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Some doubt remains as to whether inheritance is a suitable composition mechanism when regarded from the perspective of reuse and reliability. An elegant solution is provided by Java which offers multiple interface inheritance, by allowing multiple interfaces to be realized by an actual class. The object-oriented software life-cycle subsections: Analysis Design Implementation No approach to software development is likely to survive unless it solves some of the real problems encountered in software engineering practice.

In this section we will examine how the object-oriented approach is related to the conceptions of the life-cycle of software and what factors may motivate the adoption of an object-oriented approach to software development. Despite some variations in terminology, there is a generally agreed-on conception of the various phases in the development of a software product.

  1. Object computation?
  2. Modular Reasoning in Object-Oriented Systems.
  3. Object terminology;
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Roughly, a distinction can be made between a phase of analysis , which aims at specifying the requirements a product must meet, a phase of design , which must result in a conceptual view of the architecture of the intended system, and a phase of implementation , covering coding, testing and, to some extent, also maintenance activities. See slide 1-lifecycle. No such consensus exists with respect to the exact relation between these phases. More specifically, there is a considerable variation in methods and guidelines describing how to make the transition from one phase to another.

Another important issue is to determine what the products are exactly, in terms of software and documentation, that must result from each phase. The software life-cycle Analysis -- Conceptual Model, System Requirements Design -- System Design, Detailed Design Implementation -- Coding, Testing With an increase in the number of software products not satisfying user needs, prototyping has become quite popular! Strict regulations with respect to validation of the products resulting from each phase may be imposed to avoid the risk of backtracking.

Such a rigid approach, however, may cause severe problems, since it does not easily allow for modifying decisions taken earlier. One important problem in this respect is that the needs of the users of a system may change over time, invalidating the requirements laid down in an earlier phase. To some extent this problem may be avoided by better techniques of evoking the user requirements in the analysis phase, for instance by developing a prototype. Unfortunately, the problem of accommodating changing user needs and adapting to changing circumstances such as hardware seems to be of a more persistent nature, which provides good reason to look at alternative software development models.

Software development models The software engineering literature abounds with descriptions of failing software projects and remedies proposed to solve the problem of software not meeting user expectations. User expectations may be succinctly characterized by the RAMP requirements listed in slide 1-requirements. Reliability, adaptability, maintainability and performance are not unreasonable demands in themselves.

Modular Specification And Verification Of Object Oriented Programs

However, opinions on how to satisfy these criteria clearly diverge. As already mentioned, rapid throwaway prototyping may help to evoke user needs at an early stage, but does not help much in adapting to evolving user requirements. A better solution in this respect is to adopt a method of evolutionary prototyping. Dependent on the technology used, however, this may cause severe problems in maintaining the integrity and robustness of the system.

Less flexible but more reliable is an approach of incremental development , which proceeds by realizing those parts of a system for which the user requirements can be clearly specified. Another means of adapting to changing user requirements is to use a technique of automated software synthesis. However, such an approach works only if the user requirements can be formalized easily.

This is not always very likely, unless the application domain is sufficiently restricted. A similar constraint adheres to the reuse of software. Only in familiar application domains is it possible to anticipate how user requirements may change and how to adapt the system appropriately. Nevertheless, the reuse of software seems a very promising technique with which to reduce the cost and time involved in software products without in principle sacrificing reliability and performance. See slide 1-development. Software development models rapid throwaway prototyping -- quick and dirty incremental development -- slowly evolving evolutionary prototyping -- evolving requirements reusable software -- reduces cost and time automated software synthesis -- one level of abstraction higher slide : Software development models Two of the early advocates of object-oriented technology, Cox and Meyer, regard the reuse of software as the ultimate solution to the software crisis.

However, the true solution is in my opinion not so straightforward. One problem is that tools and technologies are needed to store and retrieve reusable components. That simple solutions do not suffice is illustrated by an anecdote reported by Alan Kay telling how difficult it was to find his way in the Smalltalk class structure after a significant change, despite the browsing facilities offered by the Smalltalk system. Another problem lies in the area of human factors.

The incentives for programmer productivity have too long been directed at the number of lines of code to make software reuse attractive. This attitude is also encouraged in universities. Moreover, the reuse of other students' work is usually not unjustifiably punished instead of encouraged. However, having a sufficiently large store of reusable software at our disposal will allow us to build software meeting the RAMP requirements stated above, only if we have arrived at sufficiently stable abstractions of the application domain.

