Browsing by Author "Crasso,M."
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Article Citation Count: 14Assessing cognitive complexity in Java-based Object-Oriented systems: Metrics and tool support(Slovak Academy of Sciences, 2016) Mısra, Sanjay; Mateos,C.; Zunino,A.; Misra,S.; Polvorín,P.; Computer EngineeringSoftware cognitive complexity refers to how demanding the mental process of performing tasks such as coding, testing, debugging, or modifying source code is. Achieving low levels of cognitive complexity is crucial for ensuring high levels of software maintainability, which is one of the most rewardful software quality attributes. Therefore, in order to control and ensure software maintainability, it is first necessary to accurately quantify software cognitive complexity. In this line, this paper presents a software metric to assess cognitive complexity in Object-Oriented (OO) systems, and particularly those developed in the Java language, which is very popular among OO programming languages. The proposed metric is based on a characterization of basic control structures present in Java systems. Several algorithms to compute the metric and their materialization in the Eclipse IDE are also introduced. Finally, a theoretical validation of the metric against a framework specially designed to validate software complexity metrics is presented, and the applicability of the tool is shown by illustrating the metric in the context of ten real world Java projects and relevant metrics from the well-known Chidamber-Kemerer metric suite.Conference Object Citation Count: 0An evaluation on developer's perception of XML schema complexity metrics for web services(2013) Mısra, Sanjay; Mateos,C.; Coscia,J.L.O.; Zunino,A.; Misra,S.; Computer EngineeringUndoubtedly, the Service-Oriented Computing (SOC) is not an incipient computing paradigm anymore, while Web Services technologies is now a very mature stack of technologies. Both have been steadily gaining maturity as their adoption in the software industry grew. Accordingly, several metric suites for assessing different quality attributes of Web Services have been recently proposed. In particular, researchers have focused on measuring services interfaces descriptions, which like any other software artifact, have a measurable size, complexity and quality. This paper presents a study that assesses human perception of some recent services interfaces complexity metrics (Basci and Misra's metrics suite). Empirical evidence suggests that a service interface that it is not complex for a software application, in terms of time and space required to analyze it, will not be necessarily well designed, in terms of best practices for designing Web Services. A Likert-based questionnaire was used to gather individuals opinions about this topic. © 2013 Springer-Verlag Berlin Heidelberg.Conference Object Citation Count: 13Predicting web service maintainability via object-oriented metrics: A statistics-based approach(2012) Mısra, Sanjay; Crasso,M.; Mateos,C.; Zunino,A.; Misra,S.; Computer EngineeringThe Service-Oriented Computing paradigm enables the construction of distributed systems by assembling loosely coupled pieces of software called services, which have clear interfaces to their functionalities. Service interface descriptions have many aspects, such as complexity and quality, all of which can be measured. This paper presents empirical evidence showing that services interfaces maintainability can be predicted by applying traditional software metrics in service implementations. A total of 11 source code level metrics and 5 service interface metrics have been statistically correlated using 154 real world services. © 2012 Springer-Verlag.Conference Object Citation Count: 19A suite of cognitive complexity metrics(2012) Koyuncu, Murat; Koyuncu,M.; Mısra, Sanjay; Mateos,C.; Zunino,A.; Information Systems Engineering; Computer EngineeringIn this paper, we propose a suite of cognitive metrics for evaluating complexity of object-oriented (OO) codes. The proposed metric suite evaluates several important features of OO languages. Specifically, the proposed metrics are to measure method complexity, message complexity (coupling), attributes complexity and class complexity. We propose also a code complexity by considering the complexity due to inheritance for the whole system. All these proposed metrics (except attribute complexity) use the cognitive aspect of the code in terms of cognitive weight. All the metrics have critically examined through theoretical and empirical validation processes. © 2012 Springer-Verlag.