As per the previous research, it has been concluded that there exists various methodologies and some methodologies have some tools concerned with them which help to simulate the system and some have don’t. The methodologies with tools are more efficient to represent system and check formal behavior of agents. But some methodologies have tools only to design the system not express the behavior. So to check the working and communication between agents a tool named Petri net is used. To express behavior of agents more clearly every methodology needs to design a appropriate or a tool supporting for all methodologies must be designed. Thus there is a great need of a powerful tool to represent complex system implemented from agent oriented software engineering.
Secure Tropos  extends the agent oriented software engineering method- ology Tropos  by providing a set of security-related concepts and processes to allow developers to consider security issues throughout the development stages. Secure Tropos supports three development stages: the early requirements anal- ysis stage, in which the social issues related to the security of the system are identified and analysed; the late requirements analysis stage, in which the tech- nical issues related to the security of the system are identified and analysed; and the architectural design stage, in which the architectural style of the system is defined with respect to the system’s security requirements and the requirements are transformed into a design. However the latter could be a very difficult task, especially for a developer without knowledge of security, possibly resulting in the development of a non-secure system. For this reason, we propose to comple- ment secure Tropos with the use of security patterns. Security patterns capture existing proven experience about how to deal with security problems during the software development and they help to promote best design practices.
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Wooldridge, Jennings and Kinney present the Gaia methodology for agent-oriented analysis and design. Gaia is a general methodology that supports both the micro-level (agent structure) and macro-level (agent society and organization structure) of agent development, it is however no “silver bullet” approach since it requires that inter-agent relationships (organization) and agent abilities are static at run-time. The motivation behind Gaia is that existing methodologies fail to represent the autonomous and problem-solving nature of agents; they also fail to model agents’ ways of performing interactions and creating organizations. Using Gaia, software designers can systematically develop an implementation-ready design based on system requirements. The first step in the Gaia analysis process is to find the roles in the system, and the second is to model interactions between the roles found. Roles consist of four attributes: responsibilities, permissions, activities and protocols. Responsibilities are of two types: liveness properties - the role has to add something good to the system, and safety properties- prevent and disallow that something bad happens to the system. Permissions represents what the roles allowed to do, in particular, which information it is allowed to access. Activities are tasks that a role performs without interacting with other roles.
When the system goals have been identified, the next step of the development cycle involves the definition of the system’s global architecture in terms of subsystems (actors) interconnected through data and control flows (dependencies). To achieve this, Secure Tropos employs different processes during the architectural design stage, such as the Addition of new actors, in which new actors (and sub-actors) are added to make the system interact with the external actors, to take responsibility to fulfil one or more goals of the system and to contribute positively to the fulfilment of some non-functional requirements; the Capabilities identification, in which the capabilities needed by the actors to fulfil their goals and tasks are identified; and the Agents assignment, in which a set of agent types is defined assigning to each agent one or more different capabilities. The first step on the architectural design is the choice of the architectural style to be used for the system. For the eSAP system a client/server architectural style has been chosen , as opposed to a mobile agents style. Mainly, this decision took place because the client/server style contributes more to the security of the eSAP system than the mobile agents style .
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Item (3) has shown how a design metaphor can assist the production of agent models, however the eventual artefact produced can suffer from the in herent generic abstraction; a more specialised graph, that incorporates core agent concepts, could assist the process considerably. With reference to Chap ter 2, more explicit links to Belief-Desire-Intention (BDI) concepts (Georgeff et ah, 1999) would provide not only extra support when populating the con ceptual models, which is fundamental for realistic actor to agent mappings, but it would also make more agent-specific declarations in the ontology. As a result, agent-literate ontologies are more likely to be re-used and designers could take the ontology as a basis for new systems, knowing that the core BDI concepts are included.