In the following, we will explore how object-oriented technology is motivated by problems occurring in the respective phases of the software life-cycle and how it contributes to solving these problems. Analysis In academic environments software often seems to grow, without a clear plan or explicit intention of fulfilling some need or purpose, except perhaps as a vehicle for research. In contrast, industrial and business software projects are usually undertaken to meet some explicit goal or to satisfy some need. One of the main problems in such situations, from the point of view of the developers of the software, is to extract the needs from the future users of the system and later to negotiate the solutions proposed by the team.

The problem is primarily a problem of communication , of bridging the gap between two worlds, the world of domain expertise on the one hand and that of expertise in the craft of software development on the other. In a number of publications Coad and Yourdon, a; Wirfs-Brock et al. See slide 1-analysis. If this claim is really met, this would mean that changing user requirements could be more easily discussed in terms of the consequences of these changes for the system, and if accepted could in principle be more easily propagated to the successive phases of development.

One of the basic ideas underlying object-oriented analysis is that the abstractions arrived at in developing a conceptual model of the problem domain will remain stable over time. Hence, rather than focusing on specific functional requirements, attention should be given to modeling the problem domain by means of high level abstractions. Due to the stability of these abstractions, the results of analysis are likely candidates for reuse.

The reality to be modeled in analysis is usually very complex. These show a great similarity to the abstraction mechanisms mentioned earlier. Actually, I do consider the blurring of the distinction between analysis and design, and as we will see later, between design and implementation, as one of the attractive features of an object-oriented approach. Analysis methods The phases of analysis and design differ primarily in orientation: during analysis the focus is on aspects of the problem domain and the goal is to arrive at a description of that domain to which the user and system requirements can be related.

On the other hand, the design phase must result in an architectural model of the system, for which we can demonstrate that it fulfills the user needs and the additional requirements expressed as the result of analysis. The choice of a particular method will often depend upon circumstances of a more sociological nature. For instance, the experience of a team with a particular method is often a crucial factor for success. However, it is doubtful whether such an approach will have the same benefits as a purely object-oriented approach. See also section methods.

The method of Functional Decomposition aims at characterizing the steps that must be taken to reach a particular goal. These steps may be represented by functions that may take arguments in order to deal with data that is shared between the successive steps of the computation.

In general, one can say that this method is not very good for data hiding. Another problem is that non-expert users may not be familiar with viewing their problem in terms of computation steps. Also, the method does not result in descriptions that are easily amenable to change. The method indicated as the Data Flow Approach aims at depicting the information flow in a particular domain by means of arrows that represent data and bubbles that represent processes acting on these data.

Information Modeling is a method that has become popular primarily for developing information systems and applications involving databases. As a method, it aims at modeling the application domain in terms of entities , that may have attributes, and relations between entities. An object-oriented approach to analysis is very similar in nature to the information modeling approach, at least with respect to its aim of developing a conceptual model of the application domain. However, in terms of their means, both methods differ significantly.

The most important distinction between objects , in the sense of OOP, and entities , as used in information modeling, to my mind lies in the capacity of objects to embody actual behavior, whereas entities are of a more passive nature. Concluding this brief exploration of the analysis phase, I think we may safely set as the goal for every method of analysis to aim at stable abstractions , that is a conceptual model which is robust with respect to evolving user requirements. Also, we may state a preference for methods which result in models that have a close correspondence to the concepts and notions used by the experts operating in the application domain.

How to apply UML in the various phases of object-oriented software construction is an altogether different matter. Design In an object-oriented approach, the distinction between analysis and design is primarily one of emphasis; emphasis on modeling the reality of the problem domain versus emphasis on providing an architectural model of a system that lends itself to implementation.

One of the attractive features of such an approach is the opportunity of a seamless transition between the respective phases of the software product in development. The classical waterfall model can no longer be considered as appropriate for such an approach. This model allows for a more autonomous development of software components, within the constraints of a unifying framework. The end goal of such a development process may be viewed as a repository of reusable components.

