Recent advances in Language Models have led to increasingly accurate models with enhanced capabilities to analyze and understand new datasets. This paper explores the use of open-source language models to extract judicial decisions from Portuguese consumer law texts. Our focus lies on the Named Entity Recognition (NER) task to identify and extract key information from documents. To this end, we evaluate models such as BERT, Meta’s Llama 3.1, and Google’s Gemma 2. The datasets used in this work were annotated and curated by domain-specialized lawyers. Experimental results demonstrate the effectiveness of applying Natural Language Processing (NLP) techniques along with transformer-based models for the NER task in Portuguese legal documents. We achieved results with higher accuracy with BERT models (F1-scores ranging from 0.74 to 0.96) for exact entity extraction, while LLMs showed promising results in zero-shot scenarios (F1-score of 0.85 for Llama 3). This work contributes to automating legal tasks and facilitating access to legal information in the Portuguese legal system.

The modernization of monolithic legacy systems with microservices has been a trend in recent years. As part of this modernization, identifying microservice candidates starting from legacy code is challenging, as maintainers may consider many criteria simultaneously. Multi-objective search-based approaches represent a promising state-of-the-art solution to support this decision-making process. However, the rationale to adopt each microservice candidate automatically identified by these approaches is poorly investigated in industrial cases. Furthermore, studies with these approaches have not carefully investigated how maintainers reason and make decisions when designing microservice architectures from legacy systems. To address this gap, we conducted an on-site case study with maintainers of an industrial legacy system to investigate the usefulness of automatically generated microservice architectures. We analyze design decisions pointed out by the maintainers when reasoning about microservice candidates using several criteria at the same time. Our study is the first to assess a search-based approach involving actual maintainers conceiving microservice architectures in an industrial setting. Therefore, firstly, we considered individual evaluation of microservice candidates to understand the rationale for identifying a service. Secondly, we conducted a focus group study with maintainers with the goal of investigating design decisions at an architectural level. The results show that:(i)the automated approach is able to identify useful microservices;(ii)the criteria observed by previous studies are, in fact, considered by maintainers; and(iii)the maintainer profiles, i.e., the preferred granularity for microservice, highly affect design decisions. Finally, we observed the maintainers needed little effort in adjusting the automatically identified microservices to make them adoptable. In addition to indicating a promising potential of search-based approaches to generate microservice architectures, our findings highlight the need for:(i)interactive and/or customizable approaches that enable maintainers to include their preferences during the search process, and(ii)flexible or automated selection of criteria that fits the scenario in which the modernization is taking place.

Microservices are small and autonomous services that communicate through lightweight protocols. Companies have often been adopting microservices to incrementally redesign legacy systems as part of a modernization process. Microservices promote better reuse and customization of existing features while increasing business capabilities, if appropriate design decisions are made. There are some partially-automated approaches supporting the re-design of legacy features into microservices. However, they fail in covering two key aspects: (i) provide an architectural design of the features being redesigned, and (ii) simultaneously support relevant criteria, e.g., feature modularization and decrease of network communication overhead. Also, these two aspects tend to be poorly discussed along industrial case studies. To fulfill these gaps, we propose a redesign strategy to support the re-engineering of features legacy code as microservices. This strategy covers key possibly-conflicting criteria on microservice-based architectures. We employ search-based optimization to deal with such conflicting criteria. The output of the strategy is a set of redesign candidates of legacy features as microservices. We reflect upon the benefits and drawbacks of the proposed strategy through an industrial case study. In particular, we perform an in-depth analysis of the resulting microservice candidates, and a discussion about their potential for customization and reuse. The reflections/discussions are also supported by observations of developers involved in the process.

The expensive maintenance of legacy systems leads companies to migrate such systems to microservice architectures. This migration requires the identification of system's legacy parts to become microservices. However, the successful identification of microservices, which are promising to be adoptable in practice, requires the simultaneous satisfaction of many criteria, such as coupling, cohesion, reuse and communication overhead. Search-based microservice identification has been recently investigated to address this problem. However, state-of-the-art search-based approaches are limited as they only consider one or two criteria (namely cohesion and coupling), possibly not fulfilling the practical needs of developers. To overcome these limitations, we propose toMicroservices, a many-objective search-based approach that considers five criteria, the most cited by practitioners in recent studies. Our approach was evaluated in a real-life industrial legacy system undergoing a microservice migration process. The performance of toMicroservices was quantitatively compared to a baseline. We also gathered qualitative evidence based on developers' perceptions, who judged the adoptability of the recommended microservices. The results show that our approach is both: (i) very similar to the most recent proposed approach on optimizing the traditional criteria of coupling and cohesion, but (ii) much better when taking into account all the five criteria. Finally, most of the microservice candidates were considered adoptable by practitioners.