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Aviation control software has become the core control decision-making unit of the aviation system. The Boolean conditional expressions are the main parts of the branch and loop control logic of aviation control software. This paper studies the fault classification and repair method of conditional expression of aviation control software. 1) a two-level Boolean conditional expression fault classification method is proposed; 2) based on the design of mutation operator, repair solution and stop condition of mutation repair, an automatic repair method of conditional expression is proposed; 3) a repair assistant tool for conditional expression is designed and implemented, and 155 fault expressions are repaired. The results show that 55.5% of fault expressions can achieve accurate repair, 44.5% of fault expressions can generate multiple correct versions after a repair, and some versions have operation redundancy, so it is necessary to select the optimal version manually.

In the existing precise subsidy system, how to accurately select the students who need to be subsidized by analyzing a large number of student campus consumption data has become a difficult problem. We analyzed the campus consumption data of 5505 students in detail, and visualized the consumption differences of students in different colleges, grades and genders. We proposed a combination of K-means clustering and conditional expression, taking full account of days at school, frequency of meals and average daily consumption. According to the analysis results of this algorithm, more than 100 students were funded. The experimental data and the feedback received indicate that the algorithm has better accuracy.

There are context-dependent behaviors that are active only when a certain condition holds, and that require a certain transition process before activation. We propose a layer-activation mechanism of context-oriented programming languages for such context-dependent behaviors. Our mechanism supports the implicit layer activation (as opposed to the event-based layer activation) in a sense that a condition of activation is written as a conditional expression over reactive values (e.g., values obtained from sensors). In addition, it is push-based in a sense that it executes the transition process immediately after the condition becomes valid (as opposed to the mechanisms that defer the transition process until the first execution of a context-dependent behavior). In this paper, we present how this mechanism works in an extension of ServalCJ with push-based reactive values, and identify open issues raised by this proposal.

Mutation analysis is a method for predicting the quality of test suite accurately. However, it has high computational cost due to the number of mutants that are generated. For example, the ROR (Relational Operator Replacement) mutation operator will generate seven mutants for just one relational operator. Naively applying multiple operators over the entire program can result in a high number of generated mutants. One way to reduce the number of mutants is to omit redundant mutants. In this paper, we propose an approach to reducing mutants by using mutant killable precondition to identify redundant mutants. A mutant killable precondition is a logical expression for killing a mutant. We focus on the conditional expression for control flow statements, such as if and while statements. We describe the mutant killable precondition for conditional expressions that compare numbers, e.g., x > 0. We then discuss mutants that are generated for such conditional expressions, and find the minimal set of mutants. Finally, we show the theoretical and empirical reduction rate of our approach.

The use of implanted microelectrode arrays (MEAs), in the brain, has enabled a greater understanding of neural function, and new treatments for neurodegenerative diseases and psychiatric disorders. Glial encapsulation of the device and the loss of neurons at the device-tissue interface are widely believed to reduce recording quality and limit the functional device-lifetime. The integration of microfluidic channels within MEAs enables the perturbation of the cellular pathways, through defined vector delivery. This provides new approaches to shed light on the underlying mechanisms of the reactive response and its contribution to device performance. In chronic settings, however, tissue ingrowth and biofouling can obstruct or damage the channel, preventing vector delivery. In this study, we describe methods of delivering vectors through chronically implanted, single-shank, “Michigan”-style microfluidic devices, 1–3 weeks, post-implantation. We explored and validated three different approaches for modifying gene expression at the device-tissue interface: viral-mediated overexpression, siRNA-enabled knockdown, and cre-dependent conditional expression. We observed a successful delivery of the vectors along the length of the MEA, where the observed expression varied, depending on the depth of the injury. The methods described are intended to enable vector delivery through microfluidic devices for a variety of potential applications; likewise, future design considerations are suggested for further improvements on the approach.

Model checking (Clarke et al. 1999; Holzmann 2003b; Lamport 2002a) is a flexible and powerful technique for verifying systems formally with automated tools. In principle, it makes this task easy for the user: given a formal system description and certain conditions to be satisfied, the automated checker either confirms that the system satisfies the conditions, or provides a counterexample.

