problematic and needs to be synthesized for an optimized solution. Among various techniques that provide solutions in obtaining an equitable optimization solution, Genetic Algorithms (GA) corroborates as one of the persuasive techniques in a large search space. In this paper we propose an efficient and effective workflow based on a methodology, that provides an overview of the image enhancement and object classification for a DICOM image using Genetic Algorithm (GA). The edge detected medical standard DICOM image obtained from the Hybrid ACO-CPM algorithm is modified with respect to critical edge data. With the application of GA methodology, the process of enhancing the image ultimately suffices by rendering an image suitable for a specific application with an improved visual quality of the segmented image. A Figure-of-Merit is constructed to differentiate between the image metrics and their best fit values obtained for the images with respect to the Ant Colony Optimization (ACO) algorithm and proposed Hybrid ACO-CPM algorithm, upon enhancing the images using GA

Denotational semantics of membrane systems by using complete metric spaces

In this paper we present a mathematical model for a class of membrane systems, emphasizing on constructions of the denotational semantics as fixed points over complete metric spaces (to describe the semantics of multiset rewriting) and metric powerdomains (to describe the nondeterministic behaviour). We use the continuation-passing style, a technique providing enough flexibility for handling the concept of maximal parallelism and for describing the specific interactions in a membrane system. An important feature of the denotational approach is that it provides a compositional view of the membrane systems. Moreover, the semantics can be implemented naturally in a functional programming language; the implementation in Haskell is provided, and it is freely available for software experiments.

An exact schedulability test for fixed-priority preemptive mixed-criticality real-time systems

The current literature of fixed-priority scheduling algorithms relies on sufficient tests to determine if a set of mixed-criticality sporadic tasks is schedulable on a single processor. The drawback of these safe tests is their pessimism, a matter that could be solved if an exact schedulability analysis is used. However, because of the non-deterministic behavior of tasks in the mentioned setups, exact quantification of worst-case response times, needed for the test, is a difficult problem; more precisely, such a quantification needs evaluation of enormous sequences of job executions. The core problem is thus to merge such sequences to make the analysis practical. This paper, for the first time, gives an algorithm for exact worst-case response time characterization of mixed-criticality sporadic real-time tasks executing according to a given fixed-priority scheduler. We use a set of techniques which carefully consider the task properties and their relation to the worst scenarios to prune the analysis state space. We also show an interesting result that if an exact schedulability test is used, the Audsley's optimal priority assignment algorithm is not applicable to the mixed-criticality case. Accordingly, we need new priority assignment algorithms to work with the exact test; we give a simple task priority assignment algorithm to this aim. The performance of the proposed exact test (in terms of time complexity) is examined and the effectiveness of some heuristic priority assignment algorithms using the test (in terms of the ratio of task sets which are deemed schedulable) are compared.

Formal analysis and evaluation of the back-off procedure in IEEE802.11P VANET

The back-off procedure is one of the media access control technologies in 802.11P communication protocol. It plays an important role in avoiding message collisions and allocating channel resources. Formal methods are effective approaches for studying the performances of communication systems. In this paper, we establish a discrete time model for the back-off procedure. We use Markov Decision Processes (MDPs) to model the non-deterministic and probabilistic behaviors of the procedure, and use the probabilistic computation tree logic (PCTL) language to express different properties, which ensure that the discrete time model performs their basic functionality. Based on the model and PCTL specifications, we study the effect of contention window length on the number of senders in the neighborhood of given receivers, and that on the station’s expected cost required by the back-off procedure to successfully send packets. The variation of the window length may increase or decrease the maximum probability of correct transmissions within a time contention unit. We propose to use PRISM model checker to describe our proposed back-off procedure for IEEE802.11P protocol in vehicle network, and define different probability properties formulas to automatically verify the model and derive numerical results. The obtained results are helpful for justifying the values of the time contention unit.

Framework for a Calibration-Less Operation of Force Sensing Resistors at Different Temperatures

Force sensing resistors (FSRs) typically exhibit noticeably different responses from one device to another, and thus, an individual time-consuming calibration is required for each device. With the aim of speeding-up the development process of applications involving FSRs, a framework for a calibration-less operation of FSRs is presented. The method is based on performing periodic updates on the output voltage at null force and on employing a unique sensitivity value. Dynamic forces were applied at different temperatures to 96 FlexiForce sensors manufactured by Tekscan, Inc. The sensors exhibited rather constant sensitivity values at the temperatures spanning between 24 °C–60 °C. Conversely, the output voltage at null force showed a non-deterministic behavior when the temperature changed. The proposed method showed higher accuracy than the manufacturer method when measuring small forces, whereas the manufacturer method exhibited higher accuracy when working with large forces. Statistical tools were employed to fit the univariate sensitivity data to probability density functions and to assess the relationship between the FSR parameters and temperature. Finally, the effects of temperature changes over sensors’ hysteresis are discussed.

