Law-governed regularities in object systems part 1 An abstract model. Theory and Practice o

Law-Governed Regularities in Object Systems;

Part 1: An Abstract Model

By: Naftaly H. Minsky

March 1995

Computer Science Department1

Rutgers University

New Brunswick, NJ 08903

Tel: 908-445-2085

Net Address: minsky@https://www.wendangku.net/doc/9018102572.html,

Abstract

Regularities, or the conformity to unifying principles, are essential to the comprehensibility, manageability and reliability of large software systems. Yet, as is argued in this paper, the inherent globality of regularities makes them very hard to establish in traditional methods. This paper explores an approach to regularities for object systems which greatly simplifies their implementation, making them more easily employable for taming of the complexities of large scale software. This approach, which is based on a generalized concept of law-governed architecture (LGA) introduced in this paper, provides system designers and builders with the means for establishing a fairly wide range of useful regularities simply by declaring them formally and explicitly as the law of the system. Once such a law-governed regularity is declared, it is enforced by the environment in which the system is developed.

keywords:Complexity in software, regularities, object-systems, software-development environments.

1Work supported in part by NSF grant No. CCR-9308773.

1. Introduction

In his classic paper "No Silver Bullet" [1], Brooks cites complexity as a major reason for the great difficulties we have with large software systems, arguing that "software entities are more complex for their size than perhaps any other human construct," and that their "complexity is an inherent and irreducible property of software systems" [emphasis mine]. Brooks explains this bleak assessment as follows: "The physicist labors on, in a firm faith that there are unifying principles to be found ... no such faith comforts the software engineer."

Brooks is surely right in viewing conformity to unifying principles, i.e.,regularities, as essential to our ability to understand and manage large systems. The importance of such regularities can be illustrated with examples in many domains: the regular organization of the streets and avenues in the city of Manhattan greatly simplifies navigation in the city, and the planning of services for it; the protocol that all drivers use at intersections of roads makes driving so much easier and safer; and the layered organization of communication-networks provides a framework within which these systems can be constructed, managed and understood. In all these cases, and in many others, the regularities of a system are viewed as an important aspect of its architecture.

Yet, in spite of the general importance of regularities and their critical role in the taming of the complexity of systems, regularities do not play an important role in the architecture of conventional software systems, as indicated by the above mentioned quote from Brooks’ paper . This is partially because simple regularities of repetition can be easily abstracted out and "made into a subroutine," in Brooks’ words [1] --- but, as we shall see, there are other, more subtle kinds of regularities that may "comfort the software engineer," if they can be easily and reliably established. We believe that the main impediment for regularities in software is that they are inherently hard to implement reliably.

The problem with the implementation of regularities stems from their intrinsic globality. Unlike an algorithm or a data structure that can be built into few specific modules, a regularity is a principle that must be observed everywhere in the system, and thus cannot be localized by traditional methods. One can, of course, establish a desired regularity by painstakingly building all components of the system in accordance with it. But, as we shall argue in the following section, such a "manual" implementation of regularities is laborious, unreliable, unstable and difficult to verify and to change. While certain regularities are usually imposed on a system by the programming languages in which it is written, languages do not, and, as we shall argue later, probably cannot, support a sufficiently wide range of regularities.

The thesis advanced by this paper is that for regularities to become practical as a means for simplifying large systems, they ought to be formally specifiable for a given system, and then enforced by some kind of higher authority. We demonstrate the validity of this thesis by showing how a fairly wide range of regularities can be established for object systems under law-governed architecture(LGA). Broadly speaking, under this architecture a desired regularity can be established for a given system by declaring it formally and explicitly as the law of the system, to be enforced by the environment in which the system is developed. Besides the ease of establishing regularities in this way, the resulting law-governed regularities should be much more reliable and more flexible than manually implemented ones.

The rest of this paper2is organized as follows. We start, in Section 2, with a discussion of the nature of regularities in software, and with an analysis of their implementation difficulties. In Section 3 we provide a brief overview of LGA, with an informal illustration of the manner in which regularities are established under this architecture, and of the manner in which these regularities may evolve and be refined throughout the evolutionary lifetime of a system; we conclude this section with a discussion of related work by other researchers. Section 4 introduces an abstract model of LGA for object systems --- a major generalization of the model described in [15] --- and we briefly discuss two concrete realizations of this model that have been implemented so far under the Darwin/2 environment: one for an object-oriented version of Prolog, and one for the Eiffel language. The abstract LGA model is used in Section 5 to examine a sample of law-governed regularities that can be efficiently enforced under Darwin/2, along with a brief discussion of the their expected benefits.

2. The Nature of Regularities, and their Implementation Difficulties

The term "regularity" refers in this paper to any global property of a system; that is, a property that holds true for every part of the system, or for some significant and well defined subset of its parts. Thus, the statement "class B inherits from class C," in some object-oriented system, does not express a regularity, since it concerns just two specific classes; but the statement "every class in the system inherits from C" does express a regularity, and so does the statement "only class B inherits from C," both of which employ universal quantification.

One well known example of a regularity in software is the concept of layered architecture. By saying that a given system S is layered we generally mean that the modules of a system are partitioned into groups called "layers", such that any given module can call only modules at its own

2A short and non-technical version of this paper has been presented in the 1993 workshop on Software Design, and will be published in [20].

layer, or at the layer immediately below it. Another important regularity is encapsulation-- the principle that no object in a system can penetrate the interior of another object. Both of these are global statements about a system that involve universal quantifiers, and are thus properly called regularities.

In addition to such almost universally useful regularities, a given system may benefit from a variety of regularities designed specifically for it. As an example of such a "special purpose" regularity, consider the following token-based protocol which might be employed by a system S with concurrently running threads in order to ensure mutual exclusion with respect to a given operation O:

(a)No thread performs operation O unless it possesses a certain token T.

(b)Initially, there is only one copy of T in the system.

(c)Token T may be transferred from one place in the system to another, but cannot be

duplicated.

Note that to be effective, this protocol must be obeyed everywhere in the system, because the desired mutual exclusion would be endangered by any violation of this protocol, even by a single thread. In other words, this protocol must be a regularity.

The utility of regularities in large systems is almost self evident, but their implementation is very problematic. Conceptually the simplest, and currently the most common, technique for establishing regularities is to implemented them manually; that is, to carefully construct the system according to the desired regularities. The problems with this approach, which are due to the inherent globality of regularities, are exemplified by the following difficulties one would have with the above mentioned token-based regularity (or protocol), if it is to be implemented manually:

1.It would be very difficult to carry out this implementation, because it must be done

painstakingly in many different parts of the system. It would, in particular, be

difficult to ensure that no thread in the system S ever performs operation O without

possessing the token T, and that no extra copy of T is ever made, anywhere in the

system.

2.Any verification(formal or informal) that a given system satisfies this protocol,

involves the analysis of all(or, at least, many) parts of the system.

3.This protocol would be very unstable with respect to the evolution of the system.

Indeed, even if we are able to ascertain that the protocol is satisfied by a given

version of the system, we cannot have much confidence in its satisfaction in future

versions. Because, due to the global nature of the protocol, it can be compromised by

a change anywhere in the system.

4.Finally, this protocol would be very difficult to change, even if the change itself is

small, because such a change would have to be introduced manually into many parts

of the system. Changes spread out in this way are very expensive and notoriously

prone to error.

