1,430 research outputs found

    Bug Fix Time Optimization Using Matrix Factorization and Iterative Gale-Shaply Algorithms

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    Bug triage is an essential task in software maintenance phase. It assigns developers (fixers) to bug reports to fix them. This process is performed manually by a triager, who analyzes developers profiles and submitted bug reports to make suitable assignments. Bug triaging process is time consuming thus automating this process is essential to improve the quality of software. Previous work addressed triaging problem either as an information retrieval or classification problem. This paper tackles this problem as a resource allocation problem, that aims at the best assignments of developers to bug reports, that reduces the total fixing time of the newly submitted bug reports, in addition to the even distribution of bug reports over developers. In this paper, a combination of matrix factorization and Gale Shapely algorithm, supported by the differential evolution is firstly introduced to optimize the total fix time and normalize developers work load. Matrix factorization is used to establish a recommendation system for Gale-Shapley to make assignment decisions. Differential evolution provides the best set of weights to build developers score profiles. The proposed approach is assessed over three repositories, Linux, Apache and Eclipse. Experimental results show that the proposed approach reduces the bug fixing time, in comparison to the manual triage, by 80.67%, 23.61% and 60.22% over Linux, Eclipse and Apache respectively. Moreover, the workload for the developers is uniform.Comment: 14 page, 7 figures, 8 tables, 10 equation

    A Quality Model for Actionable Analytics in Rapid Software Development

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    Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by IEEE in the 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018. The final authenticated version will be available onlin