The Ada Rapporteur Group [ARG] following the directives of ISO/IEC/JTC1/SC22/WG9 is preparin and update to the Ada 2005 standard. This paper presents a snapshot of the more important language enhancements under discussion. Even though these enhancements are not yet in their final form and will not become part of the new standard until approved by ISO, the description that follows is an accurate reflection of the main directions in which the language is evolving. However, the names of packages, subprograms, and formal parameters, as well as some details of the syntax might change from what is presented here.

In Chapter 5, “Values, Basic Functions, and Expressions,” we covered the basic set functions, value functions, and value expressions incorporated into SQL. To write complex applications, however, you will often need more power than is available through these basic facilities. Data sublanguages have often been criticized for their lack of rich programming constructs, forcing users and developers to rely on the facilities of host languages or external environments. SQL: 1999 introduces some of these facilities to the SQL world, including • a conditional expression (CASE)

The point at which modeling gets particularly interesting is when model behavior becomes increasingly nonlinear. It is no coincidence that this is the point where simulation tools start having trouble. Nonlinear behavior is hard to avoid in real world models. The examples in this chapter will introduce some of the approaches used to describe nonlinear behavior.

This chapter describes the implementation of the teleprogramming language used to carry symbolic information between the master and slave sites. In common with many existing robot programming languages (see for example [59, 48, 18]), we had the usual requirements of performing relative or absolute joint or Cartesian-space motions while allowing detected sensory signals to change the flow of program execution. In addition, the limited communications channel and uncertainty in the world model acted to constrain the symbolic telemetry.

An essential aspect of computer programs is their ability to make decisions — to proceed differently depending upon properties of the data they are operating upon. In this chapter, we explore two different ways of building decision-making into Mathematica programs: multi-clause definitions, in which a function is defined by more than one rule; and conditional functions, which return one of several values depending upon a condition. These features will greatly expand what we can do with Mathematica; they are also a crucial step toward learning the basic techniques of recursion and iteration.

In this essay I present a general characterization of qualitative probability, defining the concept of a qualitative probability language and proposing some bases for comparison. In particular, enumerating some of the distinctions that can be supported by a qualitative probability language induces a partial taxonomy of possible approaches. I discuss some of these in further depth, identify central issues, and suggest some general comparisons.

In this paper, I present an approach to representing plans that make on-line decisions about resource allocation. An on-line decision is the evaluation of a conditional expression involving sensory information as the plan is being executed. I use a plan representation called 7ZS10'1 1,12that has been especially designed for the domain of robot programming, and in particular, for the problem of on-line decisions. The resource allocation example is based on the robot assembly cell architecture outlined by Venkataraman and Lyons16. I begin by setting forth a definition of on-line decision making and some arguments as to why this form of decision making is important and useful. To set the context for the resource allocation example, I take some care in categorizing the types of on-line decision making and the approaches adopted by other workers so far. In particular, I justify a plan-based approach to the study of on-line decision making. From that, the focus shifts to one type of decision making: on-line allocation of robot resources to task plans. Robot resources are the physical manipulators (grippers, wrists, arms, feeders, etc) that are available to carry out the task. I formulate the assembly cell architecture of Venkataraman and Lyons16 as an R.S plan schema, and show how the on-line allocation specified in that architecture can be implemented. Finally, I show how considering the on-line allocation of logical resources, that is a physical resource plus some model information, can be used as a non-traditional approach to some problems in robot task planning.

Program synthesis is the construction of a computer program from given specifications. An automatic program synthesis system must combine reasoning and programming ability with a good deal of knowledge about the subject matter of the program. This ability and knowledge must be represented both procedurally (by programs) and structurally (by choice of representation).

Clinical research is of utmost importance to keep standards of treatment at the highest possible level. This research is often delayed by the vast amount of time needed to record data on a suitable medium and then to order these data for analysis purposes. For this reason the computer is a useful tool for analyzing research data in a fast and flexible way.