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As already observed, traditional methodologies for analysis and design are poorly suited for multi-agent systems because of the fundamental mismatch between the respective levels of abstraction. Despite this mismatch, however, several proposals do take object-oriented modelling techniques or methodologies as their basis. On the one hand, some proposals directly extend the applicability of object-oriented methodologies and techniques to the design of agent systems. For example, some proposals attempts to directly apply the UML notation to represent agent systems and their patterns of interaction 22, 33]. However, these proposals fail to capture the autonomous and proactive behaviour of agents, as well as the richness of their interactions. On the other hand, some proposals seek to extend and adapt object-oriented models and techniques to dene a methodology for use in multi- agent systems. This can lead, for example, to extended models for representing agent behaviour and their interactions 5, 23, 30], as well as to agent-tuned extensions of UML 27, 30]. However, although these proposals can sometimes achieve a good modelling of the autonomous behaviour of agents and of their interactions, they lack the conceptual mechanisms for adequately dealing with organisations and agent societies.
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There have been several studies on agent’s intelligence, but we do not find much research on quality measures related to agent intelligence. A methodology for quantitative and qualitative evaluation for software agent’s intelligence was developed . A set of tests was done to analyse the behaviour of agent and its performance in different environments and situations. The paper outlined a methodology to test agent’s intelligence using the general intelligence factor ‘g’ and the theory of multiple intelligence in humans. It does not emphasise on the standard characteristic of agent. Simultaneously a set of measures were being developed, which considered product, process and resources to evaluate the performance of software agents. A project report was presented that depicted the result of adopting some product measurement from the procedural and object oriented paradigm to agent oriented software . This research confined to adapting object oriented software measures to evaluate the software agent. A research aiming at determining and evaluating software agent’s quality considering an agent’s characteristics like social ability , autonomy , pro-activity , and established the attributes associated with these characteristics and set out the measure enabling its global evaluation. A set of measures was proposed for evaluating the reactivity property considering its associated attributes at various levels . A set of measures of agent oriented software considering mobility characteristic which has been decomposed into three attributes .
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)] [Taromirad and Ramsin, (2008)] [Lu and DeClue, (2011)] [Likoebe and Maruping, (2009)]. One of the popular example in Agile based software development is Extreme Programming [Extreme Programming (2011)] [Erickson and Lyytinen et al. (2005)]. Due to growth of web technology the projects which are web based needs to be distributed on the global network. This brings in complexity in project development there is a need to fetch in intelligent and self – organized component, so that reusability can be increased and complexity can be reduced. Agent Oriented Software Engineering Approach is research area [Wooldridge (1997)] [Molesini1 and Andrea et al. (2009)] [Dzitac and Boldur et al. (2009)] [Scott and DeLoach, (2009)] [Sterling and Taverter, (2009)] [Abdelaziz and Elammari et al. (2008)] [Akbari and Faraahi , (2009)] An example of well known agent oriented software engineering approach is Tropos [Mouratidis and Haralambos, (2009)] [Ali and Dalpiaz , (2008)].
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The Theme/UML approach was based on the use of the Meta Object Facility (MOF) extension and the Eclipse CORE meta-model (ECORE) [Eclipse, 2010]. The MOF meta model for the development of context-aware mobile applications proposed by de Farias et al. [de Farias et al., 2007] was structured according to the core and service views of the software system. This approach provides a contextual model that is independent from the application domain. However, it does not provides high level abstraction of the software models, which express conceptual characteristics of the context-dependent behaviours. From a software developer’s perspective, it does not take into account architectural or deployment issues, because it is based on the service-oriented architectures. In addition, it has focused on the model-to-model transformation for generating the software composition. Such approach adds substantial overhead over the development for writing and configuring the MOF scripts. The Theme/UML methodology limits the development of self-adaptive applications to a very specific framework that supports the Aspect-oriented Java extension (AspectJ) and Eclipse Modelling Framework (EMF) [Kiczales et al., 2001]. Extending this paradigm for another platform requires a specific compiler that supports AOP and toolset that follow the EMF.
