Sketches and diagrams play an important role in the daily work of software developers. In this paper, we investigate the use of sketches and diagrams in software engineering practice. To this end, we used both quantitative and qualitative methods. We present the results of an exploratory study in three companies and an online survey with 394 participants. Our participants included software developers, software architects, project managers, consultants, as well as researchers. They worked in different countries and on projects from a wide range of application areas. Most questions in the survey were related to the last sketch or diagram that the participants had created. Contrary to our expectations and previous work, the majority of sketches and diagrams contained at least some UML elements. However, most of them were informal. The most common purposes for creating sketches and diagrams were designing, explaining, and understanding, but analyzing requirements was also named often. More than half of the sketches and diagrams were created on analog media like paper or whiteboards and have been revised after creation. Most of them were used for more than a week and were archived. We found that the majority of participants related their sketches to methods, classes, or packages, but not to source code artifacts with a lower level of abstraction.
@cite_3 conducted a survey with 280 software engineers at Microsoft. They found that paper and whiteboards were perceived as most effective for designing. Furthermore, they state that understanding the rationale behind code is the biggest problem for developers. In our study, over half of the sketches helped the respondents to understand source code or general issues.
@cite_3
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To understand developers' typical tools, activities, and practices and their satisfaction with each, we conducted two surveys and eleven interviews. We found that many problems arose because developers were forced to invest great effort recovering implicit knowledge by exploring code and interrupting teammates and this knowledge was only saved in their memory. Contrary to expectations that email and IM prevent expensive task switches caused by face-to-face interruptions, we found that face-to-face communication enjoys many advantages. Contrary to expectations that documentation makes understanding design rationale easy, we found that current design documents are inadequate. Contrary to expectations that code duplication involves the copy and paste of code snippets, developers reported several types of duplication. We use data to characterize these and other problems and draw implications for the design of tools for their solution. Software developers are rooted in the written form of their code, yet they often draw diagrams representing their code. Unfortunately, we still know little about how and why they create these diagrams, and so there is little research to inform the design of visual tools to support developers' work. This paper presents findings from semi-structured interviews that have been validated with a structured survey. Results show that most of the diagrams had a transient nature because of the high cost of changing whiteboard sketches to electronic renderings. Diagrams that documented design decisions were often externalized in these temporary drawings and then subsequently lost. Current visualization tools and the software development practices that we observed do not solve these issues, but these results suggest several directions for future research. [Context] Many software projects fail due to problems in requirements engineering (RE). [Objective] The goal of this paper is to gather information on relevant RE problems and to represent knowledge on their most common causes. [Method] We replicated a global family of RE surveys in the Brazil and used the data to identify critical RE problems and to build probabilistic cause-effect diagrams to represent knowledge on their common causes. [Results] The survey was answered by 74 different organizations, including small, medium and very large sized companies, conducting both, plan-driven and agile development. The most critical RE problems, according to those organizations, are related to communication and to incomplete or underspecified requirements. We provide the full probabilistic cause-effect diagrams with knowledge on common causes of the most critical identified RE problems online. [Conclusion] We believe that the knowledge presented in the diagrams can be helpful to support organizations in conducting causal analysis sessions by providing an initial understanding on what usually causes critical RE problems. In a traditional sense, ownership determines rights and duties in regard to an object, for example a property. The owner of source code usually refers to the person that invented the code. However, larger code artifacts, such as files, are usually composed by multiple engineers contributing to the entity over time through a series of changes. Frequently, the person with the highest contribution, e.g. the most number of code changes, is defined as the code owner and takes responsibility for it. Thus, code ownership relates to the knowledge engineers have about code. Lacking responsibility and knowledge about code can reduce code quality. In an earlier study, [1] showed that Windows binaries that lacked clear code ownership were more likely to be defect prone. However recommendations for large artifacts such as binaries are usually not actionable. E.g. changing the concept of binaries and refactoring them to ensure strong ownership would violate system architecture principles. A recent replication study by [2] on open source software replicate the original results and lead to doubts about the general concept of ownership impacting code quality. In this paper, we replicated and extended the previous two ownership studies [1, 2] and reflect on their findings. Further, we define several new ownership metrics to investigate the dependency between ownership and code quality on file and directory level for 4 major Microsoft products. The results confirm the original findings by [1] that code ownership correlates with code quality. Using new and refined code ownership metrics we were able to classify source files that contained at least one bug with a median precision of 0.74 and a median recall of 0.38. On directory level, we achieve a precision of 0.76 and a recall of 0.60.