Installation and Usage. The Xxxxx Daemon Wrapper plugin can be installed in Eclipse using the xxxx://xxx. xxxxxxxxxxxx.xxx/xxxxxxXxxxXxxxxXxxxxxXxxxxxx update site. Eclipse will install all the required plugins, including the Xxxxx Development Tools. Before actually using the plugin, it is necessary to configure the Xxxxx Development Tools by setting the path of the Xxxxx binaries in the preferences dialog. Once installed and configured, the plugin can be tested by opening the SDE perspective. The Xxxxx Daemon Wrapper facilitates the interaction of Xxxxx with other tools reg- istered with the SDE by exposing those features via the function executeMaudeCommand (command,commandType,resultType), which takes care of the initialization tasks, executes the Xxxxx command command, and returns the part of the Xxxxx output as specified by resultType. Figure 3 (left) exemplifies a Xxxxx command defining the algebra of Natural numbers, followed by a command to compute the sum 2 + 1. The command type is either core or full, specifying, re- spectively, if we are executing a core Xxxxx or a full Xxxxx command. The result type parameter is used to filter the Xxxxx output, discarding eventual unnecessary information (such as the number of rewrites or the time spent to execute the command). As output, the tool offers a Java string containing the output generated by Xxxxx, filtered accord- ing to the result type given as the invocation parameter. Figure 3 (right) shows the whole Xxxxx output obtained executing the command in Figure 3 (left). A detailed description of Xxxxx and its commands is available in the Xxxxx manual at http: //xxxxx.xx.xxxx.xxx/xxxxx0-xxxxxx.
Installation and Usage. To install ARGoS, it is necessary to download a pre-compiled package from xxxx://xxxxxx. xxx.xx.xx/xxxxx/xxxxxxxx.xxx. Currently, packages are available for Ubuntu/KUbuntu (32 and 64 bits), OpenSuse (32 and 64 bits), Slackware (32 bits) and MacOSX (10.6 Snow Leopard). A generic tar.bz2 package is available for untested Linux distributions. Once downloaded, the pre- compiled package should be installed using the standard package installation tools. To use ARGoS, one must run the command argos3. This command expects two kinds of input: an XML configuration file and user code compiled into a library. The XML configuration file contains all the information required to set up the arena, the robots, the physics engines, the controllers, and so on. The user code includes the robot controllers and, optionally, hook functions to be executed in various parts of ARGoS to interact with the running experiment. For more information, documentation and examples, refer to the ARGoS website at http:// xxxxxx.xxx.xx.xx/xxxxx.
Installation and Usage. (a) Permitted usage encompasses the customer’s installation of the licensed software, loading into system memory and license-compliant usage defined by the user documentation and for the therein-described purposes.
Installation and Usage. 1. The Lessee shall, at its risk and costs, install the Property in Toshiba Yokkaichi Plant based on the installation standards or the method stipulated by the Property Manufacturer and the regulatory authorities, and shall not change such manufacturing facility for installation without the prior consent of the Lessors. In the event the Property or any Unit Component is installed outside Japan, such installment shall be subject to, in addition to the prior consent of the Lessors, the conditions that each provision hereof shall be fully satisfied with respect to the Property or such Unit Component in such location outside Japan, that the right of the Borrower and the Lender relating to the Property and their rights under the Relating Agreement shall not be affected, and that the Lessee shall comply with the relevant laws concerning the export and re-export control in Japan and the United States as an exporter.
Installation and Usage. The FACPL language has a dedicated web site at [PTMM13], which provides full information on the installation process and on the usage of the supporting software tools. In short, the plugin can be installed within Eclipse by adding the update site xxxx://xxx.xxx.xxxxx.xx/facpl/ eclipse/plugin. The installation wizard adds automatically the Xtext framework dependencies and the FACPL evaluation library needed for requests evaluation. The binaries and source code of the library can be also manually downloaded from the FACPL web site. Detailed installation and usage instructions can be found in the FACPL user guide [MMPT13b]. By means of simple examples, the guide introduces policies and requests syntax and explains how the request evaluation process is performed. The guide also illustrates the design principles at the basis of the implementation of the evaluation library, and the supporting features provided by the IDE.
