A unified integration and component testing approach from deterministic stream X-machine specifications

One of the great benefits of using a stream X-machine to specify a system is its associated testing method. Under certain design for test conditions, this method produces a test suite that can determine the correctness of the implementation under test (IUT), provided that the basic components of the stream X-machine model have been correctly implemented. However, such an approach implies that each component can be tested in isolation from the rest of the system. This is a limitation that, in practice, can be resolved by developing stubs and drivers. However, this adds complexity to the testing process and, furthermore, these new pieces of software can introduce faults that can invalidate the theoretical results of the aforementioned testing method. This paper extends the approach by allowing component testing to be performed in parallel with integration testing, while still guaranteeing the IUT correctness under the given design for test conditions. It also shows how the integration test suite, produced in previous publications, can be reduced.     

Optimal <Emphasis Type="Italic">K</Emphasis>-unit cycle scheduling of two-cluster tools with residency constraints and general robot moving times

The semiconductor manufacturing industry is significantly expensive both in equipment and materials. Cluster tools, a type of automated manufacturing system integrating processing modules and transport modules, are commonly used in this industry. Nowadays, multi-cluster tools, which are composed of several cluster tools connected by joint buffer modules, are often used for wafer production. This paper deals with K-unit cycle scheduling problems in single-armed two-cluster tools for processing identical wafers in deterministic settings. In a K-unit cycle, K wafers are exactly inserted into the two-cluster tool, and K completed wafers leave the two-cluster tool, usually not the same K wafers. Residency constraints and general moving times by the robot are both considered. The objective is to obtain optimal K-unit cycle schedules, which minimize cycle times. To analyze this scheduling problem in detail, a mixed integer linear programming (MILP) model is formulated and solved. Numerical examples are used to explain how the solution can be obtained from the MILP model in a K-unit cycle.     

Generating test case chains for reactive systems

Testing of reactive systems is challenging because long input sequences are often needed to drive them into a state to test a desired feature. This is particularly problematic in on-target testing, where a system is tested in its real-life application environment and the amount of time required for resetting is high. This article presents an approach to discovering a test case chain—a single software execution that covers a group of test goals and minimizes overall test execution time. Our technique targets the scenario in which test goals for the requirements are given as safety properties. We give conditions for the existence and minimality of a single test case chain and minimize the number of test case chains if a single test case chain is infeasible. We report experimental results with our ChainCover tool for C code generated from Simulink models and compare it to state-of-the-art test suite generators.     

Generation and distillation of non-Gaussian entanglement from nonclassical photon statistics

With a product state of the form \({{\rho}_{\rm in} = {\rho}_{a} \otimes |0 \rangle_b {_b} \langle 0|}\) as input to a beam splitter, the output two-mode state ρ _out is shown to be negative under partial transpose (NPT) whenever the photon number distribution (PND) statistics { p(n _a ) } associated with the possibly mixed state ρ _a of the input a-mode is antibunched or otherwise nonclassical, i.e., whenever { p(n _a ) } fails to respect any one of an infinite sequence of necessary and sufficient classicality conditions. Negativity under partial transpose turns out to be a necessary and sufficient test for entanglement of ρ _out which is generically non-Gaussian. The output of a PND distribution is further shown to be distillable if any one of an infinite sequence of three term classicality conditions is violated.     

A genetic algorithm embedded with a concise chromosome representation for distributed and flexible job-shop scheduling problems

This paper proposes a genetic algorithm \(GA\_JS\) for solving distributed and flexible job-shop scheduling (DFJS) problems. A DFJS problem involves three scheduling decisions: (1) job-to-cell assignment, (2) operation-sequencing, and (3) operation-to-machine assignment. Therefore, solving a DFJS problem is essentially a 3-dimensional solution space search problem; each dimension represents a type of decision. The \(GA\_JS\) algorithm is developed by proposing a new and concise chromosome representation \({\varvec{S}}_{{\varvec{JOB}}}\), which models a 3-dimensional scheduling solution by a 1-dimensional scheme (i.e., a sequence of all jobs to be scheduled). That is, the chromosome space is 1-dimensional (1D) and the solution space is 3-dimensional (3D). In \(GA\_JS\), we develop a 1D-to-3D decoding method to convert a 1D chromosome into a 3D solution. In addition, given a 3D solution, we use a refinement method to improve the scheduling performance and subsequently use a 3D-to-1D encoding method to convert the refined 3D solution into a 1D chromosome. The 1D-to-3D decoding method is designed to obtain a “good” 3D solution which tends to be load-balanced. In contrast, the refinement and 3D-to-1D encoding methods of a 3D solution provides a novel way (rather than by genetic operators) to generate new chromosomes, which are herein called shadow chromosomes. Numerical experiments indicate that \(GA\_JS\) outperforms the IGA developed by De Giovanni and Pezzella (Eur J Oper Res 200:395–408, 2010), which is the up-to-date best-performing genetic algorithm in solving DFJS problems.     

