The benefits of using assessment tools for programming assignments have been widely discussed in computing education. However, as both researchers and instructors are unaware of the characteristics of existing tools, they are either not used or are reimplemented. This paper presents the results of a study conducted to collect and evaluate evidence about tools that assist in the assessment of programming assignments. To achieve our goal, we performed a systematic literature review since it provides an objective procedure for identifying the quantity of existing research related to a research question. The results identified subjects in the development of new assessment tools that researchers could better investigate and characteristics of assessment tools that could help instructors make selections for their programming courses.

Background: A Systematic Literature Review (SLR) is a methodology used to aggregate relevant evidence related to one or more research questions. Whenever new evidence is published after the completion of a SLR, this SLR should be updated in order to preserve its value. However, updating SLRs involves significant effort. Objective: The goal of this paper is to investigate the application of forward snowballing to support the update of SLRs. Method: We compare outcomes of an update achieved using the forward snowballing versus a published update using the search-based approach, i.e., searching for studies in electronic databases using a search string. Results: Forward snowballing showed a higher precision and a slightly lower recall. It reduced in more than five times the number of primary studies to filter however missed one relevant study. Conclusions: Due to its high precision, we believe that the use of forward snowballing considerably reduces the effort in updating SLRs in Software Engineering; however the risk of missing relevant papers should not be underrated.

Software architectures have been recognized as the backbone to the success of any software system. In addition, they are responsible to aggregate quality attributes, such as interoperability, dependability, and maintainability, to these systems. In parallel, currently, a new class of complex software systems has emerged, referred as Systems of Systems (SoS), resulting from a number of operationally and managerially independent software systems working together to fulfill a mission that none system alone could provide. Considering their complexity, the development of SoS has demanded special attention to their software architectures. In this scenario, the description of such architectures, i.e., the way that these architectures are represented/documented, becomes quite important as it can improve communication as well as evaluation and maintenance of these architectures. Despite its relevance, there is still no complete panorama about architectural descriptions of SoS. The main contribution of this paper is to present results of a Systematic Literature Review (SLR) on how SoS software architectures have been described. As main result, there are already important contributions in that direction; however, there is a lack of consensus on how better dealing with these descriptions. We conclude this paper with directions on how a consensus could be achieved and which aspects of the SoS architectural descriptions require further investigation.

Background: A systematic literature review (SLR) is a methodology used to aggregate all relevant existing evidence to answer a research question of interest. Although crucial, the process used to select primary studies can be arduous, time consuming, and must often be conducted manually. Objective: We propose a novel approach, known as 'Systematic Literature Review based on Visual Text Mining' or simply SLR-VTM, to support the primary study selection activity using visual text mining (VTM) techniques. Method: We conducted a case study to compare the performance and effectiveness of four doctoral students in selecting primary studies manually and using the SLR-VTM approach. To enable the comparison, we also developed a VTM tool that implemented our approach. We hypothesized that students using SLR-VTM would present improved selection performance and effectiveness. Results: Our results show that incorporating VTM in the SLR study selection activity reduced the time spent in this activity and also increased the number of studies correctly included. Conclusions: Our pilot case study presents promising results suggesting that the use of VTM may indeed be beneficial during the study selection activity when performing an SLR.

System-of-Systems (SoS) have been considered the new trend of software systems for several reasons, such as the advancement of computer technology and the increasing complexity and size of the systems. The concept of SoS has the central idea of a set of operationally independent software systems that collaborate together to compose a larger and more complex system. For SoS, several quality attributes are critical due to its characteristics and domain constraints. However, the existent quality models were not conceived to address SoS. Therefore, the identification of quality models that can address the quality attributes for SoS needs to be investigated. So, the purpose of this work is to identify the most common quality attributes in SoS context and analyze their coverage by the well established ISO/IEC 25010 quality model. As a result, we have identified that the current quality models cannot address the complex interdependencies between SoS quality attributes due its dynamic nature.