Tools
GoaID
Goald is an effort to create a Goal-Driven Deployment Framework. In your long term vision we imagine a platform in which:
Developers
Contribute with components that are means of implementing user goals.
Users
Make requests to the computing environment with goals they want to achieve in that environment.
The computer environment
Deploy the known components that allow for goal achievement at that environment making the goals achievable. It also looks for new users goals, new components, and changes in the environment.
Goal-Oriented Dependability Analysis (GODA)
GODA is a framework where a Contextual-Runtime Goal Model (CRGM) model can be converted into PRISM and PARAM models. The framework extends the TAOM4E tool for TROPOS goal model with an Eclipse plugin implementation. If you want to contribute on GODA, you are more than welcome!
Responsible researcher(s): Genaina Nunes Rodrigues
Repository: https://github.com/lesunb/CRGMToPRISM
Contributors: Danilo Mendonça.
Research areas: Dependability, Requirements Engineering
Hephaestus: A Tool for Managing SPL Variabilities
A suite of tools that follows a crosscutting approach for the product engineering phase of software product line (SPL) development. Here we focus on some design decisions that led the development of Hephaestus, and also present how it could be used for generat- ing product specific use cases and build files of a well known case study: the Mobile Media product line.
Responsible researcher(s): Rodrigo Bonifacio
Contributors: Rodrigo Bonifacio, Leopoldo Teixeira, Paulo Borba.
Research areas: Software Product Line
Heterogeneous Multi-Robots Mission Control
Heterogeneous Multi-Robots Mission Control is an architecture for the development of applications, capable of coordinating multi-robot missions subject to uncertainty in properties of the available robots in the Software Engineering Lab (LES) at University of Brasilia.
Keywords: Software architecture, cooperative heterogeneous robots, multi-robots systems, Cyber-physical systems
License
The source code is released under a MIT license.
Authors: Gabriel Rodrigues, Vicente Moraes and Gabriel F P Araujo
Affiliation: LES
Maintainers: Gabriel Rodrigues, Vicente Moraes,Gabriel F P Araujo
UnB-DALi - UnB Dependability Analysis Library
This project aim at providing the infrastructure and functionality needed by our dependability analysis on performing model transformation routines. In software engineering terms, this kind of project is often called a library, since its target is not the end-user, but the developer himself. Hence, the name: UnB Dependability Analysis Library (UnB-DALi, for short). If you want to contribute on UnB-DALi, you are more than welcome!
Responsible researcher(s): Genaina Nunes Rodrigues
Repository: https://github.com/lesunb/UnB-DALi
Contributors: Abilio Calegário de Oliveira.
Research areas: Dependability, Requirements Engineering
MutRoSe-Mission-Decomposer
This is the mission decomposer for the MutRoSe (Multi-Robot systems mission Specification and Decomposition) framework. This decomposer works given: (i) a JSON Goal Model (generated in GODA), (ii) a modified HDDL specification (the original language syntax can be found in [1]), which consists of a subset of the language with the addition of new constructs, (iii) a JSON/XML configuration file and (iv) an XML world knowledge file.
ReAna - Reliability Analysis of Software Product Lines
Responsible researcher(s): Vander Ramos Alves, Genaina Nunes Rodrigues
Repository: https://github.com/SPLMC/reana
Contributors: André Lanna, Thiago Mael Castro, Sven Apel, Pierre-Yves Schobbens.
Research areas: Dependability, Software Product Line
ReAna-SPL Evaluator
Evaluator script designed to repeatedly run ReAna-SPL's analysis strategies and gather statistics. Use ./evaluator.py --help for options. The tools needed to run the tests (ReAna-SPL and PARAM) need to be placed under tools directory. Likewise, the behavioral models for the subject SPLs need to be placed under models. Configurations such as executable path and its command-line arguments may be manually changed in the configurations.py module. The pairs of SPL and strategy to be tested are also defined there.
Responsible researcher(s): Vander Ramos Alve, Genaina Nunes Rodrigues
Repository: https://github.com/SPLMC/reana-evaluator
Contributors: André Lanna, Thiago Mael Castro.
Research areas:Dependability, Software Product Line
RE4AIEthicalGuide: Guide for Artificial Intelligence Ethical Requirements Elicitation
This guide assists the elicitation of Ethical Requirements in AI-based systems by software development teams, with a focus on agile teams, where Product Owners and developers use a set of cards to answer questions related to ethical principles in AI at each sprint, creating requirements in the form of user stories and including them in Sprint backlogs.
Link to tool: RE4AIEthicalGuide
Responsible researcher(s): José Antonio Siqueira de Cerqueira e Edna Dias Canedo
Repository: https://github.com/josesiqueira/RE4AIEthicalGuide
Research areas: Requirements Engineering
Systematic Review (SR) is a technique used to search for evidence in scientific literature that is conducted in a formal manner, applying well-defined steps, according to a previously elaborated protocol. As the SR has many steps and activities, its execution is laborious and repetitive. Therefore, the support of a computational tool is essential to improve the quality of its application. Therefore, a tool called StArt (State of the Art through Systematic Review) was developed, which aims to help the researcher, giving support to the application of this technique. The StArt tool has being used by graduate students who have declared its positive support and its advantages in relation to other tools.
The StArt tool is being redesigned for the web. Its previous desktop version can be found here:
https://www.lapes.ufscar.br/resources/tools-1/start-1
Self-Adaptive Body Sensor Network (SA-BSN)
The Self-Adaptive Body Sensor Network (SA-BSN) features an exempalr of self-adaptive system designed for experimentation on solutions for adaptation in the domain of Self-Adaptive Software Systems. Body Sensor Networks (BSNs) are networks of wearable and implantable sensors that collect physiological data (e.g., heart beat rate, blood oxigenation) from the human body. These networks are often considered safety-critical, as they enable real-time monitoring of vital signs and other health-related parameters. In addition, they interface a body of knowledge of ever evolving diseases and health conditions with a the vastness of human individuality. No solution to indentification of health conditions is comprehensive enough to tackle the current nor future diseases that may pose a threat to human condition. The self-adaptive body sensor network paves the way to such ambitious goal.
The SA-BSN provides a platform for researchers and developers to explore and evaluate adaptive solutions in the Self-Adaptive Software Systems domain.
PistarGODA MDP
This artifact extends GODA framework into supporting the goal modeling of SAS under multiple classes of uncertainty (named uncertainty related to the system itself, to system goals, and the environment). From the goal model, the framework automatically generates: (1) reliability and cost parametric formulas parameterized with uncertainty; and (2) a Markov Decision Process (MDP) of the system alongside PCTL properties. The formulas express the modeled system's overall reliability and cost. They are used for runtime verification and to guide the sysnthesis of adaptation policies in SAS (see article). The MDP and PCTL files are used for probabilistic model checking (in which we refer to the PRISM tool). The source code extends the piStar tool and provides a modeling and analysing environment in the web for GODA. The pistarGODA modeling and analyzing environment is available online at Heroku.