iStarJSON : a lightweight data-format for i* models

JSON is one of the most widely used data-interchange format. There is a large number of tools open for modelling with i*. However, none of them provides supporting for JSON. In this paper we propose iStarJSON language, a JSON-based proposal for interchanging i* models. We also, present an open source software that transforms XML-based format models to JSON models that expose a set of web services for mining iStarJSON models.Peer ReviewedPostprint (author's final draft

Open source software ecosystems : a systematic mapping

Context: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. OSS influences the way organizations develop, acquire, use and commercialize software. SECOs have emerged as a paradigm to understand dynamics and heterogeneity in collaborative software development. For this reason, SECOs appear as a valid instrument to analyze OSS systems. However, there are few studies that blend both topics together. Objective: The purpose of this study is to evaluate the current state of the art in OSS ecosystems (OSSECOs) research, specifically: (a) what the most relevant definitions related to OSSECOs are; (b) what the particularities of this type of SECO are; and (c) how the knowledge about OSSECO is represented. Method: We conducted a systematic mapping following recommended practices. We applied automatic and manual searches on different sources and used a rigorous method to elicit the keywords from the research questions and selection criteria to retrieve the final papers. As a result, 82 papers were selected and evaluated. Threats to validity were identified and mitigated whenever possible. Results: The analysis allowed us to answer the research questions. Most notably, we did the following: (a) identified 64 terms related to the OSSECO and arranged them into a taxonomy; (b) built a genealogical tree to understand the genesis of the OSSECO term from related definitions; (c) analyzed the available definitions of SECO in the context of OSS; and (d) classified the existing modelling and analysis techniques of OSSECOs. Conclusion: As a summary of the systematic mapping, we conclude that existing research on several topics related to OSSECOs is still scarce (e.g., modelling and analysis techniques, quality models, standard definitions, etc.). This situation calls for further investigation efforts on how organizations and OSS communities actually understand OSSECOs.Peer ReviewedPostprint (author's final draft

Protocol for a SLR on software ecosystems: technical report

Open Source Software (OSS) and Ecosystems (SECO) are two emergent research areas in software engineering. We are interested on the published works that join these two topics, to do it we used a well-known technique called Systematic Literature Review (SLR).Preprin

Assessing open source communities' health using Service Oriented Computing concepts

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The quality of Open Source Software products is directly related to its community's health. To date, health analysis is made accessing available data repositories or using software management tools that are often too static or ad hoc. To address this issue, we propose to adopt principles and methods from the Service Oriented Computing field. Particularly, we propose to adapt the concepts of quality service and service level agreement, and propose to reuse the existing body of knowledge and techniques from SOC monitoring. To demonstrate the feasibility of the approach, we use a service monitoring framework called SALMonOSS as a proof of concept to realize the implementation of the proposal.Peer ReviewedPostprint (author's final draft

QuESo V2.0 a quality model for open source software ecosystems: List of measures

This technical report is part of QuESo-V2.0 a quality model for open source software ecosystems (OSSECOs). Our prior efforts have focused on providing a detailed list of the quality measures found during the execution of a systematic mapping on OSSECOs. In this new version of the model, we addressing some of the issues that were highlighted in the QuESo V1.0 such as: the unbalanced distribution of measures and the ambiguity of some measures names. The measures listed in this report are not intended to be an exhaustive and complete set. However, this list provides a representative collection of OSSECOs measures. It is a small step in the direction of developing a platform for support the analysis of OSSECO.Postprint (published version

The RISCOSS platform for risk management in open source software adoption

Managing risks related to OSS adoption is a must for organizations that need to smoothly integrate OSS-related practices in their development processes. Adequate tool support may pave the road to effective risk management and ensure the sustainability of such activity. In this paper, we present the RISCOSS platform for managing risks in OSS adoption. RISCOSS builds upon a highly configurable data model that allows customization to several types of scopes. It implements two different working modes: exploration, where the impact of decisions may be assessed before making them; and continuous assessment, where risk variables (and their possible consequences on business goals) are continuously monitored and reported to decision-makers. The blackboard-oriented architecture of the platform defines several interfaces for the identified techniques, allowing new techniques to be plugged in.Peer ReviewedPostprint (author’s final draft

Towards assessing open source communities' health using SOC concepts

Quality of an open source software ecosystem (OSS ecosystem) is key for different ecosystem actors such as contributors or adopters. In fact, the consideration of several quality aspects(e.g., activeness, visibility, interrelatedness, etc.) as a whole may provide a measure of the healthiness of OSS ecosystems. The more health a OSS ecosystem is, the more and better contributors and adopters it will gather. Some research tools have been developed to gather specific quality information from open source community data sources. However, there exist no frameworks available that can be used to evaluate their quality as a whole in order to obtain the health of an OSS ecosystem. To assess the health of these ecosystems, we propose to adopt robust principles and methods from the Service Oriented Computing field.Peer ReviewedPostprint (author's final draft

Open source software ecosystems : towards a modelling framework

Open source software ecosystem modelling has emerged as an important research area in software engineering. Several models have been proposed to identify and analyse the complex relationships in OSS-ecosystems. However, there is a lack of formal models, methodologies, tool support, and standard notations for OSS-ecosystems. In this paper we propose a general framework for support the OSS-ecosystems modelling process. This framework will allow the representation, synthesis, analysis, evaluation, and evolution of OSS-ecosystems. Design science methodology is proposed to create several artefacts and investigating the suitability of these artefacts in the OSS-ecosystem context.Peer Reviewe

Measuring the quality of open source software ecosystems using QuESo

Peer ReviewedPostprint (author's final draft

Open source software ecosystems : a systematic mapping

Context: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. OSS influences the way organizations develop, acquire, use and commercialize software. SECOs have emerged as a paradigm to understand dynamics and heterogeneity in collaborative software development. For this reason, SECOs appear as a valid instrument to analyze OSS systems. However, there are few studies that blend both topics together. Objective: The purpose of this study is to evaluate the current state of the art in OSS ecosystems (OSSECOs) research, specifically: (a) what the most relevant definitions related to OSSECOs are; (b) what the particularities of this type of SECO are; and (c) how the knowledge about OSSECO is represented. Method: We conducted a systematic mapping following recommended practices. We applied automatic and manual searches on different sources and used a rigorous method to elicit the keywords from the research questions and selection criteria to retrieve the final papers. As a result, 82 papers were selected and evaluated. Threats to validity were identified and mitigated whenever possible. Results: The analysis allowed us to answer the research questions. Most notably, we did the following: (a) identified 64 terms related to the OSSECO and arranged them into a taxonomy; (b) built a genealogical tree to understand the genesis of the OSSECO term from related definitions; (c) analyzed the available definitions of SECO in the context of OSS; and (d) classified the existing modelling and analysis techniques of OSSECOs. Conclusion: As a summary of the systematic mapping, we conclude that existing research on several topics related to OSSECOs is still scarce (e.g., modelling and analysis techniques, quality models, standard definitions, etc.). This situation calls for further investigation efforts on how organizations and OSS communities actually understand OSSECOs.Peer Reviewe