Abstract. This paper indicates how effective software-process programming languages can lead to improved understandings of critical software processes, as well as improved process performance. In this paper we study the commonly mentioned, but seldom defined, rework process. We note that rework is generally understood to be a major software development activity, but note that it is poorly defined and understood. In this paper we use the vehicle of softwareprocess programming to elucidate the nature of this type of process. In doing so we demonstrate that an effective language (i.e. one incorporating appropriate semantic features) can help explain the nature of rework, and also raise hopes that this type of process can be expedited through execution of the defined process. The paper demonstrates the key role played in effective rework definition by such semantic features as procedure invocation, scoping, exception management, and resource management, which are commonly found in programming languages. A more ambitious program of research into the most useful processprogramming language semantic features is then suggested. The goal of this work is improved languages, for improved understandings of software processes, and improved support for software development.

Abstract.Many studies have shown that selective undo, a variant of the widelyimplemented linear undo, has many advantages over the prevailing model. In this paper, we define a task model for implementing selective undo in the face of dependencies that may exist between the undone action and other subsequent user actions. Our model accounts for these dependencies by identifying other actions besides the undone one that should also be undone to keep the application in a stable state. Our approach, which we call cascading selective undo, is built upon a process-programming language originally designed in the software engineering community. The result is a formal analytical framework by which the semantics of selective undo can be represented separately from the application itself. We present our task model, the selective undo algorithm, and discuss extensions that account for differing kinds of inter-action dependencies.

Little-JIL, a new language for programming the coordination of agents is an executable

Little-JIL, a new language for programming the coordination of agents is an executable

While various models of undo have been proposed over the years, no empirical study has yet been done to discover which model of undo most closely aligns with what users expect an undo command should do. In this paper, we discuss the results of such a study that compares the ubiquitous linear undo model with two variations of selective undo: script selective and cascading selective. Unlike the script model, cascading selective undo takes into account dependencies between user actions. Our study shows that, for the application studied, when a user is asked to perform undo in the absence of any guidance, the user will tend to gravitate toward an undo mechanism that uses existing dependencies between user actions. Specifically, we show that subjects prefer the dependency-aware aspects of cascading undo over either linear or script selective undo.