Since these problems are quite clearly endemic to all manually implemented regularities, it follows that it would be much better for regularities to be imposed on a system by some kind of "higher authority".

Perhaps the most obvious such authority that can impose regularities on a system is the programming language in which this system is written. In fact, certain types of regularities are routinely imposed by various languages on the programs written in them. These include block-structured name scoping,encapsulation,inheritance, and various regularities involving types. In spite of the obvious importance of such built-in regularities, the imposition of regularities by means of a programming language has several serious limitations.

1.Only very few types of regularities can be thus built into any given language; and a

regularity built into the very fabric of a language tends to be rigid, and not easily

adaptable to an application at hand.

2.Regularities that do not have universal applicability should not be built into a general

purpose language.

3.Programming languages usually adopt a module-centered view of software. They deal

mostly with the internal structure of individual modules, and with the interface

between pairs of directly interacting modules. But languages generally provide no

means for making explicit statements about the system as a whole, and thus no means

for specifying inter-module regularities beyond what is built into the language itself.

There is, for example, no language known to the author that provides the means for

imposing a layered structure on a system, although one can of course build such a

structure manually.

https://www.wendangku.net/doc/9018102572.html,nguage-imposed regularities are obviously not effective for multilingual systems,

where regularities are particularly needed.

For all these reasons it follows that the imposition of regularities requires a software architecture that provides a global view of systems; such is our law-governed architecture overviewed in the following section.

3. An Overview of Law-Governed Architecture (LGA)

The main novelty of law-governed architecture(LGA) is that it associates with every software development project P an explicit and global set of rules L, collectively called the law of the project, which is enforced by the environment that manages this project. The law governs the following aspects of the project under its jurisdiction:

1.The structure of the systems produced by this project.

2.The structure of the object base which represents the state of the project.

3.The process of software development.

4.The evolution of the law itself.

The unified treatment of the above, seemingly distinct, aspects of software development by means

of a single, formal, notion of law provides a synergistic effect that could not have been achieved by treating them separately. This treatment has, in particular, the following consequences:

First, since the law is enforced, it reflects the actual structure of the implemented system. Such a law should be helpful for software understanding because, unlike conventional specification of structures, it can be truly relied on when reasoning about a system. Second, the law is prescriptive because changes to the system which violate the law would be rejected by the environment. Thus, the law of a project establishes evolutionary invariants, as long as the law itself is not changed. Finally, the self-regulatory evolution of the law can provide software developers with a carefully circumscribed flexibility with respect to the structure of the system. For example, in a project that imposes layered structure, the manager may be empowered to authorize specific types of exceptions to the strict layering.

3.1. The Nature of the Law, and its Enforcement

Broadly speaking, the law governs the system under its jurisdiction by regulating various types of interactions between its component-objects (including program modules and the programmers that develop them) mostly ignoring the internal details of these objects. We distinguish between two kinds of regulated interactions:

1.The interactions between programmers and the system under development, including

the creation, destruction and modifications of program-modules, as well as the

modification of the law itself by the addition and deletion of rules.

2.The Interactions between the component-parts of the system being developed, such as

the exchange of messages between them, or relationships between modules such as

inheritance between classes.

Although the law treats both kinds of interactions uniformly, it is enforced differently with respect to them, as illustrated in Figure 3-1. The rules that regulate the former kind of interactions, thus governing the process of evolution of a given project P, are enforced dynamically, when the regulated interaction happens. On the other hand, the rules that regulate the latter kind of interactions, thus governing the structure and behavior of any system developed under P, are enforced largely statically, when the individual program modules are created and modified, and when a set of modules are grouped into a configuration, to be compiled into a single executable code.

3.2. The Object Base of a Project

The state of the project under Darwin/2 is represented by an object base B. It is a collection of objects of various kinds: including modules, which are the components of the systems under construction;builders, which serve as loci of activity for the people (such as programmers and managers) that participate in the process of software development; and rules, which are the component parts of the law.

Every object in B has a collection of attributes associated with it, called the exterior of the object. For example, a module m in B may have an attribute level(3)in its exterior, signifying that this module belongs to the 3rd layer of the system being developed;m may also have an attribute programmer(b), which identify the builder-object b as the programmer responsible for this module. With few exceptions, the Darwin environment has no built-in semantics for the attributes of objects, but such semantics may be established by the law of a given project B. For example, the law may permit modules to be updated only by their programmers (as defined by the attribute programmer mentioned above) and the law may impose constraints on the exchange of messages between modules based on the levels they belong to (as defined by the attribute level in their exterior).

3.3. The Initialization of a Project

A software development project starts under Darwin/2 with the definition of its initial law, which defines the general framework within which this project is to operate and evolve; and, in some analogy with the constitution of a country, it establishes the manner in which the law itself can be refined and changed throughout the evolutionary lifetime of this project. We will consider here an informal example of such an initial law, designed to support the development of layered systems. The part of this law that deals with regularities imposed on the system produced by this project is formalized later on in this paper. For a complete formalization of a very similar initial law the reader is referred to [15] where an almost identical example is discussed in greater detail. (This old example has been chosen intentionally, so that it does not have to be formalized completely here).

3.4. A Law of Evolving Layered Systems -- an Informal Example

We consider in this section a software development project P, and the initial law L0that governs it. Broadly speaking,L0partitions the modules of any system developed under P into groups called "layers". Using this grouping,L0imposes what we call the layering constraint on the interaction between modules. Furthermore, this initial-law provides for a carefully circumscribed evolution of the law itself, allowing the manager of the project and its various programmers to

establish certain kinds of additional regularities, throughout the course of software development. In particular, each programmer is authorized to specify which messages are acceptable to his own modules, subject to the layering constraint, while the manager of the project is authorized to impose global prohibitions over the exchange of messages between the modules of the system, above and beyond the layering constraint. This law is presented here as consisting of four informally specified rules (enclosed in boxes) that govern various aspects of the project under its jurisdiction. (Of these, rules r3 will be formalized in Section 5.)

Rule r1 below determines the structure of the object-base that would support project P throughout its evolutionary lifetime.

r1: The objects representing program-modules are partitioned into layers; the objects representing the builders of the system are partitioned into two roles:manager and programmer; and each module is designated as being owned by some programmer.

Technically, these partitions are defined by certain attributes associated with the various objects populating this project. The semantics of the resulting groupings of these objects is defined, in effect, by the other rules in this law, as we shall see.

Rule r2 governs the process of development and evolution under project P, by establishing the authority of the various builder-roles.

r2: A manager can create programmer-objects, and a programmer can make modules, becoming the owner of each module he makes. The owner of a module can program it, set its level, remove it, and pass its ownership to some other programmer.

This rule defines, in effect, what it means to be the manager of a project, and what it means to be an owner of a module. Note that the Darwin/2 environment itself has no built-in concept of a "manager" or of "ownership", but, as we have just seen, it provides for such concepts to be established specifically for each project, by means of its law.