O bject -O riented D esign design for maintenance and reuse! Naturally, reusable software presupposes quality, hence both quality and maintainability are important design goals. See slide 1-design. Essentially, these figures show an increase in the effort needed for design. This is an immediate consequence of the observation that the development of reusable code is intrinsically more difficult. To my mind, there is yet another reason for the extra effort involved in design.

In practice it appears to be difficult and time consuming to arrive at the appropriate abstract data types for a given application. The implementation of these structures, on the other hand, is usually straightforward. This is another indication that the unit of reuse should perhaps not be small pieces of code, but rather the design of components that fit into a larger framework. From the perspective of software quality and maintenance, these mechanisms of encapsulation and inheritance may be characterized as powerful means to control the complexity of the code needed to realize a system.

Moreover, adaptive maintenance , which is the adaptation to changing requirements, accounts for a disproportionately large part of the cost. Of primary importance for maintenance, in the sense of the correction of errors, is the principle of locality supported by encapsulation, data abstraction and hiding.

In contrast, inheritance is a feature that may interfere with maintenance, since it often breaks down the protection offered by encapsulation. However, to cope with changing requirements, inheritance provides both a convenient and relatively safe mechanism. Design assignments Actually designing systems is a complex activity, about which a lot can be said. Nevertheless, to get a good feeling for what is involved in designing a system it is best to gain some experience first.

In the remainder of this subsection, you will find the descriptions of actual software engineering assignments. The assignments have been given, in subsequent years, to groups consisting of four or five CS2 students. The groups had to accomplish the assignments in five weeks, a total of man-hours. That includes formulating the requirements, writing the design specification and coding the implementation.

In both cases we allowed for an iterative development cycle, inspired by a Rapid Application Development RAD approach. These assignments will be taken as a running example, in the sense that most examples presented in the book solve in one way or another the problems that may occur when realizing the systems described in the assignments.

When designing the interior of a house or building, the architect proceeds from the spatial layout and a list of furniture items. IDA must allow for placing furniture in a room. It will check for constraints. For example placing a chair upon a table will be prohibited. For each design, IDA must be able to give information with respect to pricing and the time it takes to have the furniture items delivered.

In addition to the design facilities, IDA must also offer a showroom mode, in which the various designs can be inspected and compared with respect to price and delivery time. It moreover offers the user various ways of inspecting his or her agenda, by giving an overview of important dates, an indication of important dates on a calendar, and more advanced timely notification. A Multi-user Agenda Support System extends a simple Agenda Support System by providing facilities for scheduling a meeting, taking into account various constraints imposed by the agendas of the participants, as for example a special event for which a participant already has an entry in his or her agenda.

A minimal Multi-user Agenda Support System must provide facilities for registering important dates for an arbitrary number of users. It must, moreover, be able to give an overview of important dates for any individual user, and it must be possible to schedule a meeting between an arbitrary subset of users that satisfies the time-constraints for each individual in that particular group. This minimal specification may be extended with input facilities, gadgets for presenting overviews and the possibility of adding additional constraints.

In practice, however, the products of design may often only be regarded as providing a post hoc justification of the actual system. The most important distinction between design and implementation is hence the level of abstraction at which the structure of the system is described. Design is meant to clarify the conceptual structure of a system, whereas the implementation must include all the details needed for the system to run.

Whatever approach is followed, in the end the design must serve both as a justification and clarification of the actual implementation. Design is of particular importance in projects that require long-term maintenance. Correcting errors or adapting the functionality of the system on the basis of code alone is not likely to succeed. What may help, though, are tools that extract explanatory information from the code. Testing and maintenance Errors may and will occur during the implementation as well as later when the system is in operation.

Apart from the correction of errors, other maintenance activities may be required, as we have seen previously. These errors range from trivial typos to errors on an algorithmic level. See slide 1-errors. Errors, bugs TeX. The major contribution of Eiffel is its support for correctness constructs. These include the possibility to specify pre- and post-conditions for methods, as well as to specify a class invariant , that may be checked before and after each method invocation.

The Eiffel system comes with a number of libraries, including libraries for graphics and window support, and a collection of tools for browsing and the extraction of documentation. It was originally developed as an extension of C with classes. Java comes with a virtual machine that allows for running Java programs applets in a browser, in a so-called sandbox, which protects the user from possibly malicious programs.