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The requirements for testing frameworks and class libraries are somewhat different than for applications. Classes used in a specific application need to work correctly in that application, whereas those in frameworks or libraries are intended to be reused and m ust work in yet unwritten applications. Of particular concern here is speciali sation inheritance, discussed in Section 3.4. A subclass that is a specialisation can be substituted for its parent provided the strengthened method preconditions are not vio lated. W hile a specific application may be able to guarantee this, it can be a potential source for errors in the use of a class library. In an ideal world, developers of class libraries and frameworks would provide their customers with test requirements for the correct use of their software (Marick 1992a), and this would include test requirements that make their specialised subclasses fail substitutability.
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Our hypothesis is motivated by our work in designing a tool to solve a specific bioinformatics problem: managing the heterogeneous formats of data so that it remains parsable into the future. In this paper, we propose the design of a data curation tool that trawls a bioinformatician’s provenance store for data in obsolete formats and converts that data to novel formats. The tool has a set of conversions, each stating an obsolete format to convert from and a novel format to convert to. We consider both a non-agent based solution and an agent based solution, and show that the properties of the latter are necessary for meeting the wider demands of the bioinformatics domain. Such demands come from the particular characteristics of the domain and two in particular. The first domain characteristic is the variation in expertise between novice researchers who cannot accurately determine which data formats may become obsolete and experts who wish to gain greater control over the management of their tools. The second characteristic is the desire to automate the many trivial manual stages of bioinformatics experiments, to give time for answering more valuable research questions. We demonstrate that an agent-oriented development method is well- suited to designing the tool, and that, because the requirements come from the domain rather than being particular to the tool, the approach applies more widely to other bioinformatics tools.
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Object-oriented Analysis and Design is a new way of approaching the solutions to problems related to the programming world. This concept is an evolutionary concept and offers a refreshing change from the obsolete programming concepts, such as modular programming (in modular programming, a program is divided into small units of code, called “modules”). In this new approach, models are organized around real world concepts. As we know that in the earlier programming concepts, the stress was upon solving the problem. The flaw in that approach was, no reusability of code was considered. All such flaws have been removed in the new approach – “Object-oriented Analysis and Design”.
5. Aspect Oriented Exception Handling Patterns Exception handling has been deployed as a key mechanism in implementing software fault tolerance through forward and backward error recovery mechanisms. It provides a convenient means of structuring software that has to deal with erroneous conditions . In , author addresses the weaknesses of exception handling mechanisms provided by mainstream programming languages like Java, Ada, C++, C#. In his experience exception handling code is inter-twined with the normal code. This hinders maintenance and reuse of both normal and exception handling code.
Adaptive programming, realized by the use of propagation patterns, extends the object- oriented paradigm by lifting programming to a higher level of abstraction. In their simplest form, which also turns out to be the worst in terms of adaptiveness, adaptive programs are nothing more than conventional object-oriented programs, where no traversal is used and where every class gets a method explicitly. But, for a large number of applications, repre- sented by related customizers, nothing has to be done to an adaptive program to select the conventional object-oriented program corresponding to any of the customizers. Moreover, when changes to an adaptive program are indeed necessary, they are considerably easier to incorporate given the ability that adaptive programs oer to specify only those elements that are essential and to specify them in a way that allows them to adapt to new environments. This means that the exibility of object-oriented programs can be signicantly improved by expressing them as adaptive programs, which specify them by minimizing their dependency on their class structures.
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This conception of a database accords well with the original motivation for centralising data, as set out in [KS91], for instance. The first databases were repositories of knowledge about data that simplified the task of writing special- purpose programs for data manipulation to such an extent that in many cases they could be directly specified as queries by a naive user. In a modern context, we would like to develop a database in such a way that we can readily construct an customised environment for interaction for any agent requiring access, making data observable and manipulable within this environment in the ways that are most appropriate to that agent's real-world view of the data. For instance, in a children's library, it might be appropriate to respond to a textual query by presenting a picture of a book, stating its title and presenting a map representation of the library in which the child could simulate locating the book on the shelves by interacting in a standard video-game style.
