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SpecificationGrammar
docker
spec
test
LICENSE.txt
README.md
__init__.py
check_features_module.py
hyvar-rec.ol
hyvar-rec.py
validate_module.py

README.md

HyVarRec

HyVarRec is a tool that allows to reconfigure an existing configuration for a given SPL when it is subject to contextual changes.

Given an existing configuration C with its features and attributes, HyVarRec returns the best configuration that maximises the user preferences and is the most similar to the initial configuration C.

HyVarRec uses the SMT solver Z3 to solve the optimization problems involved in the reconfiguration.


Requirement to install HyVarRec from sources:

Docker Installation & Use as a Service

HyVarRec could be installed using docker container technology (https://www.docker.com/) available for the majority of the operating systems. It can therefore be used simply sending a post request to the server deployed by using docker.

The file to build the docker images is contained in the docker folder. In the following we will give the instructions to deploy HyVarRec locally via docker assuming the use of a Linux machine. Similar task can be performed on other operating systems and we invite the interested user to consult the docker manual to find out how to perform the same task on his/her operating system.

The image of HyVarRec is available on Docker Hub. To run it please execute the following commands.

sudo docker pull jacopomauro/hyvar-rec
sudo docker run -d -p <PORT>:9001 --name hyvarrec_container jacopomauro/hyvar-rec

where <PORT> is the port used to use the functionalities of the service.

Assuming <JSON> is the json input file (please see below for more details about the input format), to obtain the desired configuration it is possible to perform the following post request.

curl -H "Content-Type: application/json" -X POST -d @<JSON> http://localhost:<PORT>/process

To check if the service is responding it is possible to use the following post request.

curl -X POST -d '{}' http://localhost:<PORT>/health

To clean up please lunch the following commands:

sudo docker stop hyvarrec_container
sudo docker rm hyvarrec_container
sudo docker rmi jacopomauro/hyvar-rec

For more information, please see the Docker documentation at docs.docker.com Examples of input files for HyVarRec are available in the test directory.

Input Specification

HyVarRec requires a unique JSON file in input that formalizes the FM, the initial configuration, the contextual information, and the user preferences. All these information are encoded into a JSON object following the JSON schema defined in spec/hyvar_input_schema.json.

The output is a JSON object following the schema defined in spec/hyvar_output_schema.json.

Validate and Explain Modalities

HyVarRec can also be used to check if a given FM is non void for all the possible context. This can be done by running the following POST request.

curl -H "Content-Type: application/json" -X POST -d @<JSON> http://localhost:<PORT>/validate

where <JSON> is the json input file as specified in the input format. In this case, the information related to the initial configuration are discarded.

The answer is a JSON object having the schema defined in spec/hyvar_output_validate.json. Basically, in the field "result" it will report the result of the analysis (either "valid" or "not_valid"). If the FM is void for certain context then the output will also provide the list of one context assignment that makes the model void.

When a model is void HyVarRec can be used to check the set of constraints that makes the model void. This can be done by running the following POST request.

curl -H "Content-Type: application/json" -X POST -d @<JSON> http://localhost:<PORT>/explain

where <JSON> is the json input file as specified in the input format. In this case it is important to define into the initial configuration the values of the context that makes the FM void.

The answer is a JSON object having the schema defined in spec/hyvar_output_explain.json. Basically, in the field "result" it will report if the FM is void or not (either "sat" or "unsat"). If the FM is void with the keyword "constraints" the list of the constraint responsible for the voidness of the FM is returned. Note that it is possible to select the option --constraints-minimization to get the minimal (not minimum) explanation.

Check Features Modality

HyVarRec can be used to provide the list of the dead and false optional features. Dead features are optional features that can not be selected. Mandatory features instead are optional features that must be selected. The check can be done by running the following POST request.

curl -H "Content-Type: application/json" -X POST -d @<JSON> http://localhost:<PORT>/check_features

where <JSON> is the json input file as specified in the input format. In this case, the information related to the initial configuration are discarded.

Note that that the only features that are checked are those declared as optional. This can be done by using the optional field "optional_features" in the input specification. In case evolution is considered (i.e., a context is used to express the time) then it is possible to define the exact time points where the feature are optional. In this case, the check is performed for these time point only.

The answer is a JSON object having the schema defined in spec/hyvar_output_check_features.json.

MSPL: Interface Check

HyVarRec allows to validate if a given I SPL is an interface of another SPL S. Being an interface means that every configuration of I can be extended to form a valid configuration of S.

This can be done by running the following POST request.

curl -H "Content-Type: application/json" -X POST -d @<JSON> http://localhost:<PORT>/check_interface

where <JSON> is a JSON file defining both the software product lines. In particular, assuming { I } is the JSON object defining the FM of I and { S } the feature model defining the FM of S according to the json schema in spec/hyvar_input_schema.json, the JSON input to submit to HyVarRec is the following one.

{ "interface" : { I }, "spl" : { S } }

The output obtained is a JSON object having the JSON schema spec/hyvar_output_validate.json. In particular, when the interface is not a valid interface HyVarRec returns the context, features, and attributes that can not be extended in the SPL S.

Features as Booleans

It is possible to use HyVarRec in explain and reconfiguring modality by entering features directly as booleans by using the option --features-as-boolean. In this case the feature name needs to start with a letter.

For example: the constraint 'feature[f111] = 1' can be encoded as 'f111'

To activate the --features-as-boolean option using the HTTP interface the JSON input should be extended with the following property when used in reconfiguration modality.

"hyvar_options" : ["--features-as-boolean"]

Direct encoding into SMT formulas

For performances reason it is possible to enter the formulas directly into SMT format.

For example the constraint 'feature[f111] = 1' can be encoded as follows.

"smt_constraints" : {
		"formulas": ["(declare-fun f111 () Int) (assert  (= f111 1))"],
    "features": ["_id0"]
		}

The keyword "features" is used to add all the feature introduced by the constraints.

If the --features-as-boolean option is activated then the constraint can be enter as follows.

"smt_constraints" : {
		"formulas": ["(declare-fun f111 () Bool) (assert  (= f111))"],
    "features": []
		}

Note that in this case it is not needed to specify the list of the features introduced.

Other options

HyVarRec allow the possibility to set different options. Among all the option available we would like to underline the following ones:

  • --num-of-process INTEGER It is used to speed up the parsing of the constraints (not the execution of the solver). It can be useful for large instances
  • --validate-modality [grid|forall], default: forall. When the tool is used for the validation, by default HyVarRec will use a universal quantifier formula to perform the task. If the modality is instead grid it will perform an interactive search, one context at the time
  • --check-features-modality [grid|forall|pruning], default: forall. When the tool is used for the checking of features anomalies, by default HyVarRec will use a universal quantifier formula to perform the task. If the modality is instead grid it will perform an interactive search, one context at the time. In pruning modality the tool will try to prune the features to check by repetive calls to the solver
  • --timeout INTEGER. Timeout in milliseconds for the solver (0 = no-timeout). Valid only when used in reconfiguration mode.
  • --constraints-minimization. Tries to produce a minimal explanation when used in explain mode
  • --no-default-preferences. Does not consider default preferences to minimize the difference w.r.t. the initial configuration. Option significant only in reconfiguration mode.
  • --non-incremental-solver. Do not use an incremental solver. Option significant when checking the features and in validation mode

Limitations & Notes

Operator have left associativity: e.g., x + x * y is interpreted as (x + x) * y