http://hdl.handle.net/20.500.12953/6 Thu, 09 Apr 2026 06:10:52 GMT 2026-04-09T06:10:52Z http://hdl.handle.net/20.500.12953/62 Using Naming Patterns for Identifying Architectural Technical Debt Mendoza del Carpio, Paul Hasty software development can produce immediate implementations with source code unnecessarily complex and hardly readable. These small kinds of software decay generate a technical debt that could be big enough to seriously affect future maintenance activities. This work presents an analysis technique for identifying architectural technical debt related to non-uniformity of naming patterns; the technique is based on term frequency over package hierarchies. The proposal has been evaluated on projects of two popular organizations, Apache and Eclipse. The results have shown that most of the projects have frequent occurrences of the proposed naming patterns, and using a graph model and aggregated data could enable the elaboration of simple queries for debt identification. The technique has features that favor its applicability on emergent architectures and agile software development. Wed, 18 Jan 2017 00:00:00 GMT http://hdl.handle.net/20.500.12953/62 2017-01-18T00:00:00Z http://hdl.handle.net/20.500.12953/60 A Behavior Tree-Based Model for Supporting the Analysis of Knowledge Transferred in Software R&D Teams Fernández Del Carpio, Alvaro Software R&D teams require proper forms of representing knowledge at carrying out software engineering processes and researches. In this context, transfer of knowledge becomes a dynamic process because team members participating in the process acquire, communicate and integrate knowledge from different sources. In this paper, a behavior tree-based model is presented for representing knowledge generated from research and development activities. Through structured nodes representing pieces of knowledge, it is possible to identify key points of new challenges, concerns, issues, gaps, etc., and shed lights on new insights and knowledge of importance to team members, contributing to improve and provide solutions to the domain analyzed. Thu, 12 May 2016 00:00:00 GMT http://hdl.handle.net/20.500.12953/60 2016-05-12T00:00:00Z http://hdl.handle.net/20.500.12953/47 Framework Based on Aggregated Graphs for Analysis of Architectural Conformance from Source Code Mendoza del Carpio, Paul Agile approaches consider the software architecture as an emergent feature that can have an intended structure but could be not documented. To controlling the architectural erosion, an architectural conformance analysis could be performed, but considering the source code as a primordial input. This work presents a framework that supports the development of applications for architectural conformance analysis based on rules and measures. The framework uses aggregated graphs, MapReduce operations, and an external DSL; and has been evaluated over studies related to software architecture, and projects like the test suite of Red Hat WildFly and WordPress for Android. The gotten results favor the use of the framework for executing a continuous architectural analysis from source code. Mon, 29 Aug 2016 00:00:00 GMT http://hdl.handle.net/20.500.12953/47 2016-08-29T00:00:00Z http://hdl.handle.net/20.500.12953/46 Identification of architectural technical debt: An analysis based on naming patterns Mendoza del Carpio, Paul Hasty software development can produce immediate implementations with source code unnecessarily complex and hardly readable. These small kinds of software decay generate a technical debt that could be big enough to seriously affect future maintenance activities. This work presents an analysis technique for identifying architectural technical debt related to non-uniformity of naming patterns; the technique is based on term frequency over package hierarchies. The proposal has been evaluated on projects of two popular organizations, Apache and Eclipse. The results have shown that most of the projects have frequent occurrences of the proposed naming patterns, and using a graph model and aggregated data could enable the elaboration of simple queries for debt identification. The technique has features that favor its applicability on emergent architectures and agile software development. Thu, 28 Apr 2016 00:00:00 GMT http://hdl.handle.net/20.500.12953/46 2016-04-28T00:00:00Z