Copy-and-paste, one of the fundamental operations of modern user interfaces, can be performed through various means (e.g. using the keyboard, mouse-based direct manipulation or menus). When users copy and paste between two different windows, the process is complicated by window management tasks. In this paper, we propose two new window management techniques to facilitate these tasks in the particular case of partially overlapping windows. We describe an experiment comparing four commonly used copy-andpaste techniques under four window management conditions – non-overlapping windows, partially overlapping windows, and partially overlapping ones with one of our two window management techniques. Results show that our new window management techniques significantly reduce task completion time for all copy-and-paste techniques. They also show that X Window copy-and-paste is faster than the other three techniques under all four window management conditions.

Creating and editing source code are tedious and error-prone processes. One important source of errors in editing programs is the failure to correctly adapt a block of copied code to a new context. This occurs because several dependencies to the surrounding code usually need to be adapted for the new context and it is easy to forget one of them. Conversely, this also makes such errors hard to find. This paper presents a new method for identifying some common types of errors in cut, copy and paste operations. The method analyzes the context of the original block of code and tries to match it with the context in the new location. It utilizes a simple, pattern-based model of context, which we found to be well suited to the analysis of relocated blocks of text. Furthermore, we discuss the ability of our technique to detect semantic errors. While semantic errors are relatively difficult to recognize in a static document, our new technique can infer important information from the original context to detect some semantic mismatches. Finally, we present a proof-of-concept implementation and discuss our simple user interface for contextsensitive cut, copy and paste.

Transferring data across applications is a common end user task, and copying and pasting via the clipboard lets users do so relatively easily. Using the clipboard, however, can also introduce inefficiencies and errors in user tasks. To help researchers and tool developers understand and address these problems, we studied how end users interact with the clipboard through cut, copy, and paste actions. This study was performed by logging clipboard interactions while end users performed everyday tasks. From the clipboard usage data, we have identified several usage patterns that describe how data is transferred within the desktop environment. Such patterns help us understand end user behavior and indicate areas in which clipboard support tools can be improved. 1.

items across multiple contexts.