Regression test size reduction using improved precision slices

We propose a technique to select regression test cases that is targeted to reduce the size of test suite by using improved precision slices. For this, we first construct the control flow graph model of an object-oriented program. Subsequently, we identify the infeasible paths and compute the definition-use (def-use) pairs only along the feasible paths. Next, we construct the dependency model using this information. This helps us to ignore the dependencies existing along infeasible paths leading to construction of precise slices. Then, we build the dependency model and construct forward slices on the dependency model to determine the affected nodes and the test cases that cover the affected nodes in the dependency graph model are selected for regression testing. The results obtained from our experimental studies indicate that our approach reduces the regression test suite size on an average by 11.25 % as compared to a related approach, without degrading the fault-revealing effectiveness.     

Certifying a java type resolution function using program transformation,annotation, and reflection

In Java, type resolution is a function that takes a reference to a type occurring in a given context as input and returns the canonical name of that type. This information is fundamental to static analysis—a “must have” function underlying virtually all forms of semantic-based analysis. In the case of Java, this function is also complex and it is quite common to encounter tools where it is implemented incorrectly. This paper presents a novel approach for certifying the correctness of a given type resolution function with respect to an arbitrary Java source code base. The approach uses program transformation to instrument a subject code base in such a way that reflection can then be used to certify the correctness of the type resolution function against the function used by the Java compiler. In this form of certification, the type resolution function of the Java compiler serves as the test oracle.     

Fast Regulation Control of a Class of Input-delayed Linear Systems with Pre-feedback

A control problem of a class of input-delayed linear systems is considered in this paper. Due to the delay τ in the input, any designed feedback controller can only be engaged after t ≥ τ. Then, this can become the cause of slow regulation since any feedback information cannot be available during the delay. So, the initial function defined for -τ ≤ t ≤ 0 is engaged as an ‘initial non-feedback input’ for 0 ≤ t ≤ τ, which governs the system behavior during this initial time period. There have been numerous research results on the control of input-delayed linear systems by far. Yet, there have been no results on the examination and design of this initial function. Utilizing a time optimal control in the existing results, we show that if some pre-feedback as the initial function is engaged, the system response of the input-delayed linear system can be much improved, and a bang-bang input function is a good candidate as a pre-feedback which can provide better starting state values for the state feedback controller in order to perform the fast regulation. Two examples are given for the illustration of our results.     

Minimization of the maximal lateness for a single machine

Consideration was given to the classical NP-hard problem 1|r_j|L_max of the scheduling theory. An algorithm to determine the optimal schedule of processing n jobs where the job parameters satisfy a system of linear constraints was presented. The polynomially solvable area of the problem 1|r_j|L_max was expanded. An algorithm was described to construct a Pareto-optimal set of schedules by the criteria L_max and C_max for complexity of O(n³logn) operations.     

Continuous visible nearest neighbor query processing in spatial databases

In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CVNN query returns a set of \({\langle p, R\rangle}\) tuples such that \({p \in P}\) is the nearest neighbor to every point r along the interval \({R \subseteq q}\) as well as p is visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R due to the obstruction of some obstacles in O. In contrast to existing continuous nearest neighbor query, CVNN retrieval considers the impact of obstacles on visibility between objects, which is ignored by most of spatial queries. We formulate the problem, analyze its unique characteristics, and develop efficient algorithms for exact CVNN query processing. Our methods (1) utilize conventional data-partitioning indices (e.g., R-trees) on both P and O, (2) tackle the CVNN search by performing a single query for the entire query line segment, and (3) only access the data points and obstacles relevant to the final query result by employing a suite of effective pruning heuristics. In addition, several interesting variations of CVNN queries have been introduced, and they can be supported by our techniques, which further demonstrates the flexibility of the proposed algorithms. A comprehensive experimental evaluation using both real and synthetic data sets has been conducted to verify the effectiveness of our proposed pruning heuristics and the performance of our proposed algorithms.     

