Expressive modular linking for object-oriented languages

technical reportIn this paper we show how modular linking of program fragments can be added to statically typed, object-oriented (OO) languages. Programs are being assembled out of separately developed software components deployed in binary form. Unfortunately, mainstream OO languages (such as Java) still do not provide support for true modular linking. Modular linking means that program fragments can be separately compiled and type checked, and that linking can ensure global program type correctness without analyzing program fragment implementations. Supporting modular linking in OO languages is complicated by two expressive features that current OO languages do not support together: mixin-style inheritance across program fragment boundaries, and cyclic dependencies between program fragments. In a previous paper at OOPSLA 2001, we have demonstrated the practical uses for such expressiveness. When such expressiveness is permitted, link-time type checking rules must ensure that method collisions and inheritance cycles do not occur after program fragments are linked into a program. In this paper, we show how modular linking with both cyclic linking and mixin-style inheritance can be supported using a type-checking architecture that can be added on top of existing OO languages, such as Java.

A path-precise analysis for property synthesis

technical reportRecent systems such as SLAM, Metal, and ESP help programmers by automating reasoning about the correctness of temporal program properties. This paper presents a technique called property synthesis, which can be viewed as the inverse of property checking. We show that the code for some program properties, such as proper lock acquisition, can be automatically inserted rather than automatically verified. Whereas property checking analyzes a program to verify that property code was inserted correctly, property synthesis analyzes a program to identify where property code should be inserted. This paper describes a path-sensitive analysis that is precise enough to synthesize property code effectively. Unlike other path-sensitive analyses, our intra-procedural path-precise analysis can describe behavior that occurs in loops without approximations. This precision is achieved by computing analysis results as a set of path machines. Each path machine describes assignment behavior of a boolean variable along all paths precisely. This paper explains how path machines work, are computed, and are used to synthesize code

A comparison of Jiazzi and AspectJ for feature-wise decomposition

technical reportFeature-wise decomposition is an important approach to building configurable software systems. Although there has been research on the usefulness of particular tools for featurewise decomposition, there are not many informative comparisons on the relative effectiveness of different tools. In this paper, we compare AspectJ and Jiazzi, which are two different systems for decomposing Java programs. AspectJ is an aspect-oriented extension to Java, whereas Jiazzi is a component system for Java. To compare these systems, we reimplemented an AspectJ implementation of a highly configurable CORBA Event Service using Jiazzi. Our experience is that Jiazzi provides better support for structuring the system and manipulating features, while AspectJ is more suitable for manipulating existing Java code in non-invasive and unanticipated ways

Semi-Automated SVG Programming via Direct Manipulation

Direct manipulation interfaces provide intuitive and interactive features to a broad range of users, but they often exhibit two limitations: the built-in features cannot possibly cover all use cases, and the internal representation of the content is not readily exposed. We believe that if direct manipulation interfaces were to (a) use general-purpose programs as the representation format, and (b) expose those programs to the user, then experts could customize these systems in powerful new ways and non-experts could enjoy some of the benefits of programmable systems. In recent work, we presented a prototype SVG editor called Sketch-n-Sketch that offered a step towards this vision. In that system, the user wrote a program in a general-purpose lambda-calculus to generate a graphic design and could then directly manipulate the output to indirectly change design parameters (i.e. constant literals) in the program in real-time during the manipulation. Unfortunately, the burden of programming the desired relationships rested entirely on the user. In this paper, we design and implement new features for Sketch-n-Sketch that assist in the programming process itself. Like typical direct manipulation systems, our extended Sketch-n-Sketch now provides GUI-based tools for drawing shapes, relating shapes to each other, and grouping shapes together. Unlike typical systems, however, each tool carries out the user's intention by transforming their general-purpose program. This novel, semi-automated programming workflow allows the user to rapidly create high-level, reusable abstractions in the program while at the same time retaining direct manipulation capabilities. In future work, our approach may be extended with more graphic design features or realized for other application domains.Comment: In 29th ACM User Interface Software and Technology Symposium (UIST 2016

SB27-20/21: Resolution Creating a Code of Ethics

SB27-20/21: Resolution Creating a Code of Ethics. This resolution was approved unanimously during the September 23, 2020 meeting of the Associated Students of the University of Montana (ASUM)

An Overview of the Scala Programming Language (2. Edition)

Scala fuses object-oriented and functional programming in a statically typed programming language. It is aimed at the construction of components and component systems. This paper gives an overview of the Scala language for readers who are familar with programming methods and programming language design

Glitch: A Live Programming Model

Abstract Input changes are often handled by reactive and incremental constructs that are tedious to use or inexpressive, while changes to program code are typically not handled at all during execution, complicating support for "live programming." We propose that change in code and input should be managed automatically, similar to how garbage collection eliminates memory management as an explicit programmer concern. Our programming model, Glitch, realizes such managed time by progressively re-executing nodes of program execution when they become inconsistent due input/code state changes. Unlike many reactive models, Glitch supports expressive shared-state procedural programming, but with one caveat: operations on shared state must be undoable and commutative to ensure re-execution efficiency and eventual consistency. Still, complex programs like compilers can be written in Glitch using mundane programming styles. Overview Programs react continuously to changing inputs by repairing their execution state. Beyond tediously using callbacks and observers, declarative approaches based on functions [6], constraints Change in program code during execution is handled even more poorly, which is essential to providing programmers with responsive execution feedback during live programming [10] or in Bret Victor's demoes The goal of our work is to (a) manage input and code changes automatically, removing change as an explicit programmer concern, while (b) also improving expressiveness to expand what programs can take advantage of such managed time, a concept that was introduced by Edwards To do better, we are inspired by Time Warps in virtual time We meld elements of incremental computation and Time Warps together to form an expressive managed time model that can support input and code changes efficiently. Our solution improves on rollback by logging imperative operations on execution, undoing them only when they are not performed on re-execution. Because re-execution can occur in arbitrary orders, imperative operations must also be commutative. We have found that these requirements are not overly restrictive; e.g. they are good enough to write a compiler. Glitch A program execution in our model, called Glitch, is decomposed into a tree of nodes that can be re-executed independently on a code or input change. Node decompositions are specified by programmers based on their understanding of the program's run-time modularity; e.g. execution nodes for a compiler can be chosen to correspond to nodes of the syntax tree (AST) for the code being compiled. Consider