We analyzed what computer vision techniques have been adopted or designed, for what reasons, how they are used, what benefits they provide, and how they are evaluated. We collected an initial pool of 2,716 papers, from which we obtained 66 final relevant papers covering a variety of SE areas. Our inclusion criteria targeted papers applying computer vision techniques that address problems related to any area of SE. We examined an extensive body of literature from top-tier SE venues, as well as venues from closely related fields (machine learning, computer vision, and human-computer interaction). The goal of this manuscript is to survey the use of computer vision techniques in SE with the aim of assessing their potential in advancing the field of SE research. These approaches allow analyzing the software from a different complementary perspective other than the source code, and they are used to either complement existing source code-based methods, or to overcome their limitations. However, novel approaches that analyze software through computer vision have been increasingly adopted in SE. Software engineering (SE) research has traditionally revolved around engineering the source code. We also reported 33 bugs, some of which have already been confirmed or fixed by developers. We evaluate our automatic approach on a large corpus of over 230 K documents using 11 popular readers and our experiments have detected 30 unique bugs in these readers and files. We then propose an approach to detect and localize the source of such inconsistencies automatically. We start by manually investigating a large number of real-world PDF documents to understand the frequency and characteristics of cross-reader inconsistencies, and find that such inconsistencies are common-13.5% PDF files are inconsistently rendered by at least one popular reader. In this paper, we present a study on the correctness of PDF documents and readers. However, this is not always the case, and these inconsistencies, regardless of their causes-bugs in the application or the file itself-can become critical sources of miscommunication. Many different applications exist for displaying a given electronic document, and users rightfully assume that documents will be rendered similarly independently of the application used. Electronic documents are widely used to store and share information such as bank statements, contracts, articles, maps and tax information.
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