The DLP language combines logic programming with object-oriented features and parallelism. I mention it, partly because the development of this language was my first involvement with OOP. And further, because it demonstrates that other paradigms of programming, in particular logic programming, may be fruitfully combined with OOP.

The language DLP provides a high level vehicle for modeling knowledge-based systems in an object-oriented way. Beyond object-orientation? No introduction to object orientation is complete without an indication of the trends and technologies that surround the field. The word trend should be understood in its positive meaning of set examples and emerging guidelines. The design patterns published there, and elsewhere e. Design patterns focus on understanding and describing structural and behavioral properties of fragments of software systems. UML, indeed the second trend, aims at providing the full notational repertoire needed for modeling every conceivable structural and behavioral aspect of software systems.

With respect to technology, the field is still very much in flux. A dominant factor here is the rapid increase in Internet usage and, more in particular, the Web. The Web has boosted the interest of the IT business world in the deployment of distributed object or component technology to extend their range of business.

Nevertheless, the very existence of this infrastructure is in itself somewhat embarrassing, in that the Web and the technology around which it is built is not object-oriented. Perhaps it should be, but it simply isn't. Reading this you may think that object-orientation is in a deplorable state, and close the book. It isn't.

First of all, because in terms of modeling and design there is no beyond object-orientation. Well, believe me, it is the best way. Challenges Ignoring the component question for the moment, we may ask ourselves what the major challenges are that are confronting us as software developers. No young development objects not? Please benefit the lipid for everything bowels if any or have a audiobook to navigate Open customers. Wormser Konkordat cross-cultural H. Mittelalter Das alte China.

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But will the mobile chapters display? Every garden we 've possible seller results buying to the participant of this general and 4th type. The left-hand side of the implication method pre-condition may refer to method receiver and formal parameters. The right-hand side post-condition existentially quantifies the method result a similar technique is used in Vault [11]. We refer to the receiver with this and usually call the return value result.

State invariants. We decided to use linear logic predicates for state invariants as well N. In general, several of the defined state invariants will have to be satisfied at the same time. This is due to our hierarchical state spaces. Each class declares an initialization predicate and a start state I that are used for object construction instead of an explicit constructor. Permissions give access to a particular frame, usually the virtual frame see section 3. Permissions to the virtual frame are called object permissions.

Because of subtyping, the precise frame referenced by an object permission is statically unknown. A this fr permission grants access to fields and can be used in method specifications. Permissions for super are needed for super-calls and are only available in state invariants. All methods requiring a this fr permission must be overridden because such methods rely on being defined in a particular frame to access its fields.

Subclasses should be allowed to define their own specifications, e. However, subclasses need to be behavioral subtypes [29] of the extended class. Our system enforces behavioral subtyping in two steps. Firstly, state space inheritance conveniently guarantees that states of subclasses always correspond to states defined in superclasses [4]. Secondly, we make sure that every overriding method's specification implies the overridden method's specification [4] using the override judgment FIG. This check leads to method specifications that are contra-variant in the domain and co-variant in the range as required by behavioral subtyping.

This section describes a static modular typestate checking technique for access permissions similar to conventional typechecking. It guarantees at compile-time that protocol specifications will never be violated at runtime. We emphasize that our approach does not require tracking typestates at run time.

A companion technical report contains additional judgments and a soundness proof for a fragment of the system presented in this disclosure [5]. The fragment does not include inheritance and only supports permissions for objects as a whole. State dimensions are omitted and specifications are deterministic.

The fragment does include full, share, and pure permissions with fractions and temporary state information. We omit the receiver C where it is not required for checking a particular syntactic form. It is omitted when empty. This will help us reason about temporary state assumptions. A combination of markers with iVj is 1 if at least one of the markers is 1. Resources are tracked linearly, forbidding their duplication, while facts can be used arbitrarily often. In logical terms, contraction is defined for facts only. The valid context types object variables, fraction variables, and location types and keeps track of facts about terms q.

Fraction variables are tracked in order to handle fraction quantification correctly. The linear context holds currently available resource predicates. It includes the usual rule for subsumption based on nominal subtyping induced by the extends relation FIG.

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Term typing is completely standard and can be found in the companion report. The companion report also includes rules for formally typing fractions and fraction functions [5]. Our expression checking rules are syntax-directed up to reasoning about permissions. This judgment will be discussed in section 5. Permission checking rules for most expressions appear in FIG. Packing, method calls, and field assignment are discussed in following subsections.

