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Item type:Publication, Software testing in the DevOps context: A systematic mapping study(Pleiades Publishing, 2022-12-01)Abstract: DevOps is a philosophy and framework that allows software development and operations teams to work in a coordinated manner, with the purpose of developing and releasing software quickly and cheaply. However, the effectiveness and benefits of DevOps depend on several factors, as reported in the literature. In particular, several studies have been published on software test automation, which is a cornerstone for the continuous integration phase in DevOps, which needs to be identified and classified. This study consolidates and classifies the existing literature on automated tests in the DevOps context. For the study, a systematic mapping study was performed to identify and classify papers on automated testing in DevOps based on 8 research questions. In the query of 6 relevant databases, 3,312 were obtained; and then, after the selection process, 299 papers were selected as primary studies. Researchers maintain a continuing and growing interest in software testing in the DevOps context. Most of the research (71.2%) is carried out in the industry and is done on web applications and SOA. The most reported types of tests are unit and integration tests. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Microfinance institutions failure prediction in emerging countries, a machine learning approach(Public Library of Science, 2025-04-01)This study is about what matters: predicting when microfinance institutions might fail, especially in places where financial stability is closely linked to economic inclusion. The challenge? Creating something practical and usable. The Adjusted Gross Granular Model (ARGM) model comes here. It combines clever techniques, such as granular computing and machine learning, to handle messy and imbalanced data, ensuring that the model is not just a theoretical concept but a practical tool that can be used in the real world.Data from 56 financial institutions in Peru was analyzed over almost a decade (2014-2023). The results were quite promising. The model detected risks with nearly 90% accuracy in detecting failures and was right more than 95% of the time in identifying safe institutions. But what does this mean in practice? It was tested and flagged six institutions (20% of the total) as high risk. This tool's impact on emerging markets would be very significant. Financial regulators could act in advance with this model, potentially preventing financial disasters. This is not just a theoretical exercise but a practical solution to a pressing problem in these markets, where every failure has domino effects on small businesses and clients in local communities, who may see their life savings affected and lost due to the failure of these institutions. Ultimately, this research is not just about a machine learning model or using statistics to evaluate results. It is about giving regulators and supervisors of financial institutions a tool they can rely on to help them take action before it is too late when microfinance institutions get into bad financial shape and to make immediate decisions in the event of a possible collapse.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing the role of servicing in enhancing sanitation-related quality of life among container-based sanitation users(Springer Nature, 2025-10-01)Here we evaluate the servicing of container-based sanitation (CBS)-which includes the collection, replacement and cleaning of cartridges-and its influence on sanitation-related quality of life (using the SanQoL-5 index) in informal settlements across Kenya, Peru and South Africa. We (1) compared the incidence and severity of problems associated with CBS toilets against other sanitation types, (2) assessed the quality of CBS servicing across different regions and implementations and (3) evaluated the relationship between servicing issues and sanitation-related quality of life, utilizing high-frequency longitudinal smartphone survey data collected at various intervals over 1 year. Results revealed significantly fewer and less severe issues were recorded for CBS toilets than other toilet types, such as pit latrines, sewers and open drains. CBS servicing was consistently well regarded in all countries. Participants in Kenya highlighted particular satisfaction with the frequency of container replacement, whereas, in Peru, the cleanliness of replacement containers was highly regarded. SanQoL-5 scores decreased when CBS servicing issues were recorded, particularly in Kenya. This study underscores the potential of CBS as a sustainable sanitation solution in urban informal settlements, provided that high-quality servicing is maintained.2