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Abstract:The software development process is a key factor in the efficient production of quality software. Software process improvement has been a constant theme not only in academia but also in the software industry, where countless works have been developed and published. The Theory of Constraints (TOC) was originally proposed by the physicist Eliyahu Moshe Goldratt, in the 80s as a method for the continuous improvement of manufacturing processes. This research aims to survey the academic research on the application of the TOC to the software development process. We also searched for its application to other productive environments in an attempt to visualize approaches that could be adapted to the software development process, such as studies about process optimization, process improvement and process scheduling. The results showed research opportunities both theoretical and practical with application of the TOC in software process development, software process improvement, identification and treatment of bottlenecks in software process, optimization of software process and applications using heuristics, meta heuristics, mathematical models and optimization models.

This work presents the results of a case study to identify the main risk factors in the software deployment phase involving two government Brazilian companies. The case study was developed through several on-site visits to monitor the deployment of the system adopted by companies and conduct interviews with team managers. The data were acquired mainly through questionnaires applied to the technical team (analysts and developers) involved with the software implementation. After acquiring the data, an empirical analysis was carried out, where the Risk Factors (RF) and the Containment Strategies (CS) identified in the literature were compared with the RF and CS found in the software deployment phase of the two companies. As a result, this work presents 11 risk factors and 14 Containment strategies found in the literature, in addition to a total of 9 RF and 9 CS recorded in the implementation of the software in companies A and B, which had not yet been cataloged in the literature.

No processo de implantação de software, inúmeras falhas podem ocorrer, comprometendo a entrega ao cliente, tais como a falta de recursos, o surgimento de novos requisitos e a não aceitação pelos usuários das mudanças impostas devido à implantação. Estas mudanças estão associadas à adoção de novas tecnologias ou uma nova metodologia de trabalho. Este artigo mostra os resultados de uma revisão da literatura com o intuito de identificar os principais fatores de risco envolvidos neste processo, suas causas e estratégias de contenção durante a entrega do software ao usuário final. A partir deste mapeamento, serão apresentados estudos primários que tratam os fatores de riscos na fase de implantação de projetos de software. A partir dos resultados obtidos, apresentamos onze fatores que visam contribuir na eficácia do gerenciamento de riscos de software durante a fase de implantação.

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This work proposes a Dynamic Job Shop Scheduling (DJSS) model for scheduling the task in a software production environment. The aim is to organize the insertion of tasks in the shop in a precedence order previously defined that obeys the mapping of the critical path and the critical chain to identify constraints in the productive process. The complexity and dynamism of the software development environment require a mature and adjusted process that enables management throughout its extension. Therefore, the Unified Process (UP) was used in conjunction with the Theory of Constraints (TOC) in the Software Development Process (SDP). The UP requires an efficient model for the processing of activities, given by the set of independent variables involved in the process. For this reason, a model to programming the task based on dynamic scheduling was developed. The problem around the DJSS is to program the tasks in the shop in a way that allows identifying one or more production lines in the shop with constraints of capacity at runtime. A capacity constraint is any element that disturbs the productive process, causing L={Mi Aj} to have delivery (DA) of less than 100% of the artifacts, given by the set of jobs (j n ) scheduled. The resource with capacity constraint limits the production of the machines in the production line, leading to bottlenecks in the production process. A bottleneck, in turn, is denoted by the production limitation of a machine (people) caused by one or more capacity constraints that imply maximum production, which in this case is defined by D={Mi, Aj=100%}. In this work, the maximum production is given by the set of tasks processed in each of the phases of the UP and according to the productive calendar, which delimits the deadline of each delivery and establishes the budget of hours

Este artigo apresenta um fragmento de modelo ontológico do domínio de testes de software, representado pelos principais objetos, papéis, relações, fases e artefatos produzidos. Posteriormente, são apresentadas duas abordagens conceituais complementares dos elementos envolvidos no teste de software, utilizando como base a Ontologia de Fundamentação-A (UFO-A), com o objetivo de fornecer uma compreensão mais clara da modelagem conceitual existente no processo de testes.

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