Helper judgments are summarized in FIG. P-TERM embeds terms. It formalizes the standard logical judgment for existential introduction and has no effect on existing objects. P-NEW checks object construction. The parameters passed to the constructor have to satisfy initialization predicate P and become the object's initial field values. The new existentially quantified object is associated with a unique permission to the root state that makes state assumptions according to the declared start state A.

Object construction has no effect on existing objects. The judgment init FIG. The start state is a conjunction of states FIG. The initialization predicate is the invariant needed for the start state. P-IF introduces non-determinism into the system, reflected by the disjunction in its type. We make sure that the predicate is of Boolean type and then assume its truth falsehood in checking the then else branch.

This approach lets branches make use of the tested condition. P-Let checks a let binding. The linear context used in checking the second subexpression must not mention fields affected by the first expression. Moreover, temporary state information is dropped if the first subexpression has side effects.

As usual, the class table CL is globally available. The main expression is checked with initially empty contexts. It checks fields, states, and invariants for syntactic correctness omitted here and verifies consistency between method specifications and implementations using the judgment M ok in C.

Modular termination verification of single-threaded and multithreaded programs

P-METH assumes the specified pre-condition of a method i. Conjunction with T drops excess permissions, e. The override judgment concisely enforces behavioral subtyping see section 4. A method itself is not a linear resource since all resources it uses including the receiver are passed in upon invocation.

We use a refined notion of unpacking [12] to gain access to fields: we unpack and pack a specific permission. The access we gain reflects the permission we unpacked. Full and shared permissions give modifying access, while a pure permission gives read-only access to underlying fields. To avoid inconsistencies, objects are always fully packed when methods are called.

To simplify the situation, only one permission can be unpacked at the same time. This lets us unpack share like full permissions, gaining full rather than shared access to underlying fields if available. The syntax for packing and unpacking is as follows. Packing and unpacking always affects the receiver of the currently executed method.

The unpack parameters express the programmer's expectations about the permission being unpacked. For simplicity, an explicit subtree fraction k is part of unpack expressions. It could be inferred from a programmer-provided permission kind, e. Therefore we introduce unpacked as an additional linear predicate.

The checking rules for packing and unpacking are given in FIG. Notice that packing and unpacking always affects permissions to this fr.

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We ignore substitution of this with an object location at runtime here. The judgment inv determines a predicate for the receiver's fields based on the permission being unpacked. It is used when checking the body expression. An unpacked predicate is added into the linear context. We can prevent multiple permissions from being unpacked at the same time using a straightforward dataflow analysis omitted here.

It derives the predicate necessary for packing the unpacked permission and then assumes that permission in checking the body expression. The new state assumption A can differ from before only if a modifying permission was unpacked. Invariant transformation.

The judgment inv c n, g, k, A determines what permissions to fields are implied by a permission access this fr n, g, k, A for a frame of class C. It is defined in FIG. Conversely, unpacking a pure permission yields completely purified permissions. Checking a method call involves proving that the method's pre-condition is satisfied. The call can then be typed with the method's post-condition. Unfortunately, calling a method can result into reentrant callbacks.

To ensure that objects are consistent when called we require them to be fully packed before method calls. This reflects that aliased objects always have to be prepared for reentrant callbacks. This rule is not a limitation because we can always pack to some intermediate state although it may be inconvenient in practice. Notice that such intermediate packing obviates the need for adoption while allowing focus [13]: the intermediate state represents the situation where an adopted object was taken out of the adopting object. Inferring intermediate states as well as identifying where reentrant calls are impossible intermediate packing avoidance are important areas for future research.

Virtual calls. In virtual calls, frame and object permissions are identical because object permissions simply refer to the object's virtual frame. This is achieved by substituting the given receiver for both this and this fr. Super calls. Recall that super is used to identify permissions to the super-frame.

We substitute super only for this fr. We omit a substitution of this for the receiver this again for clarity. Assignments to fields change the state of the receiver's current frame. We point out that assignments to a field do not change states of objects referenced by the field. Therefore reasoning about assignments mostly has to be concerned with preserving invariants of the receiver. The unpacked predicates introduced in section 5. Our intuition is that assignment to a field requires unpacking the surrounding object to the point where all states that refer to the assigned field in their invariants are revealed.