    Open source software ecosystems quality analysis from data sources

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    Background: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. The adoption of OSS by firms, governments, researchers and practitioners has been increasing rapidly in the last decades, and in consequence, they find themselves in a new kind of ecosystem composed by software communities,foundations, developers and partners, namely Open Source Software Ecosystem (OSSECO). In order to perform a systematic quality evaluation of a SECO, it is necessary to define certain types of concrete elements. This means that measures and evaluations should be described (e.g., through thresholds or expert judgment). The quality evaluation of an OSSECO may serve several purposes, for example: adopters of the products of the OSSECO may want to know about the liveliness of the OSSECO (e.g., recent updates); software developers may want to know about the activeness (e.g., how many collaborators are involved and how active they are); and the OSSECO community itself to know about the OSSECO health (e.g., evolving in the right direction). However, the current approaches for evaluating software quality (even those specific for open source software) do not cover all the aspects relevant in an OSSECO from an ecosystem perspective. Goal: The main goal of this PhD thesis is to support the OSSECO quality evaluation by designing a framework that supports the quality evaluation of OSSECOs. Methods: To accomplish this goal, we have used and approach based on design science methodology by Wieringa [1] and the characterization of software engineering proposed by M. Shaw [2], in order to produce a set of artefacts to contribute in thequality evaluation of OSSECOs and to learn about the effects of using these artefacts in practice. Results: We have conducted a systematic mapping to characterize OSSECOs and designed the QuESo framework (a framework to evaluate the OSSECO quality) composed by three artifacts: (i) QuESo-model, a quality model for OSSECOs; (ii) QuESoprocess, a process for conducting OSSECO quality evaluations using the QuESo-model; and (iii) QuESo-tool, a software component to support semi-automatic quality evaluation of OSSECOs. Furthermore, this framework has been validated with a case study on Eclipse. Conclusions: This thesis has contributed to increase the knowledge and understanding of OSSECOs, and to support the qualityevaluation of OSSECOs. [ntecedentes: el software de código abierto (OSS, por sus siglas en inglés) y los ecosistemas de software (SECOs, por sus siglas en inglés) son dos áreas de investigación consolidadas en ingeniería de software. La adopción de OSS por parte de empresas, gobiernos, investigadores y profesionales se ha incrementado rápidamente en las últimas décadas, y, en consecuencia, todos ellos hacen parte de un nuevo tipo de ecosistema formado por comunidades de software, fundaciones, desarrolladores y socios denominado ecosistema de software de código abierto. (OSSECO, por sus siglas en inglés)). Para realizar una evaluación sistemática de la calidad de un SECO, es necesario definir ciertos tipos de elementos concretos. Esto significa que tanto las métricas como las evaluaciones deben ser descritos (por ejemplo, a través de datos históricos o el conocimiento de expertos). La evaluación de la calidad de un OSSECO puede ser de utilidad desde diferentes perspectivas, por ejemplo: los que adoptan los productos del OSSECO pueden querer conocer la vitalidad del OSSECO (por ejemplo, el número de actualizaciones recientes); los desarrolladores de software pueden querer saber sobre la actividad del OSSECO (por ejemplo, cuántos colaboradores están involucrados y qué tan activos son); incluso la propia comunidad del OSSECO para conocer el estado de salud del OSSECO (por ejemplo, si está evolucionando en la dirección correcta). Sin embargo, los enfoques actuales para evaluar la calidad del software (incluso aquellos específicos para el software de código abierto) no cubren todos los aspectos relevantes en un OSSECO desde una perspectiva ecosistémica. Objetivo: El objetivo principal de esta tesis doctoral es apoyar la evaluación de la calidad de OSSECO mediante el diseño de un marco de trabajo que ayude a la evaluación de la calidad de un OSSECO. Métodos: Para lograr este objetivo, hemos utilizado un enfoque basado en la metodología design science propuesta por Wieringa [1]. Adicionalmente, nos hemos basado en la caracterización de la ingeniería de software propuesta por M. Shaw [2], con el fin de construir un conjunto de artefactos que contribuyan en la evaluación de la calidad de un OSSECO y para conocer los efectos del uso de estos artefactos en la práctica. Resultados: Hemos realizado un mapeo sistemático para caracterizar los OSSECOs y hemos diseñado el marco de trabajo denominado QuESo (es un marco de trabajo para evaluar la calidad de los OSSECOs). QuESo a su vez está compuesto por tres artefactos: (i) QuESo-model, un modelo de calidad para OSSECOs; (ii) QuESo-process, un proceso para llevar a cabo las evaluaciones de calidad de OSSECOs utilizando el modelo QuESo; y (iii) QuESo-tool, un conjunto de componentes de software que apoyan la evaluación de calidad de los OSSECOs de manera semiautomática. QuESo ha sido validado con un estudio de caso sobre Eclipse. Conclusiones: esta tesis ha contribuido a aumentar el conocimiento y la comprensión de los OSSECOs, y tambien ha apoyado la evaluación de la calidad de los OSSECOsPostprint (published version