Rule r3 governs the structure of the system being developed, by specifying the condition under which modules will be allowed to exchange messages. One of these conditions is the above mentioned layering constraints, the other two are the hooks that allow the manager of the project, and its programmers to have their say about the structure of the system.

r3: A message m from s to t is permitted only if the following three conditions are satisfied:

1.the message obeys the layering constraint;

2.it is acceptable to the target module t(as defined by the acceptable-rules, which,

according to rule r4 below can be written into the law only by the owner of t);

3.this message is not prohibited(as defined by prohibited-rules, which, according to

rule r4 below, can be written into the law only by the manager).

Finally, rule r4 governs the evolution of the law itself, allowing the manager of the project, and the various programmers to refine the regularities of the system during its development.

r4: The law can change only as specified below:

1.Every programmer can add to the law (and remove from it)acceptable-rules, which,

according to r3, define which messages are acceptable to any of his own modules, and

which module should be allowed to send these messages.

2.A manager can add to the law (and remove from it) arbitrary prohibited-rules,

which, according to r3, serve as prohibitions.

Note that this particular law, which is, of course, merely an example of what can be done under LGA, establishes a framework which is analogous to, but much more general than, the conventional module-interconnection frameworks(MIFs) which are based on selective export, as in Eiffel [12] in particular. The analogy comes from an apparent similarity between Eiffel’s export statements, and our acceptable-rules. Both are anchored on a module, defining the kind of messages that can be sent to it.3Yet, our example-law has several characteristics which are unmatched by Eiffel, or by any conventional MIF known to the author (such as the one based on imports of interfaces used in Modula-3 [2]).

First, under this law the layering constraint is an invariant of the evolution of this project--unchangeable even by its manager. Our ability to establish such invariants of evolution, without them being hard-wired into the environment, or into the language at hand, can attest to the power of this architecture. (As a possible refinement of this initial law, we shall show in Section 5.1.1 that it is possible to provide for a controlled exception mechanism from such an invariant.)

Second, even our acceptable-rules are significantly more general than the conventional export-statements. In particular, the Eiffel’s export-statements in a given module m list explicitly the names of the modules that can send a given message to m(unless it is a universal export). In our case, on the other hand, the analogous specification, by means of the acceptable-rules, can

3While the export-statement must be included textually within a module, our acceptable-rules are writable by the owner of the module they are anchored on -- not a major difference.

be by some condition defined over the attributes of the various modules of the system. These allows programmers to formulate general prescriptive policies, concerning the use of their modules. Here are two, informally stated, examples of policies concerning a given module m that can be expressed by means of a single acceptable-rule writable by the programmer of m.

?Module m can accept messages from every module at the layer of m.

?Module m can accept a specified message from every module owned by a programmer

Jones.

The formal statement of these rules will be given later on in this paper.

Finally, the prohibition-clause in rule r3 provides the manager of the project with a veto power over the exchange of messages between modules, which, as we shall see later, can be used by him to establish some general policies about the system being developed.

3.5. On the Implementation of Darwin/2

The Darwin/2 environment is currently implemented in Prolog, but is built to support the development of systems written in various languages. Darwin/2 has essentially two layers:

1.The abstract, language-independent, layer, that implements what we call the abstract

LGA model.

2.The concrete layer, that contains a set of language interfaces, one for each

programming language which may be used by any of the modules of the system.

(Note, however, that although the abstract layer is language independent, it assumes

that the languages support some form of encapsulated objects, or that they can be

made to support it.)

The abstract layer provides a language-independent view of the objects constituting a system, of the interactions between these objects, and of the law that governs these interactions. This layer also maintains the object-base constituting a system, and provides an abstract, language-independent, framework for the enforcement of the law. The LGA model defined by this layer is discussed in detail in Section 4.

It should be pointed out that our abstract model has some of the flavor of Prolog, which is, in particular, used for the formulation of laws. Therefore, a passing familiarity with this language would be helpful for reading this paper. We note, however, that this bias towards Prolog is quite superficial, and it does not reduce the language independence of this model. The Prolog bias is due, in part, to the fact that Darwin/2 environment itself happens to be implemented in this language.

A language-interface, for a given language, performs two functions. First, it maps the various concepts of the abstract model to the concrete concepts of the language at hand. Second, it provides

the language specific part of the enforcer of the law. The details of such interfaces are beyond the scope of this paper, but in Section 4.7 we will comment briefly on the three language-interfaces which have been implemented so far in Darwin/2: an interface called LGA/user, which deals with the interactions of users (or, programmers) with the system being developed; an interface called LGA/Prolog for the programming language Prolog [4] (modified to support encapsulation); and an interface called LGA/Eiffel for the object-oriented language Eiffel [12].

3.6. Related Work

The idea that a large system needs to be governed by an explicit,global and enforced set of rules (which we call "law") is not entirely new. It appeared in several incarnations in various kinds of systems, but so far it has never been developed into a fully fledged architecture for general software systems, of the kind described here. The following are the main such efforts known to the author:

?Ever since the seminal paper on module interconnection by DeRemer and Kron

[6] there have been several successful attempt at specifying constraints over the

interconnection between the various modules of a system. Three of the most prominent

ones are the PIC formalism of Wolf et al. [31], the Inscape system of Perry [26] and

the work on connectors by Garlan and Shaw [7, 27]. While these are very powerful

techniques for specifying the interface between modules, and in many ways they do

more than we can do under Darwin, they usually do not deal with regularities, i.e.,

with statements involving universal quantification. For example, none of these

techniques can specify that a given system should be layered, which is so very simple

to do under LGA.

?Perhaps the earliest attempt to provide an explicit global law for general software

systems (not for some specific kind of systems, like databases) was by Ossher [24, 25].

He built a mechanism that imposes a specified layered module-interconnection

structure on a given system, which bears some similarity to our example-law discussed

in this section.

?The Metaobject Protocol [10] by Kiczales et al. provides means for changing and

refining the structure and behavior of classes of objects in CLOS. It can do much of

what our laws can, and much that laws cannot do. But it lacks the global view of the

system which is so fundamental to laws under LGA, so that it cannot be used for

establishing regularities (and was never intended for quite this purpose.)

?The Meta system of Marzullo and Wood [11] has a global set of "policy rules" about

the interaction between nodes in a distributed system. Like our law, these rules are

explicit and enforced, and they serve as a kind of "glue" to bind the various pieces of

the system together.This system deals exclusively with certain aspects of distributed

system.

?Finally, and most recently, Shoham and Tennenholtz [28], using a rationale very

similar to our own (apparently with no knowledge of it), proposed the use of global

laws to regulate systems of robots. They discuss techniques for determining the

appropriate laws (they actually call them "laws") in certain situations, but so far they

proposed no mechanism or general architecture to enforce such laws.

Note that we do not mention here the extensive work on process-based environments. This work is

relevant to some aspects of Darwin but not to this paper, because none of these environments attempts to impose structure on the system being developed.

4. The Abstract Model of LGA (Under a Fixed Law)

A law-governed system is a triple

?O, L, E?,

where O is a set of interacting objects,L is a global law that governs the interaction between objects, and E is a mechanism that enforces the law. This general organization of software is called law-governed architecture, or LGA. The model of LGA to be presented here is abstract in that it does not specify the language, or languages, that drive the objects involved.

We start our discussion by defining our concept of interaction and of object. We then introduce the concept of law, together with a language for the specification laws, and we outline the law-enforcement mechanism. We conclude with a very brief outline of two concrete language-interfaces which have been implemented so far. (Note that throughout this paper, we limit ourselves by assuming the law itself to be fixed during the life-time of the system governed by it, which is not the case in general under LGA.)