Fuzzy c-Least Medians clustering for discovery of web access patterns from web user sessions data

Mining web usage data of e-business organizations is essential to provide knowledge about clients’ web utilization patterns, which can help these businesses in landing at vital business choices. Because of non-deterministic web access behavior of web clients, web user session data is usually noisy and imperfect. Such imperfection has a negative impact on pattern discovery process. One of the real issues associated with the prevalently used Fuzzy c-Means (FCM) and Fuzzy c-Medoids (FCMdd) methods is that they are not robust against the noise, because a single outlier object could lead to a very different clustering result. In this research we propose a robust Fuzzy c-Least Medians (FCLMdn) clustering framework to deal with the user session data contaminated with noise and outlier user session objects, with the objective of improving the quality of the extracted patterns. To deal with the high dimensionality of user session data which may contain noise and outliers, a fuzzy set theoretic approach for assigning fuzzy weights to user sessions and associated URLs has been proposed. Our results clearly indicate that quality of user session clusters formed using FCLMdn algorithm is much better than those using FCM and FCMdd algorithms in terms of various cluster validity indices.

Automated Steering of Model-Based Test Oracles to Admit Real Program Behaviors

The test oracle —a judge of the correctness of the system under test (SUT)—is a major component of the testing process. Specifying test oracles is challenging for some domains, such as real-time embedded systems, where small changes in timing or sensory input may cause large behavioral differences. Models of such systems, often built for analysis and simulation, are appealing for reuse as test oracles. These models, however, typically represent an idealized system, abstracting away certain issues such as non-deterministic timing behavior and sensor noise. Thus, even with the same inputs, the model's behavior may fail to match an acceptable behavior of the SUT, leading to many false positives reported by the test oracle. We propose an automated steering framework that can adjust the behavior of the model to better match the behavior of the SUT to reduce the rate of false positives. This model steering is limited by a set of constraints (defining the differences in behavior that are acceptable) and is based on a search process attempting to minimize a dissimilarity metric. This framework allows non-deterministic, but bounded, behavioral differences, while preventing future mismatches by guiding the oracle—within limits—to match the execution of the SUT. Results show that steering significantly increases SUT-oracle conformance with minimal masking of real faults and, thus, has significant potential for reducing false positives and, consequently, testing and debugging costs while improving the quality of the testing process.

Oscillation-Based Slime Mould Electronic Circuit Model for Maze-Solving Computations

The ability of slime mould to learn and adapt to periodic changes in its environment inspired scientists to develop behavioral memristor-based circuit models of its memory organization. The computing abilities of slime mould Physarum polycephalum have been used in several applications, including to solve mazes. This work presents a circuit-level bio-inspired maze-solving approach via an electronic model of the oscillatory internal motion mechanism of slime mould, which emulates the local signal propagation and the expansion of its vascular network. Our implementation takes into account the inherent noise existent in the equivalent biological circuit, so that its behavior becomes closer to the non-deterministic behavior of the real organism. The efficiency and generality of the proposed electronic computing medium was validated through SPICE-level circuit simulations and compared with data from two cardinally different biological experiments, concerning 1) enhancing of Physarum's protoplasmic tubes along shortest path and 2) chemo-tactic growth by diffusing chemo-attractants.

A doctrinal approach to modal/temporal Heyting logic and non-determinism in processes

The study of algebraic modelling of labelled non-deterministic concurrent processes leads us to consider a category LB, obtained from a complete meet-semilattice B and from B-valued equivalence relations. We prove that, if B has enough properties, then LB presents a two-fold internal logical structure, induced by two doctrines definable on it: one related to its families of subobjects and one to its families of regular subobjects. The first doctrine is Heyting and makes LB a Heyting category, the second one is Boolean. We will see that the difference between these two logical structures, namely the different behaviour of the negation operator, can be interpreted in terms of a distinction between non-deterministic and deterministic behaviours of agents able to perform computations in the context of the same process. Moreover, the sorted first-order logic naturally associated with LB can be extended to a modal/temporal logic, again using the doctrinal setting. Relations are also drawn to other computational models.

Fault Activity Aware Service Delivery in Wireless Sensor Networks for Smart Cities

Wireless sensor networks (WSNs) are increasingly used in smart cities which involve multiple city services having quality of service (QoS) requirements. When misbehaving devices exist, the performance of current delivery protocols degrades significantly. Nonetheless, the majority of existing schemes either ignore the faulty behaviors’ variability and time-variance in city environments or focus on homogeneous traffic for traditional data services (simple text messages) rather than city services (health care units, traffic monitors, and video surveillance). We consider the problem of fault-aware multiservice delivery, in which the network performs secure routing and rate control in terms of fault activity dynamic metric. To this end, we first design a distributed framework to estimate the fault activity information based on the effects of nondeterministic faulty behaviors and to incorporate these estimates into the service delivery. Then we present a fault activity geographic opportunistic routing (FAGOR) algorithm addressing a wide range of misbehaviors. We develop a leaky-hop model and design a fault activity rate-control algorithm for heterogeneous traffic to allocate resources, while guaranteeing utility fairness among multiple city services. Finally, we demonstrate the significant performance of our scheme in routing performance, effective utility, and utility fairness in the presence of misbehaving sensors through extensive simulations.

Improving the performance of reverse debugging

Reverse debugging is the software development technique that effectively helps fix bugs occurring at the nondeterministic program behavior. It allows one to examine the past states of the program without rerunning it. An implementation of reverse debugging based on deterministic replay in the QEMU 2.0 emulator is described. A number of techniques improving the debugging performance due to reducing the amount of saved data, optimized storage of system snapshots, indexing, and compressing of the event log are proposed. The emulator can work together with the interactive GDB debugger, which makes it possible to use the reverse-continue, reverse-nexti, reverse-stepi and reverse-finish commands in the course of debugging. The execution time of these commands depends on the frequency of recording the system's state snapshots. An estimate of the optimal frequency for the reverse-continue command is obtained.