    Open source software ecosystems quality analysis from data sources

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    Background: Open source software (OSS) and software ecosystems (SECOs) are two consolidated research areas in software engineering. The adoption of OSS by firms, governments, researchers and practitioners has been increasing rapidly in the last decades, and in consequence, they find themselves in a new kind of ecosystem composed by software communities,foundations, developers and partners, namely Open Source Software Ecosystem (OSSECO). In order to perform a systematic quality evaluation of a SECO, it is necessary to define certain types of concrete elements. This means that measures and evaluations should be described (e.g., through thresholds or expert judgment). The quality evaluation of an OSSECO may serve several purposes, for example: adopters of the products of the OSSECO may want to know about the liveliness of the OSSECO (e.g., recent updates); software developers may want to know about the activeness (e.g., how many collaborators are involved and how active they are); and the OSSECO community itself to know about the OSSECO health (e.g., evolving in the right direction). However, the current approaches for evaluating software quality (even those specific for open source software) do not cover all the aspects relevant in an OSSECO from an ecosystem perspective. Goal: The main goal of this PhD thesis is to support the OSSECO quality evaluation by designing a framework that supports the quality evaluation of OSSECOs. Methods: To accomplish this goal, we have used and approach based on design science methodology by Wieringa [1] and the characterization of software engineering proposed by M. Shaw [2], in order to produce a set of artefacts to contribute in thequality evaluation of OSSECOs and to learn about the effects of using these artefacts in practice. Results: We have conducted a systematic mapping to characterize OSSECOs and designed the QuESo framework (a framework to evaluate the OSSECO quality) composed by three artifacts: (i) QuESo-model, a quality model for OSSECOs; (ii) QuESoprocess, a process for conducting OSSECO quality evaluations using the QuESo-model; and (iii) QuESo-tool, a software component to support semi-automatic quality evaluation of OSSECOs. Furthermore, this framework has been validated with a case study on Eclipse. Conclusions: This thesis has contributed to increase the knowledge and understanding of OSSECOs, and to support the qualityevaluation of OSSECOs. [ntecedentes: el software de código abierto (OSS, por sus siglas en inglés) y los ecosistemas de software (SECOs, por sus siglas en inglés) son dos áreas de investigación consolidadas en ingeniería de software. La adopción de OSS por parte de empresas, gobiernos, investigadores y profesionales se ha incrementado rápidamente en las últimas décadas, y, en consecuencia, todos ellos hacen parte de un nuevo tipo de ecosistema formado por comunidades de software, fundaciones, desarrolladores y socios denominado ecosistema de software de código abierto. (OSSECO, por sus siglas en inglés)). Para realizar una evaluación sistemática de la calidad de un SECO, es necesario definir ciertos tipos de elementos concretos. Esto significa que tanto las métricas como las evaluaciones deben ser descritos (por ejemplo, a través de datos históricos o el conocimiento de expertos). La evaluación de la calidad de un OSSECO puede ser de utilidad desde diferentes perspectivas, por ejemplo: los que adoptan los productos del OSSECO pueden querer conocer la vitalidad del OSSECO (por ejemplo, el número de actualizaciones recientes); los desarrolladores de software pueden querer saber sobre la actividad del OSSECO (por ejemplo, cuántos colaboradores están involucrados y qué tan activos son); incluso la propia comunidad del OSSECO para conocer el estado de salud del OSSECO (por ejemplo, si está evolucionando en la dirección correcta). Sin embargo, los enfoques actuales para evaluar la calidad del software (incluso aquellos específicos para el software de código abierto) no cubren todos los aspectos relevantes en un OSSECO desde una perspectiva ecosistémica. Objetivo: El objetivo principal de esta tesis doctoral es apoyar la evaluación de la calidad de OSSECO mediante el diseño de un marco de trabajo que ayude a la evaluación de la calidad de un OSSECO. Métodos: Para lograr este objetivo, hemos utilizado un enfoque basado en la metodología design science propuesta por Wieringa [1]. Adicionalmente, nos hemos basado en la caracterización de la ingeniería de software propuesta por M. Shaw [2], con el fin de construir un conjunto de artefactos que contribuyan en la evaluación de la calidad de un OSSECO y para conocer los efectos del uso de estos artefactos en la práctica. Resultados: Hemos realizado un mapeo sistemático para caracterizar los OSSECOs y hemos diseñado el marco de trabajo denominado QuESo (es un marco de trabajo para evaluar la calidad de los OSSECOs). QuESo a su vez está compuesto por tres artefactos: (i) QuESo-model, un modelo de calidad para OSSECOs; (ii) QuESo-process, un proceso para llevar a cabo las evaluaciones de calidad de OSSECOs utilizando el modelo QuESo; y (iii) QuESo-tool, un conjunto de componentes de software que apoyan la evaluación de calidad de los OSSECOs de manera semiautomática. QuESo ha sido validado con un estudio de caso sobre Eclipse. Conclusiones: esta tesis ha contribuido a aumentar el conocimiento y la comprensión de los OSSECOs, y tambien ha apoyado la evaluación de la calidad de los OSSECO

    Open source software ecosystems : a systematic mapping

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    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
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