4.1. Interactions

Various kinds of binary interactions between objects can be regulated under LGA. This include dynamic operation carried out by one object on another, as well as permanent relationship between pairs of objects. The dynamic interactions include (see Section 3.1): (1) the interactions between programmers and the system under development, and (2) the interactions between the component-parts of the system being developed, when it runs. The permanent interactions, include such things as the existence of inheritance relation between objects representing classes, and the redefinition of a feature defined in one class, by one of its heirs. For the sake of specificity, we will deal here only with dynamic interactions, referring to them as messages. (The precise semantics of such "messages" is determined by the language-interface, but we will asumme it to be synchronous4.) The difference in the way we treat dynamic interactions, and permanent interaction will be clarified in Section 4.3.1.

Syntactically, messages are expected to have the form of a Prolog-like term, which, as already explained, is a recursive data-structure of the form f(t1,...,tk), where f is a symbol, and the zero or more arguments t1,...,tk are either terms or variables.Variables, which are denoted

4Asynchronous message passing is is supported by a different model for LGA, presented in [16].

by a capitalized symbols, are used here in a message as a means for returning results to the sender. For example, consider a message sin(x,R)sent by an object s. The receiver of this message is expected to compute the sine of x, and to bind the result to the variable R, which would be returned to the sender s. (As we shall see, such a binding of value to the variable-argument can be caused by the law as well).

4.2. The Objects

An object is a triple

?exterior, interior, agent?,

where exterior together with interior constitute the state of the object, and agent is its active component.

The exterior is the part of the state of objects which is "visible" by the law, and controlled by it. That is to say, the law can make distinctions between objects only on the basis of their exterior, and changes in the exterior of objects are directly regulated by the law. We often refer to the exterior of an object as its control state, because of its critical role in LGA. The set of the exteriors of all objects in a system is often called the control state of the system.

The interior of an object is completely accessible to its own agent, and only to it. This access is not subject to the law, and its manner is left unspecified here. In fact, the interior of an object plays no explicit role in the abstract model, and is treated as a black box.

The agent of an object operates (a) by manipulating its own interior, and (b) by sending and receiving messages, subject to the law of the system. The law-governed interaction between objects is illustrated in Figure 4-1. The law is depicted here as mediator of interaction between objects, which "sees" only the exterior of objects. Specifically, this diagram depicts an object x whose agent sends a message m to an object y. This message is submitted to the law which rules, in this case, that a modified message m’should be delivered to y, and also that the exterior of y should be modified, in a manner not specified here.

y

Figure 4-1:Objects and the Interaction Between Them

One can distinguish between three kinds of agents, and, by implication, three kinds of objects:

1.A programmed agent, which is driven by its program-text, also to be called the script

of the object. An object with such an agent may represent a program-module, such as

a class, or an instance of such a class, depending on the language at hand, and

language-interface being used.

2.An unprogrammed agent, is any unpredictable generator of messages. An object

with such an agent may serve as a locus for the activity of a human user, as the

unprogrammed and unpredictable agent in question.

3.A idle agent, which performs no operations. Objects with such an agent generally

represent passive data-structures, defined by their exterior. (The rules that constitute

the law of a system are also represented by this kind of objects.)

Note that agents are treated as black boxes by the abstract model, which assumes no knowledge of, or control over, what an agent might attempt to do. Therefore, the above distinction between types of agents is important mostly to the concrete layer of LGA, that must enforce the law, and does not matter much to the abstract model which distinguishes between objects only on the basis of their exterior.

Structurally, the exterior of an object is a bag of terms, also called attributes of the object. A term5is a recursive data-structure which has the form f(t1,...,tk), where f is a symbol, and the zero or more arguments t1,...,tk are either terms or variables. (Variables are denoted by capitalized symbols, and may be viewed, roughly speaking, as representing arbitrary (or unknown) terms.) As a simple example, an object in layered system may have the term level(2)in its state, which may be intended to signify that this object belongs to the second layer of the system.

With few exceptions, the abstract model does not assign any semantics to the attributes of an object, which is left to be defined by the law of a given project (in a sense which will become

5Our terms have essentially the structure of terms in Prolog.

evident later). The main such exception is the distinguished attribute id(i), which has a prespecified semantics in the model itself. This attribute, which is used for addressing, is guaranteed to be present in every object, providing a unique and immutable identifier,i, for it.

4.2.1. Primitive Operations on Objects

Objects can be affected and examined by means of a fixed set of primitive operations which, as will be explained later, can be mandated by the law to be carried out in response to certain messages. They include operations that read and update the exterior of objects, operations that destroy objects and create new ones, operations that invoke the agents of objects, etc. (What is not included here are operations used by an agent to access its own interior, which, as we have assumed, are not subject to the law.)

A primitive operation is denoted by p@o, where p specifies the operation itself, and o names an object to which this operation is to be applied. Below is a brief description of the set of primitive operations defined by this model. (For pragmatic reasons, Darwin/2 [17] has a few additional primitive operations, which will not be discussed here.)

1.add(c)@o-- Adds the term c to the exterior of object o.

2.remove(c)@o-- Removes from the exterior of o a single term that unifies(in the

Prolog sense) with c. (If there is no such term, then this operation has no effect; if

there are several such terms, then one of them is arbitrarily selected for removal.)

3.read(c)@o-- Attempts to unify (in the Prolog sense) the term c with some term c’

in the exterior of object o. If successful, this unification binds variables in c, if any,

to matching sub terms of c’; if no unification is possible then this operation has no

effect. (The use of this primitive for retrieval will be illustrated later.)

4.destroy@o-- Removes object o from the system.

5.create(Id)@o-- Creates a new object using o as a prototype. The new object is

identical to o, except that it has a new, and unique, name. That is, the term id(i)of

the new object contains a unique, system-generated, symbol i; this symbol is bound

to the variable-parameter Id of this operation, and is thus returned to the invoker.

6.install(script)@o-- Installs in object o a new script, as specified by the

parameter script.6(script is expected to contain also the initial state of the

interior of the newly created object.)

7.deliver(m)@o-- This operation delivers the term m as a message to the agent of

object o, thus invoking an appropriate procedure, or method, in the script of o. (The

invocation mechanism depends, of course, on the language in which the script is

written, and, like the language itself, is left unspecified here.)

6The syntax of this parameter is left unspecified in the abstract model; in Darwin/2 it is the name of the file that contains the actual program.

8.poke(a)@o-- This operation can be used to modify (or examine) the interior of

object o, depending on the argument a, which is left unspecified here. (This

operation violates the assumed encapsulation of o; but such violations are

controllable by the law.)

9.error(diagnostics)@o-- This is a signal that an error occurred at object o.

The nature of this error is expected to be described by the argument diagnostics, its

effect is left unspecified in the abstract model.

Note that two kinds of error-conditions might arise due to the execution of a primitive operation: (1) The condition arising from the execution of the operation error(...)@o. (2) The condition arising from improper application of a primitive; say when the object addressed by o does not exist, when a message is delivered to an object that is not programmed, or to a programmed object that does not have a method for the given message. The treatment of both kinds of errors is language dependent, and should be specified by the interface to the language in question.

