Designing multi-agent unit tests using systematic test design patterns-(extended version)

Khamis, Mohamed A.; Nagi, Khaled

doi:10.1016/j.engappai.2013.04.009

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…The answer, at the unit/agent level, depends on compilation and the execution model of those frameworks. For frameworks like Jade and JS-son [23], that use mainstream programming languages to define agents, these tools should be compatible out of the box with minor effort [24]. For cross-compilation-based frameworks like Astra [14] and ASC2 [27] it is only the matter of tooling (e.g.…”

Section: Discussion and Future Developmentsmentioning

confidence: 99%

“…This method of testing has however been criticized in [25] as being "too fine-grained", proposing instead to perform testing at a module level, that is, considering a set of goals, plans, and/or rules as a single unit. Still other works refer to software testing techniques applied on MAS development, focusing on testing agents and their interaction patterns as the main level of abstraction [10,24]. At implementation level, such unit testing is performed in a Jade multi-agent system via the JUnit library.…”

Section: Verification Of (Multi-)agent Systemsmentioning

confidence: 99%

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Seamless Integration and Testing for MAS Engineering

Parizi

Sileno

Engers

2022

Lecture Notes in Computer Science

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Testing undeniably plays a central role in the daily practice of software engineering, and this explains why better and more efficient libraries and services are continuously made available to developers and designers. Could the MAS developers community similarly benefit from utilizing state-of-the-art testing approaches? The paper investigates the possibility of bringing modern software testing tools as those used in mainstream software engineering into multi-agent systems engineering. Our contribution explores and illustrates, by means of a concrete example, the possible interactions between the agent-based programming framework ASC2 (AgentScript Cross-Compiler) and various testing approaches (unit/agent testing, integration/system testing, continuous integration) and elaborate on how the design choices of ASC2 enable these interactions.

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Section: Discussion and Future Developmentsmentioning

confidence: 99%

Section: Verification Of (Multi-)agent Systemsmentioning

confidence: 99%

Seamless Integration and Testing for MAS Engineering

Parizi

Sileno

Engers

2022

Lecture Notes in Computer Science

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“…The classifier was used to take the behavior that each of the agents identified in the late requirements diagram would have. The JADE platform supports the development of the MAS, which provides advantages such as [31]: simplifying the development of a MAS, guaranteeing compliance with FIPA standards; high cohesion and low coupling between the modules; simple liability; independent threads to simultaneously perform different functions; allows programmers to focus on the specific parts of your problem; and adaptive and decisionmaking capacity. The Implementation_JADE pattern [30] encapsulates the processes and functionalities that can be implemented with the JADE platform and implements and solves those functionalities that are essential so that developers can make use of this agent technology more easily.…”

Section: Activitymentioning

confidence: 99%

Goal-oriented Email Stream Classifier with A Multi-agent System Approach

Hojas-Mazo¹,

Espino²,

Martínez³

et al. 2021

IJACSA

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Now-a-days, email is often one of the most widely used means of communication despite the rise of other communication methods such as instant messaging or communication via social networks. The need to automate the email stream management increases for reasons such as multifolder categorization, and spam email classification. There are solutions based on email content, capable of contemplating elements such as the text subjective nature, adverse effects of concept drift, among others. This paper presents an email stream classifier with a goal-oriented approach to client and server environment. The i* language was the basis for designing the proposed email stream classifier. The email environment was represented with the early requirements model and the proposed classifier with the late requirements model. The classifier was implemented following a multi-agent system approach supported by JADE agent platform and Implementation_JADE pattern. The behavior of agents was taking from an existing classifier.The multi-agent classifier was evaluated using functional, efficacy and performance tests, which compared the existing classifier with the multi-agent approach. The results obtained were satisfactory in all the tests. The performance of multi-agent approach was better than the existing classifier due to the use of multi-threads.

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“…Similarly, the methodology of [12] is based on specific 'meta-models' and 'protocol descriptions'. Other methods focus on the interaction between agents specifically, often using 'mock agents' to check if specific interaction has taken place [6,18]. The concept of a 'mock agent', i.e., a specific agent that is used for testing, is also used in the work of [5] to test an agent's behaviour based on 'agent stories'.…”

Section: Related Workmentioning

confidence: 99%

Automating failure detection in cognitive agent programs

Koeman

Hindriks

Jonker

2018

IJAOSE

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Debugging is notoriously difficult and extremely time consuming but also essential for ensuring the reliability and quality of a software system. In order to reduce debugging effort and enable automated failure detection, we propose an automated testing framework for detecting failures in cognitive agent programs. Our approach is based on the assumption that modules within such programs are a natural unit for testing. We identify a minimal set of temporal operators that enable the specification of test conditions and show that the test language is sufficiently expressive for detecting all failures in an existing failure taxonomy. We also introduce an approach for specifying test templates that supports a programmer in writing tests. Furthermore, empirical analysis of agent programs allows us to evaluate whether our approach using test templates detects all failures.

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Designing multi-agent unit tests using systematic test design patterns-(extended version)

Cited by 7 publications

References 14 publications

Seamless Integration and Testing for MAS Engineering

Seamless Integration and Testing for MAS Engineering

Goal-oriented Email Stream Classifier with A Multi-agent System Approach

Automating failure detection in cognitive agent programs

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