Monalessa Perini Barcellos

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Measurement is an important activity in several domains. Although there are specific concepts regarding measurement in each domain, some concepts are common to all of them. This paper presents a Measurement Ontology Pattern Language (M-OPL) that addresses the measurement core conceptualiza-tion. M-OPL can be used for building measurement ontologies to(More)
Ontology design patterns have been pointed out as a promising approach for ontology engineering. The goal of this paper is twofold. Firstly, based on well-established works in Software Engineering, we revisit the notion of ontology patterns in Ontology Engineering to introduce the notion of ontolo-gy pattern language as a way to organize related ontology(More)
The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain(More)
Enterprise ontologies are useful for many purposes. Over the years, there have been a number of efforts aiming at building them. However, due to the complexity of the enterprise domain, enterprise ontologies tend to be complex and difficult to reuse. In this paper, we advocate in favor of organizing Core Enterprise Ontologies as Ontology Pattern Languages,(More)
Software measurement is a key process for software process improvement. Measurement provides organizations with the objective information they need to make informed decisions that impact their business performance. Nowadays, there are several process quality models and standards that point out the importance of software measurement, such as CMMI.(More)
The escalating demands on the development of software products require software organizations to produce mature software processes that are capable of providing the required levels of quality and productivity. The implementation of statistical process control (SPC) in performance process analysis uses data collected during the course of the project to(More)
Software organizations have increased their interest in software process improvement (SPI). Nowadays, there are several frameworks that support SPI implementation. Some of them, such as CMMI (Capability Maturity Model Integration), propose to implement SPI in levels. At high maturity levels, such as CMMI levels 4 and 5, SPI involves carrying out statistical(More)
Organizations define strategies and establish business goals aiming to be competitive. The process performance analysis supports goals monitoring, allowing to detect and to treat threats to goals achievement. In this context, measurement is essential. The collected data for measures are used to analyze the process performance and to guide informed decisions(More)