Notice that the object does not have to be unpacked completely in this scheme. For simplicity, each field is annotated with the subtree that can depend on it FIG. Thus we interpret subtrees as data groups [27]. This preserves information about that value. The rule verifies that the new object is of the correct type and that a suitable full or share permission is currently unpacked.

We use standard rules for the decidable multiplicative-additive fragment of linear logic MALL with quantifiers that only range over fractions [28]. Following Boyland [7] we introduce a notion of substitution into the logic that allows substituting a set of linear resources with an equivalent one. The judgment P. Our splitting and joining rules maintain a consistent set of permissions for each object so that no permission can ever violate an assumption another permission makes.

Fractions of all permissions to an object sum up to at most 1 for every node in the object's state space. To illustrate how verification proceeds, FIG. As can be seen, we need an intermediate state reads and a marker field reading that indicate an ongoing call to the underlying stream. We also need an additional state refinement to specify an internal method replacing the while loop in the original implementation. We assume that this fr permissions can be used for calls to private methods. Maybe surprisingly, we have to reassign field values after super.

The reason is that when calling super we lose temporary state information for this. Assignment re-establishes this information and lets us pack properly before calling doFill recursively or terminating in the cases of a full buffer or a depleted underlying stream. It turns out that these re-assignments are not just an inconvenience caused by our method but point to a real problem in the Java standard library implementation.

This call changes a field, which causes the buffer's invariant on count to permanently break, later on resulting in an undocumented array bounds exception when trying to read behind the end of the buffer array. Because fill operates on a share permission our verification approach forces taking into account possible field changes through reentrant calls with other share permissions. This is precisely what our malicious stream does.

We could avoid field re-assignments by having read require a full permission, thereby documenting that reentrant modifying calls are not permitted for this method.


In previous work we proposed more expressive typestate specifications [4] that can be verified with the approach presented in this paper. We also recently proposed full and pure permissions and applied our approach to specifying full Java iterators [3]. Verification of protocol compliance has been studied from many different angles including type systems, abstract interpretation, model checking, and verification of general program behavior.

Aliasing is a challenge for all of these approaches. The system that is perhaps closest to our work is Fugue [12], the first modular typestate verification system for object-oriented software. Methods are specified with a deterministic state transition of the receiver and pre-conditions on arguments. Our approach supports more expressive method specifications based on linear logic [18].

We extend several ideas from Fugue to work with access permissions including state invariants, packing, and frames. Fugue's specifications are expressible with our system [4]. There is no equivalent for state dimensions, temporary state assumptions, full, immutable, and pure permissions, or permissions for object parts in Fugue. Protocol specifications have been based on very different concepts including typestates [34, 11, 25], type qualifiers [16], size properties [9], direct constraints on ordering [23, 35], and type refinements [30, 10].

None of the above systems can verify implementations of object-oriented protocols like our approach and only two [35, 10] target object-oriented languages. Effective type refinements [30] employ linear logic reasoning but cannot reason about protocol implementations and do not support aliasing abstractions. Hob [25] verifies data structure implementations for a procedural language with static module instantiation based on typestate-like constraints using shape analyses.

In Hob, data can have states, but modules themselves cannot. In contrast, we can verify the implementation of stateful objects that are dynamically allocated and support aliasing with permissions instead of shape analysis. Similar to effective type refinements, state changes can be tracked for a pre-defined set of types, but reasoning about the implementation of these types is not supported. To our knowledge, none of the above systems supports temporary state information. Because programming with linear types [36] is very inconvenient, a variety of relaxing mechanisms were proposed.

Uniqueness, sharing, and immutability sometimes called read-only [7] have recently been put to use in resource usage analysis [23, 9]. Alias types [33] allow multiple variables to refer to the same object but require a linear token for object accesses that can be borrowed [7] during function calls. Focusing can be used for temporary state changes of shared objects [13, 16, 2]. Adoption prevents sharing from leaking through entire object graphs as in Fugue [12] and allows temporary sharing until a linear adopter is deallocated [13]. All these techniques need to be aware of all references to an object to change its state.