Installation and Usage. Prerequisites The source code of GMC is available from [gmca]. During the installation, it is necessary to compile the extended GCC and GMC itself. A detailed step-by-step description of the installation and prerequisites can be found in the INSTALL file, which is provided in the source code distribution. The integrated model checker tests provide the basic usage examples. →
Installation and Usage. The latest version of the SPL framework can be obtained from xxxx://xxxxxx.xxx/ vhotspur/spl-java. The source code is distributed with Apache Ant build.xml, which al- lows building the entire package and running unit tests. The framework provides a JVM agent, which can can evaluate an SPL formula with modular data sources [BBH+12]. The framework can be used in two modes. In one, SPL acts as an external mechanism controlling the application adaptation. In the other, adaptation rules are contained in the business logic of the application. When SPL is used as an external mechanism, the source code of the application does not need to be modified. As a matter of fact, source code is not needed at all and even the bytecode is modified at run-time only. However, the application itself must expose interfaces for run-time configuration changes. When SPL is incorporated into the application itself, the rules for adaptation are part of the busi- ness logic. This can provide fine-grained performance tuning, however, source code modification are necessary. This is illustrated in the example below. An SPL demonstration example is provided together with the source code. The example shows a monitoring application that adjusts the output quality to reflect load – it draws a graph that normally contains a data point for each hour, however, under high system load only a data point for each day is used – the output is still useful but processing time is reduced. See Figure 19 for an example. Figure 19: Graphs of different quality provided for different monitoring application load. The demo is available in the src/demo-java folder, in the imagequality package, and can be started through the run-demo-imagequality Ant target of the framework build file. The demo uses the HTTP server provided by JVM to respond to requests on port 8888. We used the Pylot performance tool5 to roughly evaluate the advantage of the performance adapta- tion – with no adaptation, the demo could handle 33 requests per second and 95 % of requests finished in 3 seconds, whereas with adaptation, the demo handled 44 requests per second and 95% of all re- quests were finished in 2 seconds. The code itself is intentionally simple, serving to illustrate the benefits of adding an external SPL adaptation to an application. 5xxxx://xxx.xxxxx.xxx
Installation and Usage. The Xxxxx Daemon Wrapper plugin can be installed in Eclipse using the xxxx://xxx. xxxxxxxxxxxx.xxx/xxxxxxXxxxXxxxxXxxxxxXxxxxxx update site. Eclipse will install all the required plugins, including the Xxxxx Development Tools. Before actually using the plugin, it is necessary to configure the Xxxxx Development Tools by setting the path of the Xxxxx binaries in the preferences dialog. Once installed and configured, the plugin can be tested by opening the SDE perspective. The input of the Xxxxx Xxxxxx Wrapper consists of three Java strings: a Xxxxx command and the command and result types. A Xxxxx command typically contains a sequence of Xxxxx modules Figure 3: A Xxxxx command (left) and its evaluation (right). (a Xxxxx specification) and the actual command to be executed (for example reduce t, rewrite t, search t, with t being a Xxxxx term). Figure 3 (left) exemplifies a Xxxxx command defining the algebra of Natural numbers, followed by a command to compute the sum 2 + 1. The command type is either core or full, specifying, respectively, if we are executing a core Xxxxx or a full Xxxxx command. Finally, the result type parameter is used to filter the Xxxxx output, discarding eventual unnecessary information (such as the number of rewrites or the time spent to execute the command). As output, the tool offers a Java string containing the output generated by Xxxxx, filtered accord- ing to the result type given as the invocation parameter. Figure 3 (right) shows the whole Xxxxx output obtained executing the command in Figure 3 (left).
Installation and Usage. MESSI can be downloaded from its website [ML], where the usage description is also provided. An example of the analysis activities that can be performed with XXXXX is provided in the deliverable JD3.1. Additionally, the deliverable JD3.2 also discusses use of MESSI for the robotics case study. The inputs of MESSI are the initial configuration and the self-assembly strategy, provided as Xxxxx modules. The former provides information about the environment (an arena), specifying the presence of obstacles and targets (e.g. particular sources of light), and about the numbers and positions of the robots. The latter specifies the behaviour of the robots in the form of a finite state machine, which will be independently executed by each robot. Figures 4 and 5 provide a pictorial view of the two inputs. Figure 4 depicts an initial configuration with 9 robots distributed in an arena. The robots have to reach the target (the orange circle) situated behind a hole too large to be crossed by any single robot. Figure 5 depicts the basic self-assembly response strategy (BSRS) proposed in [OGCD10]. The strategy specifies the possible states (each circle is a bird-eye view of a robot) of the robots (i.e. the different mode of operation that the robots have) and the status of the robots LED signals (used to communicate with other robots) in each state. The transitions among the states provide the conditions that trigger a change of state of a robot, i.e., an adaptation. XXXXX provides a library of predefined basic behaviours (e.g. move towards light, or search a given color emission and grab its source), thus a self-assembly strategy is specified by just providing the list of states, the correspondence between the states and the basic behaviours, the status of the LED signals in each state, and a conditional rewrite rule for each transition of the finite state machine, with the condition as the label of the transition. Given an initial configuration and a self-assembly strategy, XXXXX allows to generate probabilistic simulations. As discussed, such simulations can be used to debug the strategy, or to measure its performance via statistical quantitative analysis.
Installation and Usage. The following instructions concern using the jDEECo runtime framework through the SDE plugin. Instructions for using the jDEECo runtime framework through the Java API are available on the project website at xxxxx://xxxxxx.xxx/d3scomp/jdeeco/wiki. To use jDEECo from SDE, download both the jDEECo SDE plugin and the jDEECo runtime framework jar files from the project website at xxxxx://xxxxxx.xxx/d3scomp/jdeeco and place them in the plugins folder of the SDE installation. After starting the SDE with the jDEECo plugin installed, the jDEECo runtime manager tool entry will be shown in the tool browser window. The functions of the tool can be accessed either via the tool description window or via the SDE shell. The main functions include start() and stop() to start and stop the jDEECo runtime framework and execution of the registered components and ensembles. The listAllComponents(), listAllEnsembles() and listAllKnowledge() functions facilitate introspection of the executing components and ensembles. The full list of functions is available in the SDE shell.