4.3. The Law

The law prescribes what should be the actual effect of any attempt by an object to send a message, as follows: Let a message-sending-event sent(s,m,t)be the act of an object s(the sender) sending a message m to an object t(the target). The effect of any such event is prescribed as the ruling of the law for this event. This ruling is a (possibly empty) sequence of primitive operations7which are to be carried out in response to the event in question. Such a ruling may depend on the event sent(s,m,t)itself, as well as on the control state of the system (i.e., on the exterior of all objects of the system) at the time that the event happens. (Note that in practice, the ruling of the law usually depends only on a small part of the control state; usually only on the control state of the sender of the message, and of its target.)

To illustrate the manner in which the ruling of the law may determine the effect of message-sending-events, we consider several examples of rulings for some specific events. (Note that this is not the way the ruling of law will be actually specified, which is defined later.)

7Those listed in Section 4.2.1.

example 1: ruling(sent(s,m,t)) = [deliver(m)@t]

example 2: ruling(sent(s,m,t)) = [deliver(m’)@t]

example 3: ruling(sent(s,m,t)) = [deliver(m)@t’]

example 4: ruling(sent(s,setLevel(7),t)) = [remove(level(L)@T,

add(level(7))@t] example 5: ruling(sent(s,getLevel(V),t)) = [read(level(V))@t] example 6: ruling(sent(s,m,t)) = [remove(token)@s,

add(token)@t,

deliver(m)@t]

example 7: ruling(sent(s,m,t)) = [error(...)@s]

example 8: ruling(sent(s,m,t)) = []

By the ruling in example 1, the message m sent by s to t will be delivered to its intended destination. This is, of course, the "natural" effect of sending a message, which in conventional systems is done automatically. Under LGA, on the other hand, the delivery of a message requires an explicit ruling of the law, which, as we shall see below, may be different from the above. The ruling in example 2, in particular, would cause a message m’, instead of m, to be delivered to t; while the ruling in example 3 would cause message m to be delivered to a different object t’. Thus, the law can, among other things, cause messages to be changed and/or rerouted. (We are using here the phrase "the law causes" to mean "the law prescribes"; this is justified because the law is strictly enforced under LGA.)

A message which ends up being delivered to some object (even if not in its original form or to the original target, as in examples 2 and 3) will be referred to as a regular message. As has already been pointed out, we assume here that such a message behaves as an invocation of a method (i.e., of a procedure) defined by the script of the object to which this message is delivered. This method is expected to finish its computation eventually, returning control, to the sender s. If the delivered message has some variable V in it, say if it has the form p(V), than V may be bound to some value by the receiver of the message, and it is thus returned to the sender. (The details of returning control and of binding values to variables by the receiver of a message, depend on the language in which the script of the receiver is written and are left unspecified here.)

A sent-event may not result in the delivery of any message at all, as is illustrated by examples

4 and 5. In example 4, the effect of a message setLevel(7)sent by s to t would be the execution of the primitive operations remove(level(L))@t and add(level(7))@t, resulting in an update of the exterior of t. Thus, this ruling defined directly the semantics of the message "setLevel(7)". Similarly, in example

5 the effect of a message getLevel(V)sent by s to t would be the execution of the primitive operation read(level(V))@t. This operation would bind variable V to the current level number of object t, if any. This binding would be returned to the sender s, when it resumes control.

The law may also combine the delivery of a message with causing side-effects to certain objects, as is illustrated by example 6. Under the ruling of this example, a message m sent by s to t would be delivered to its destination, but only after removing a term token from the exterior of s and adding this term to the exterior of t.

The ruling in example 7 consists of the primitive error(...)@s. We do not specify the precise semantics of this primitive, but it means to indicate that the sent-event in question is illegal. The precise effect of this ruling depends, among other things, on the way the law is enforced. The enforcer will either prevent such an illegal event from occurring (say, by not admitting into the system any object that may cause such an event), or it may force the sender of the offending message into some kind of error exterior (whose nature would depend on the programming language in which the sender of this message is written). Finally, the ruling of Example 8 is empty, which means simply that the sent-event in question has no effect.

To summarize, the ruling of the law for a given event e is a (possibly empty) sequence of primitive operations, which may depend on e itself, and on the exterior of the system (i.e., the exterior of all the objects of the system) at the time that the event e occurred. Formally speaking, let E be the set of all possible events, let CS be the set of all possible control states of a system, and let R be the set of all sequences of primitive-operations, then the law can be viewed as a function:

law:E×CS→R

Of course, the law cannot be represented purely by extension, that is, by listing the ruling explicitly for each possible event. In the following section we introduce a technique for specifying the law by intension.

4.3.1. The Interpretation of the Law Regarding Permanent Interactions

Since our law has been defined as dealing with events, it is not self evident how it can apply to permanent interactions, such as the existence of inheritance relation between two classes in an OO language. This is done as follows:

Consider a moment T when a collection of modules (say, classes) are grouped into a configuration C, to be compiled into a single executable code. Darwin interprets all permanent interactions between the modules of C as if they occur at time T, in a nondeterministic order. In other words, all permanent interaction in a given configuration are enforced when this configuration is created. For a detailed discussion of such interaction the reader is referred to [22]. of their formation under Darwin/2 is beyond the scope of this paper.

4.3.2. The Difference Between this and the Original LGA Model

The main novel aspect of this model of LGA, compared to the model underlining Darwin/1 [15], is the nature of the ruling of the law. Specifically, under Darwin/1 the ruling of the law can either deliver a message, possibly in a modified form, or block it. Under the present model, on the other hand, the ruling of a law for a given event may also cause some changes to be carried out, most significantly to the control state (exterior) of various objects. This enhanced significantly the expressive power of laws under LGA, as we shall see in Section 5. It also makes the compile-time enforcement of laws more challenging. It should be pointed out that analogous capabilities have been built into our model for distributed law-governed systems[16].

4.4. The Representation of Laws

The law of a system is actually defined by means of a Prolog program which, when presented with a goal sent(s,m,t)representing a message-sending-event, produces a list of primitive-operations constituting the ruling of the law for this event. (Note that the use of Prolog here is quite incidental, and can easily be replaced by other means).

The Prolog program representing the law is a set of rules which have the form: h :- b1,...,b k.The left-hand side of such a rule, called its head, consists of a single term, or goal. The right-hand side of the rule, called its body, consists of a sequence of zero or more goals. In addition to the standard types of Prolog goals,8the body of a rule may contain two distinguished types of goals which have special roles to play in the interpretation of the law. A goal of the first type, called a do-goal, has the form do(p@o). It means that the primitive-operation "p@o" should be added to the ruling being evaluated, to be carried out by the enforcer. (The word "do" is underlined for emphasis). A goal of the second type, called a relative-goal, has the form g@o. It causes the evaluation of the goal g to be performed relative to the exterior of object o, and it provides us with a means to make the ruling of the law dependent on the exterior of various objects. We will say some more about these two types of goals in due course.

Consider, now, a law L and an event e submitted to it for evaluation. To explain how the ruling for e is computed we note that the interpreter of the law maintains an auxiliary variable R, that starts as an empty list at the beginning of the evaluation, and whose value at the conclusion of the evaluation would become the ruling of law L for the given event e. Whenever a do-goal of the form do(p@o)is encountered, it is evaluated as follows: this goal succeeds if the term "p@o" is bound to a valid form of a primitive-operation. This primitive operation is then appended to the list

8Actually, certain types of Prolog goals, such as assert,retract and call, are not allowed in the law.