Testing Convexity Properties of Tree Colorings

A coloring of a graph is convex if it induces a partition of the vertices into connected subgraphs. Besides being an interesting property from a theoretical point of view, tests for convexity have applications in various areas involving large graphs. We study the important subcase of testing for convexity in trees. This problem is linked, among other possible applications, with the study of phylogenetic trees, which are central in genetic research, and are used in linguistics and other areas. We give a 1-sided, non-adaptive, distribution-free ε-test for the convexity of tree colorings. The query complexity of our test is O(k/ε), where k is the number of colors, and the additional computational complexity is O(n). On the other hand, we prove a lower bound of \(\Omega(\sqrt{k/\epsilon})\) on the query complexity of tests for convexity in the standard model, which applies even for (unweighted) paths. We also consider whether the dependency on k can be reduced in some cases, and provide an alternative testing algorithm for the case of paths. Then we investigate a variant of convexity, namely quasi-convexity, in which all but one of the colors are required to induce connected components. For this problem we provide a 1-sided, non-adaptive ε-test with query complexity O(k/ε ²) and time complexity O(kn/ε). For both our convexity and quasi-convexity tests, we show that, assuming that a query takes constant time, the time complexity can be reduced to a constant independent of n if we allow a preprocessing stage of time O(n) and O(n ²), respectively. Finally, we show how to test for a variation of convexity and quasi-convexity where the maximum number of connectivity classes of each color is allowed to be a constant value other than 1.     

Two-agent flowshop scheduling to maximize the weighted number of just-in-time jobs

We consider the scheduling problem in which two agents (agents A and B), each having its own job set (containing the A-jobs and B-jobs, respectively), compete to process their own jobs in a two-machine flowshop. Each agent wants to maximize a certain criterion depending on the completion times of its jobs only. Specifically, agent A desires to maximize either the weighted number of just-in-time (JIT) A-jobs that are completed exactly on their due dates or the maximum weight of the JIT A-jobs, while agent B wishes to maximize the weighted number of JIT B-jobs. Evidently four optimization problems can be formulated by treating the two agents’ criteria as objectives and constraints of the corresponding optimization problems. We focus on the problem of finding the Pareto-optimal schedules and present a bicriterion analysis of the problem. Solving this problem also solves the other three problems of bicriterion scheduling as a by-product. We show that the problems under consideration are either polynomially or pseudo-polynomially solvable. In addition, for each pseudo-polynomial-time solution algorithm, we show how to convert it into a two-dimensional fully polynomial-time approximation scheme for determining an approximate Pareto-optimal schedule. Finally, we conduct extensive numerical studies to evaluate the performance of the proposed algorithms.     

Real-time processing of streaming big data

In the era of data explosion, high volume of various data is generated rapidly at each moment of time; and if not processed, the profits of their latent information would be missed. This is the main current challenge of most enterprises and Internet mega-companies (also known as the big data problem). Big data is composed of three dimensions: Volume, Variety, and Velocity. The velocity refers to the high speed, both in data arrival rate (e.g., streaming data) and in data processing (i.e., real-time processing). In this paper, the velocity dimension of big data is concerned; so, real-time processing of streaming big data is addressed in detail. For each real-time system, to be fast is inevitable and a necessary condition (although it is not sufficient and some other concerns e.g., real-time scheduling must be issued, too). Fast processing is achieved by parallelism via the proposed deadline-aware dispatching method. For the other prerequisite of real-time processing (i.e., real-time scheduling of the tasks), a hybrid clustering multiprocessor real-time scheduling algorithm is proposed in which both the partitioning and global real-time scheduling approaches are employed to have better schedulablity and resource utilization, with a tolerable overhead. The other components required for real-time processing of streaming big data are also designed and proposed as real time streaming big data (RT-SBD) processing engine. Its prototype is implemented and experimentally evaluated and compared with the Storm, a well-known real-time streaming big data processing engine. Experimental results show that the proposed RT-SBD significantly outperforms the Storm engine in terms of proportional deadline miss ratio, tuple latency and system throughput.     