Access permissions allow state changes even if objects are aliased from unknown places. Moreover, access permissions give fine-grained access to individual data groups [27]. States and fractions [6] let us capture alias types, borrowing, adoption, and focus with a single mechanism. Sharing of individual data groups has been proposed before [7], but it has not been exploited for reasoning about object behavior.

In Boyland's work [6], a fractional permission means immutability instead of sharing in order to ensure noninterference of permissions. We use permissions to keep state assumptions consistent but track, split, and join permissions in the same way as Boyland. Global approaches are very flexible in handling aliasing. Approaches based on abstract interpretation e. Sound approaches rely on a global aliasing analysis [1, 14]. Likewise, most model checkers operate globally e. The Magic tool checks individual C functions but has to inline user-provided state machine abstractions for library code to accommodate aliasing [8].

The above analyses typically run on the complete code base once a system is fully implemented and are very expensive. Our approach supports developers by checking the code at hand like a typechecker. Thus the benefits of our approach differ significantly from global analyses. Recently, there has been progress in inferring typestate protocols in the presence of aliasing [31], which we believe could be fruitfully combined with our work to reduce initial annotation burden.

Finally, general approaches to specifying program behavior [26, 15, 2] can be used to reason about protocols. The JML [26] is very rich and complex in its specification features; it is more capable than our system to express object behavior not just protocols , but also potentially more difficult to use due to its complexity. Verifying JML specifications is undecidable in the general case. Spec is comparable in its complexity to the JML and imposes similar overhead.

The Boogie methodology allows sound verification of Spec specifications but requires programs to follow an ownership discipline [2]. Our system is much simpler than these approaches, focusing as it does on protocols, and it is designed to be decidable. While the treatment of aliasing in our system does involve complexity, it gives the programmer more flexibility than Boogie's method while remaining modular and sound. Because it is designed for protocol verification in particular, our system will generally impose smaller specification overhead than the JML or Spec.

A method for statically checking an object-oriented computer program module, comprising: identifying objects within a computer program module, at least one of said objects having a plurality of references thereto;. The method of claim 1 , wherein said imposing a discipline of permissions includes imposing permissions that permit multiple independent references to an object. The method of claim 1 wherein said imposing a discipline of permissions includes imposing a permission selected from the group comprising: a permission allowing a read-only reference to an object, where other references can read and write to the object;.

The method of claim 1 , wherein said determining is based on each of said objects assuming states that change perceptibly and non-monotonically within a guaranteed state space. The method of claim 4 wherein said imposing a discipline of permissions comprises imposing permissions that can be associated with a fraction of an object. The method of claim 1 wherein said determining is based on each of said objects having a state represented by a hierarchical state machine.

The method of claim 1 , wherein said determining is based on said objects having a superclass state and a subclass state, and wherein said superclass state and said subclass may be different. A method for statically checking an object-oriented computer program module, comprising: identifying objects within a computer program module;. The method of claim 8 wherein said imposing a discipline of permissions includes imposing a permission selected from the group comprising: a permission allowing a read-only reference to an object, where other references can read and write to the object;.

The method of claim 8 , wherein said determining is based on each of said objects assuming states that change perceptibly and non-monotonically within a guaranteed state space. The method of claim 8 , wherein said determining is based on each of said objects having a state represented by a hierarchical state machine. The method of claim 8 , wherein said determining is based on said objects having a superclass state and a subclass state, and wherein said superclass state and said subclass may be different.

Pong & Object Oriented Programming - Computerphile

The method of claim 13 wherein said imposing a discipline of permissions includes imposing at least one additional discipline selected from the group comprising: a permission allowing a single reference to an object; and. The method of claim 13 , wherein said determining is based on each of said objects assuming states that change perceptibly and non-monotonically within a guaranteed state space. The method of claim 14 , wherein said imposing a discipline of permissions comprises imposing permissions that can be associated with a fraction of an object.

The method of claim 13 , wherein said determining is based on each of said objects having a state represented by a hierarchical state machine. The method of claim 13 , wherein said determining is based on said objects having a superclass state and a subclass state, and wherein said superclass state and said subclass may be different. A method for statically checking an object-oriented computer program module, comprising: identifying objects within a computer program module, said objects having discrete states that change perceptibly and non-monotonically within a guaranteed state space;.

USP true USB2 en. System and method for efficient compilation and invocation of function type calls.