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论刑法中的犯罪构成 犯罪构成理论在犯罪体系及整个刑法学体系中占据核心地位，它是由资产阶级刑法学家首先提出并创立的，是资产阶级反对封建司法专制的历史性产物。犯罪构成是定罪量刑的法律标准，行为符合犯罪构成是负刑事责任的根据。 一、大陆法系犯罪构成理论：犯罪构成的概念最早起源于13世纪意大利宗教裁判上的“查究程序”或称“纠问手续”，其构成要件只有诉讼上的意义。直到19世纪德国著名刑法学家费尔巴哈、施鸠别尔才明确把犯罪构成作为刑事实体法上的概念来使用。现代意义上的犯罪构成理论，形成于本世纪初，德国学家贝林格首先提出了系统的犯罪构成要件理论，使构成要件上升为刑法总论的概念。贝林格主张犯罪论体系应有三部分组成，即构成要件该当性、违法性和有责性。认为构成要件是“犯罪类型的轮廓”，构成要件是确定可罚行为的基础。并认为，构成要件的符合性是犯罪成立的第一要件，同时犯罪还必须具备违法性及有责任诸要件。迈耶尔的犯罪理论体系继承了贝林格的犯罪理论体系的框架。但迈耶尔与贝林格的观点还有不同，他认为有些场合下，违法性是由主观要素所决定的，所以存在有主观的违法要素。梅次凯尔提出了由行为、不法和责任组成的犯罪体系，梅次凯尔把构成要件符合性论和违法性论合二为一构建成不法论。而小野清一郎赞同传统的又构成要件符合性、违法性和有责性构成犯罪论体系，但是，他认为构成要件既是违法的类型，也是有责类型。现在，大陆法系国家的构成要件理论则普遍认为：构成要件符合性、违法性和有责性是成立犯罪的三个条件，故构成要件符合性只是犯罪成立条件之一，构成要件是违法类型，即符合构成要件的行为原则上具有违法性；构成要件不仅包括客观的、记述的要素，而且包括主观的、规范的要素。 二、英美法系犯罪构成理论：以英、美为代表的犯罪构成体系，具有双层次性的特点。英美刑法的犯罪构成分为实体意义上的犯罪要件和诉讼意义上的犯罪要件。实体意义上的犯罪要件是指犯罪行为和犯罪意图，这种意义包含在犯罪定义之中。犯罪定义之外的责任要件是诉讼意义上的犯罪要件，通过合法抗辩事由体现出来。犯罪行为和犯罪心态，是犯罪本体要件。要成立犯罪，除应具有犯罪本体要件外，还必须排除合法辩护的可能，即具备责任充足条件。在理论结构上，

“八荣八耻”主要内容：

根据学校开展党的群众路线教育实践活动实施方案，我们党支部在此召开了关于“公与私、对与错、荣与辱界限”的专题讨论会，也很荣幸邀请到了我们学校学科建设处的齐锰老师，首先请我们的齐锰老师为我们做一下讲话，接着也希望大家可以畅所欲言，深刻讨论这个专题。 座谈会上，干部们按照人事教育科的安排，结合本职工作岗位，对照“理想信念、党章党纪、民心民生、先辈先进”四面镜子，紧紧围绕“公与私、对与错、荣与辱界限”专题进行广泛的大讨论。 讨论中，干部们深刻理解在国家层面上倡导的富强、民主、文明、和谐，在社会层面的价值取向上倡导的自由、平等、公正、法治，在公民个人层面的价值准则上倡导的爱国、敬业、诚信、友善的社会主义核心价值观内涵的基础上，联系实际就如何做好本职工作实现自身价值、如何把“公与私、对与错、荣与辱”的是非观念贯穿于工作的各方面进行了交流，使核心价值观真正触及每名干部的思想灵魂，真正解决实际问题。 通过对社会主义核心价值观的学习讨论，能够使广大干部进一步深入了解国税工作的重大意义，激发其工作热情，引导国税干部追求正确的世界观、人生观、价值观，使每一位国税干部不断提高自身的综合素质，增强锐意进取、秉公执法、廉洁从税的敬业态度具有很强的现实意义。 讨论结束后，干部们表示：只有把我们的价值观从理论落实到实际中去，才能把我们的价值观融入到我们的工作和生活中去，在平凡的岗位上实践着全心全意为人民服务的宗旨，脚踏实地地履行着工作职责，满腔热情地为企业和纳税人服务。 对照“理论思想、党章党纪、民心民生、先辈先进”四面镜子，厘清“公与私、对与错、荣与辱”三对关系界限，树立起观大势、善谋事、肯干事的工作导向，全力推动全州经济社会发展。 会议强调，“公与私、对与错、荣与辱”看似三对简单的矛盾对立关系，对于我们党员来说，这三对关系泾渭分明，来不得半点混淆。厘清三种关系的界限，是党员树立正确的群众观、权力观、民族观和事业观的前提。作为我们党支部要贯彻好学校的精神，突出抓好党员与群众的关系，紧密联系普通同学。

最小二乘法原理及应用【文献综述】

毕业论文文献综述 信息与计算科学 最小二乘法的原理及应用 一、国内外状况 国际统计学会第56届大会于2007年8月22-29日在美丽的大西洋海滨城市、葡萄牙首都里斯本如期召开。应大会组委会的邀请，以会长李德水为团长的中国统计学会代表团一行29人注册参加了这次大会。北京市统计学会、山东省统计学会，分别组团参加了这次大会。中国统计界（不含港澳台地区）共有58名代表参加了这次盛会。本届大会的特邀论文会议共涉及94个主题，每个主题一般至少有3-5位代表做学术演讲和讨论。通过对大会论文按研究内容进行归纳，特邀论文大致可以分为四类：即数理统计，经济、社会统计和官方统计，统计教育和统计应用。 数理统计方面。数理统计作为统计科学的一个重要部分，特别是随机过程和回归分析依然展现着古老理论的活力，一直受到统计界的重视并吸引着众多的研究者。本届大会也不例外。 二、进展情况 数理统计学19世纪的数理统计学史, 就是最小二乘法向各个应用领域拓展的历史席卷了统计大部分应用的几个分支——相关回归分析, 方差分析和线性模型理论等, 其灵魂都在于最小二乘法; 不少近代的统计学研究是在此法的基础上衍生出来, 作为其进一步发展或纠正其不足之处而采取的对策, 这包括回归分析中一系列修正最小二乘法而导致的估计方法。 数理统计学的发展大致可分 3 个时期。① 20 世纪以前。这个时期又可分成两段，大致上可以把高斯和勒让德关于最小二乘法用于观测数据的误差分析的工作作为分界线，前段属萌芽时期，基本上没有超出描述性统计量的范围。后一阶段可算作是数理统计学的幼年阶段。首先，强调了推断的地位，而摆脱了单纯描述的性质。由于高斯等的工作揭示了最小二乘法的重要性，学者们普遍认为，在实际问题中遇见的几乎所有的连续变量，都可以满意地用最小二乘法来刻画。这种观点使关于最小二乘法得到了深入的发展，②20世纪初到第二次世界大战结束。这是数理统计学蓬勃发展达到成熟的时期。许多重要的基本观点和方法，以及数理统计学的主要分支学科，都是在这个时期建立和发展起来的。这个时期的成就，包含了至今仍在广泛使用的大多数统计方法。在其发展中，以英国统计学家、生物学家费希尔为代表的英国学派起了主导作用。③战后时期。这一时期中，数理统计学在应用和理论两方面继续获得很大的进展。