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The primary ontology for AOP is by van den Berg et al . This consists of fifteen ontology views, of which two are of particular interest in identifying ontology-enabled development from an AOSD perspective. These are the Software System View and the Weaving View, which between them encompass the high level view of the system and the core engineering perspective of managing aspects. In addition, Black and Harman  propose some extensions to this model, in particular the integration of spatial, lingual and social aspects. These three aspects can be defined as follows. Spatial- If only the system is viewed from spatial aspect, the user will be conscious that the system may be located in geographically dissimilar locations. Lingual- A system may be viewed as language independent if the concern that it is written in a particular language can be separated out. Social-This is related to the computer programmers. Separating out the social aspects of the programmers helps to understand the cognitive thinking of the programmers. These views and extensions have been integrated together to provide a single ontology of aspect oriented software development.
We compare the metric values of WMC, DIT, RFC, AMC, CBO, CAM, CA, CE, LCOM and LCOM3 for the projects B1, B2, D1, D2, E, F1 and F2 at B, X1, X2, X3 to the time it took for the developers to reach the next extension, scaled to B and scaled to B plus preceding extensions. The CKJM Extended tool measures the metric values. We use Python to, per metric, calculate the Pearsons and Spear- mans correlation coefficients of the data sets of the times and means. Literature research should determine if there are other ways to test the suitability of the software met- rics as indicators of software agility.
There are many issues remaining for future work. Perhaps most importantly, our methodology does not attempt to deal with truly open systems, in which agents may not share common goals. This class of systems represents arguably the most important applica- tion area for multi-agent systems, and it is therefore essential that our methodology should be able to deal with it. Another aspect of agent-based analysis and design that requires more work is the no- tion of an organisational structure. At the moment, such structures are only implicitly defined within our methodology — within the role and interaction models. However, direct, explicit representa- tions of such structures will be of value for some applications. For example, if agents are used to model large organisations, then these organisations will have an explicitly defined structure. Represent- ing such structures may be the only way of adequately capturing and understanding the organisation’s communication and control structures. More generally, the development of organisation design patterns might be useful for reusing successful multi-agent system structures (cf. ). Finally, we believe that a successful methodol- ogy is one that is not only of pragmatic value, but one that also has a well-defined, unambiguous formal semantics. While the typical developer need never even be aware of the existence of such a se- mantics, it is nevertheless essential to have a precise understanding of what the concepts and terms in a methodology mean .
By the improvement of the product business and the advances of the product building sciences, the utilization of Object-Oriented Software Engineering (OOSE) has expanded in the product complex world. The cause of the OOSE in assessment and outline of the product has extended much and is currently considered as one of the product mix forms. The OOSE is an arrangement of the Object Oriented Analysis (OOA) models, Object Oriented Design (OOD) and the Object Oriented Programming (OOP) which give a capable structure to the improvement of the product. The OOSE gives the likelihood of OOP on the improvement and generation of the product after the examination and planning the product. In the paper, we concentrate the OOSE models which are an advancing innovation in the programming industry.
At the time of writing, the development of any agent system — however trivial — is essentially a process of experimentation. There are no tried and trusted techniques available to assist the devel- oper. Unfortunately, because the process is experimental, it en- courages the developer to forget that they are actually developing software. Project plans tend to be pre-occupied with investigating agent architectures, developing cooperation protocols, and improv- ing coordination and coherence of multi-agent activity. Mundane software engineering processes — requirements analysis, specifi- cation, design, verification, and testing — become forgotten. The result of this neglect is a foregone conclusion: the project flounders, not because of agent-specific problems, but because basic software engineering good practice was ignored. The abandonment of the software process is often justified with reference to the fact that software engineering for agent systems is, as yet, a research area. While it is true that development techniques for agent systems are in their infancy, it is nevertheless also true that almost any prin- cipled software development technique is better than none. Thus in the absence of agent-oriented development techniques, object- oriented techniques may be used to great effect. They may not be ideal, but they are certainly better then nothing.