A metric for total tardiness minimization

In this paper we consider the NP-hard 1|r _j |ΣT _j scheduling problem, suggesting a polynomial algorithm to find its approximate solution with the guaranteed absolute error. The algorithm employs a metric introduced in the parameter space. In addition, we study the possible application of such an approach to other scheduling problems.     

Locally adaptive <Emphasis Type="Italic">k</Emphasis> parameter selection for nearest neighbor classifier: one nearest cluster

The k nearest neighbors (k-NN) classification technique has a worldly wide fame due to its simplicity, effectiveness, and robustness. As a lazy learner, k-NN is a versatile algorithm and is used in many fields. In this classifier, the k parameter is generally chosen by the user, and the optimal k value is found by experiments. The chosen constant k value is used during the whole classification phase. The same k value used for each test sample can decrease the overall prediction performance. The optimal k value for each test sample should vary from others in order to have more accurate predictions. In this study, a dynamic k value selection method for each instance is proposed. This improved classification method employs a simple clustering procedure. In the experiments, more accurate results are found. The reasons of success have also been understood and presented.     

A new strategy for generating shortest addition sequences

An addition sequence problem is given a set of numbers X = {n ₁, n ₂, . . . , n _m }, what is the minimal number of additions needed to compute all m numbers starting from 1? This problem is NP-complete. In this paper, we present a branch and bound algorithm to generate an addition sequence with a minimal number of elements for a set X by using a new strategy. Then we improve the generation by generalizing some results on addition chains (m = 1) to addition sequences and finding what we will call a presumed upper bound for each n _j , 1 ≤ j ≤ m, in the search tree.     

Discerning individual interests and shared interests for social user profiling

Traditionally, research about social user profiling assumes that users share some similar interests with their followees. However, it lacks the studies on what topic and to what extent their interests are similar. Our study in online sharing sites reveals that besides shared interests between followers and followees, users do maintain some individual interests which differ from their followees. Thus, for better social user profiling we need to discern individual interests (capturing the uniqueness of users) and shared interests (capturing the commonality of neighboring users) of the users in the connected world. To achieve this, we extend the matrix factorization model by incorporating both individual and shared interests, and also learn the multi-faceted similarities unsupervisedly. The proposed method can be applied to many applications, such as rating prediction, item level social influence maximization and so on. Experimental results on real-world datasets show that our work can be applied to improve the performance of social rating. Also, it can reveal some interesting findings, such as who likes the “controversial” items most, and who is the most influential in attracting their followers to rate an item.     

List decoding for a multiple access hyperchannel

We obtain bounds on the rate of (optimal) list-decoding codes with a fixed list size L ≥ 1 for a q-ary multiple access hyperchannel (MAHC) with s ≥ 2 inputs and one output. By definition, an output signal of this channel is the set of symbols of a q-ary alphabet that occur in at least one of the s input signals. For example, in the case of a binary MAHC, where q = 2, an output signal takes values in the ternary alphabet {0, 1, {0, 1}}; namely, it equals 0 (1) if all the s input signals are 0 (1) and equals {0, 1} otherwise. Previously, upper and lower bounds on the code rate for a q-ary MAHC were studied for L ≥ 1 and q = 2, and also for the nonbinary case q ≥ 3 for L = 1 only, i.e., for so-called frameproof codes. Constructing upper and lower bounds on the rate for the general case of L ≥ 1 and q ≥ 2 in the present paper is based on a substantial development of methods that we designed earlier for the classical binary disjunctive multiple access channel.     

Perceptrons of large weight

A threshold gate is a linear combination of input variables with integer coefficients (weights). It outputs 1 if the sum is positive. The maximum absolute value of the coefficients of a threshold gate is called its weight. A degree-d perceptron is a Boolean circuit of depth 2 with a threshold gate at the top and any Boolean elements of fan-in at most d at the bottom level. The weight of a perceptron is the weight of its threshold gate.For any constant d ≥ 2 independent of the number of input variables n, we construct a degree-d perceptron that requires weights of at least \(n^{\Omega (n^d )} \); i.e., the weight of any degree-d perceptron that computes the same Boolean function must be at least \(n^{\Omega (n^d )} \). This bound is tight: any degree-d perceptron is equivalent to a degree-d perceptron of weight \(n^{O(n^d )} \). For the case of threshold gates (i.e., d = 1), the result was proved by Håstad in [2]; we use Håstad’s technique.