(和谐社会演讲稿)八荣八耻对国家的重要意义

八荣八耻对国家的重要意义 胡锦涛总书记提出的“八荣八耻”精辟地阐述了社会主义荣辱观的深刻内涵和社会主义道德规范的本质要求，体现了中华民族传统美德、党的优良传统和作风与时代精神的凝聚和升华，为党和国家、社会、人民群众树起了道德建设的新标杆，更为中华民族的复兴伟业增添了巨大的智力支持和行为规范。 先秦著名政治家管子在《牧民》中写到“礼仪廉耻乃国之四维，四维不张，国乃灭亡。”从管子的论述我们可以看到礼仪廉耻作为四种重要纲领对于维护国家安定、社会和谐、人们安居乐业的重要性，同时也对树立良好的国际形象、国家在国际竞争中的有利地位以及社会的安定团结具有更深厚的现实意义。 如果国家没有正确的荣辱观就不能树立良好的国际形象。顾炎武在《日知录》卷十三中认为“人之不廉，而至于悖礼犯义，其原生于无耻也。故士大夫之无耻，是谓国耻。”在世界政治多极化、经济全球化的今天，你中有我，我中有你，已经形成了相互依赖的共同体。如果整个国家没有高尚的道德情操、本民族独特的美德优势以及先进的思想和文化统御着国家，那么必将国将不国。如果国际形象好，并且是对国际上负起真正的责任，那么就会以自身正确的荣辱观和高尚的品德温仪天下，世界就会因你的光明未来而蜂拥而至、趋之若骛，最终达到以德服人。 如果国家没有正确的荣辱观就不能保证在激烈的国际竞争中始终处于优势地位。在竞争异常激烈的世界里，如果不能树立正确的荣辱观，不能凝聚本国人民的智慧和力量，不能沿着人类发展的方向构筑先进的思想和道德标准，就会出现道德颓废、是非不辩、胸无大志，浑浑噩噩，整个国家就不能带领本国人民实现任何伟大的战略目标，就完全有可能被具有更高道德标准的国家和民族所打败。 如果国家没有正确的荣辱观就不能保证社会的安定。顾炎武在《廉耻》中认为“廉耻，立人之大节。盖不廉，则无所不取，不耻则无所不为。”廉耻之心是人类所独有的，如果没有廉耻，就不能对世界和人类的真善美与假恶丑的褒奖和贬斥，更不能真正高扬清正、伐拓混浊，人民就会丧失明辨大是大非的能力，就可以为所欲为，那么社会的法制、科学的道德规范必将被破坏怠尽，社会将出现混乱，国家元气也必然大受损伤。因此，在构建和谐社会和实现国家富强的道路一定要深入学习和掌握“八荣八耻”的深刻内涵和本质要求，并以自身的表率真切地实践“八荣八耻”。

最小二乘法综述及举例

最小二乘法综述及算例 一最小二乘法的历史简介 1801年，意大利天文学家朱赛普·皮亚齐发现了第一颗小行星谷神星。经过40天的跟踪观测后，由于谷神星运行至太阳背后，使得皮亚齐失去了谷神星的位置。随后全世界的科学家利用皮亚齐的观测数据开始寻找谷神星，但是根据大多数人计算的结果来寻找谷神星都没有结果。时年24岁的高斯也计算了谷神星的轨道。奥地利天文学家海因里希·奥尔伯斯根据高斯计算出来的轨道重新发现了谷神星。 高斯使用的最小二乘法的方法发表于1809年他的著作《天体运动论》中。 经过两百余年后，最小二乘法已广泛应用与科学实验和工程技术中，随着现代电子计算机的普及与发展，这个方法更加显示出其强大的生命力。 二最小二乘法原理 最小二乘法的基本原理是：成对等精度测得的一组数据),...,2,1(,n i y x i i =，是找出一条最佳的拟合曲线，似的这条曲线上的个点的值与测量值的差的平方和在所有拟合曲线中最小。 设物理量y 与1个变量l x x x ,...,2,1间的依赖关系式为:)(,...,1,0;,...,2,1n l a a a x x x f y =。 其中n a a a ,...,1,0是n +l 个待定参数,记()2 1 ∑=- = m i i i y v s 其中 是测量值, 是由己求 得的n a a a ,...,1,0以及实验点),...,2,1)(,...,(;,2,1m i v x x x i il i i =得出的函数值 )(,...,1,0;,...,2,1n il i i a a a x x x f y =。 在设计实验时, 为了减小误差, 常进行多点测量, 使方程式个数大于待定参数的个数, 此时构成的方程组称为矛盾方程组。通过最小二乘法转化后的方程组称为正规方程组(此时方程式的个数与待定参数的个数相等) 。我们可以通过正规方程组求出a 最小二乘法又称曲线拟合, 所谓“ 拟合” 即不要求所作的曲线完全通过所有的数据点, 只要求所得的曲线能反映数据的基本趋势。 三曲线拟合 曲线拟合的几何解释: 求一条曲线, 使数据点均在离此曲线的上方或下方不远处。 （1）一元线性拟合 设变量y 与x 成线性关系x a a y 10+=,先已知m 个实验点),...,2,1(,m i v x i i =，求两个未知参数1,0a a 。 令()2 1 10∑ =--=m i i i x a a y s ，则1,0a a 应满足1,0,0==??i a s i 。 即 i v i v

《操作系统原理》5资源管理(死锁)习题

第五章死锁练习题 (一)单项选择题 1．系统出现死锁的根本原因是( )。 A．作业调度不当B．系统中进程太多C．资源的独占性D．资源管理和进程推进顺序都不得当 2．死锁的防止是根据( )采取措施实现的。 A．配置足够的系统资源B．使进程的推进顺序合理 C．破坏产生死锁的四个必要条件之一D．防止系统进入不安全状态 3．采用按序分配资源的策略可以防止死锁．这是利用了使( )条件不成立。 A．互斥使用资源B循环等待资源C．不可抢夺资源D．占有并等待资源 4．可抢夺的资源分配策略可预防死锁，但它只适用于( )。 A．打印机B．磁带机C．绘图仪D．主存空间和处理器 5．进程调度算法中的( )属于抢夺式的分配处理器的策略。 A．时间片轮转算法B．非抢占式优先数算法C．先来先服务算法D．分级调度算法 6．用银行家算法避免死锁时，检测到( )时才分配资源。 A．进程首次申请资源时对资源的最大需求量超过系统现存的资源量 B．进程己占用的资源数与本次申请资源数之和超过对资源的最大需求量 C．进程已占用的资源数与本次申请的资源数之和不超过对资源的最大需求量，且现存资源能满足尚需的最大资源量 D进程已占用的资源数与本次申请的资源数之和不超过对资源的最大需求量，且现存资源能满足本次申请量，但不能满足尚需的最大资源量 7．实际的操作系统要兼顾资源的使用效率和安全可靠，对资源的分配策略，往往采用( )策略。 A死锁的防止B．死锁的避免C．死锁的检测D．死锁的防止、避免和检测的混合 (二)填空题 1．若系统中存在一种进程，它们中的每一个进程都占有了某种资源而又都在等待其中另一个进程所占用的资源。这种等待永远不能结束,则说明出现了______。 2．如果操作系统对______或没有顾及进程______可能出现的情况，则就可能形成死锁。 3．系统出现死锁的四个必要条件是：互斥使用资源，______，不可抢夺资源和______。 4．如果进程申请一个某类资源时，可以把该类资源中的任意一个空闲资源分配给进程，则说该类资源中的所有资源是______。 5．如果资源分配图中无环路，则系统中______发生。 6．为了防止死锁的发生，只要采用分配策略使四个必要条件中的______。 7．使占有并等待资源的条件不成立而防止死锁常用两种方法：______和______. 8静态分配资源也称______，要求每—个进程在______就申请它需要的全部资源。 9．释放已占资源的分配策略是仅当进程______时才允许它去申请资源。 10．抢夺式分配资源约定，如果一个进程已经占有了某些资源又要申请新资源，而新资源不能满足必须等待时、系统可以______该进程已占有的资源。 11．目前抢夺式的分配策略只适用于______和______。 12．对资源采用______的策略可以使循环等待资源的条件不成立。 13．如果操作系统能保证所有的进程在有限的时间内得到需要的全部资源，则称系统处于______。14．只要能保持系统处于安全状态就可______的发生。 15．______是一种古典的安全状态测试方法。 16．要实现______，只要当进程提出资源申请时，系统动态测试资源分配情况，仅当能确保系统安全时才把资源分配给进程。

Application对象基本操作应用示例

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“八荣八耻”主要内容：

一、“八荣八耻”主要内容： 以热爱祖国为荣、以危害祖国为耻， 以服务人民为荣、以背离人民为耻， 以崇尚科学为荣、以愚昧无知为耻， 以辛勤劳动为荣、以好逸恶劳为耻， 以团结互助为荣、以损人利己为耻， 以诚实守信为荣、以见利忘义为耻， 以遵纪守法为荣、以违法乱纪为耻， 以艰苦奋斗为荣、以骄奢淫逸为耻。 二、“八荣八耻”的重要意义： 胡锦涛总书记在看望出席全国政协十届四次会议委员时提出的“八荣八耻”重要论述，涵盖爱国主义、集体主义、社会主义思想，体现中华民族传统美德和时代要求，反映社会主义世界观、人生观、价值观，明确了当代中国最基本的价值取向和行为准则，是马克思主义道德观的精辟概括，是新时期社会主义道德的系统总结，是以人为本、全面协调可持续科学发展观的重要组成部分，是新形势下社会主义思想道德建设的重要指导方针。大力倡导以“八荣八耻”为主要内容的社会主义荣辱观，对于弘扬以爱国主义为核心的民族精神和以改革创新为核心的时代精神，加强社会主义思想道德建设，巩固马克思主义在意识形态领域的指导地位，打牢全国人民团结奋斗的共同思想基础，形成积极健康向上的社会风尚，具有重大的现实意义和深远的历史意义。 三、“八荣八耻”诗词汇集 1、知荣耻行万里 莺歌燕舞三春日神州大地新风起 一夜好雨伴轻雷尽知“八荣”和“八耻” 从来中华多正气赤胆爱国震西夷 俯仰上下五千年心系百姓垂青史 近代之辱因无知崇尚科学雪国耻 千秋自力凭劳动万代更生丰衣食 齐心协力动天地团结互助泰山移 诚以待人诚为本守信处世守金玉 遵纪才能促和谐守法还须懂法律 勤俭创业富家底艰苦奋斗今胜昔 神五飞天常入梦生逢盛世自欣喜 盼得天规顺民意风正帆悬正此时 2、八荣八耻“七字歌谣” “八荣八耻”要牢记，“八荣八耻”要明晰。 爱国爱校爱集体，为了祖国齐努力。 做人不能顾自己，服务他人记心里。 好逸恶劳是耻辱，参加劳动要积极。 勤俭节约不能忘，铺张浪费要摒弃。 尊老爱幼是美德，团结友爱创美誉。 诚实守信最重要，做人诚信要牢记。

操作系统死锁练习及答案

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怎样理解树立社会主义荣辱观的重要意义? 树立和践行社会主义荣辱观是一项社会系统工程，不仅要靠广泛的宣传教育，更需要各方面的共同努力。 首先要大力营造浓厚的舆论氛围。正确价值观的确立良好社会风尚的形成离不开舆论力量的倡导和推动。要以践行社会主义荣辱观、加强思想道德建设为主题，以促进社会风气改善为目的，形成“知荣辱、讲正气、树新风、促和谐”的文明风尚。充分发挥大众传媒的独特优势运用多种形式大力宣传“八荣八耻”的重大意义和深刻内涵宣传社会主义荣辱观的基本内容和精神实质宣传广大干部群众践行社会主义荣辱观的生动实践和新鲜经验使“八荣八耻”的基本要求家喻户晓、深入人心成为社会共识。 官气正则民风清。树立和践行社会主义荣辱观，需要领导干部发挥带头和示范作用。领导就是领路引导，干部就是先行一步。领导干部的行为及其体现出来的思想境界、道德情操，直接影响着一个地方、一个单位风气的形成，是社会行为规范的风向标，对社会道德起着重要的示范和导向作用。每个领导干部都要以“八荣八耻”为镜子，日日照、时时省，以身作则、率先垂范，“常修为政之德，常思贪欲之害，常怀律己之心”，做扬荣抑耻的积极实践者，用自己的模范行动和人格力量为群众作出榜样。 树立和践行社会主义荣辱观，重点是青少年。要坚持以学校为主阵地，把荣辱观教育纳入学校德育工作的全过程渗透到学校教育的各个方面、各个环节。把“八荣八耻”的基本要求体现到大中小学的政治理论课和思想品德课教材之中。根据青少年的认知水平、行为能力和心理特点科学规划教育内容改进教学方式方法增强教育的吸引力、感染力。把树立社会主义荣辱观作为师德建设的重要内容引导广大教师学为人师、行为世范用自己的模范言行影响和带动学生。 古人说，“知之惟艰，行之更艰”。树立和践行社会主义荣辱观，要“真知”，更要“真行”，特别是要用制度来约束和规范人们的行为。要把社会主义荣辱观的要求贯穿到各项制度的制定和执行的过程中，渗透到社会管理之中。广泛发动群众对照“八荣八耻”，修订完善市民公约、乡规民约、职业规范、学生守则等具体行为准则，让人们在参与中受到教育、得到提高。重视发挥法律法规对道德建设的保障作用，依法惩治那些败坏道德的不法行为，用法律手段引导和规范社会道德生活。 “荣辱之责，在乎己而不在乎人”。只要我们每个人都行动起来，按照“八荣八耻”的要求，明荣辱之分、做当荣之事、拒为辱之行，聚沙成塔，集腋成裘，就能汇集起知荣辱、树新风的强大力量，一个更加风清气正的社会就离我们不会太远。 学生作为青年一代中文化层次较高的群体，更是实现国家富强、中华振兴的希望所在。但是，