Pharo

Abstract: This paper presents our experience in implementing a chatbot for expert recommendation tasks. The chatbot was developed for the Pharo software ecosystem, and is integrated with the Discord chat service, which is used by the Pharo Community. We also report on a preliminary evaluation for which; the recommendation system was welcomed, though the conversational behavior was not; users expected a fully conversational chatbot, capable of following the conversation flow that the user handles. We discuss that such expectations might be hard to meet because of the uncanny valley effect.

Abstract: Application Programming Interfaces (APIs) are a tremendous resource—that is, when they are stable. Several studies have shown that this is unfortunately not the case. Of those, a large-scale study of API changes in the Pharo Smalltalk ecosystem documented several findings about API deprecations and their impact on API clients. We extend this study, by analyzing clients of both popular third-party Java APIs and the JDK API. This results in a dataset consisting of more than 25,000 clients of five popular Java APIs on GitHub, and 60 clients of the JDK API from Maven Central. This work addresses several shortcomings of the previous study, namely: a study of several distinct API clients in a popular, statically-typed language, with more accurate version information. We compare and contrast our findings with the previous study and highlight new ones, particularly on the API client update practices and the startling similarities between reaction behavior in Smalltalk and Java. We make a comparison between reaction behavior for third-party APIs and JDK APIs, given that language APIs are a peculiar case in terms of wide-spread usage, documentation, and support from IDEs. Furthermore, we investigate the connection between reaction patterns of a client and the deprecation policy adopted by the API used.

Abstract: Dependency Structure Matrix (DSM) has been successfully applied to identify software dependencies among packages and subsystems. A number of algorithms were proposed to compute the matrix so that it highlights patterns and problematic dependencies between subsystems. However, existing DSM implementations often miss important information to fully support reengineering effort. For example, they do not clearly qualify and quantify problematic relationships, information which is crucial to support remediation tasks.In this paper we present enriched DSM (eDSM) where cells are enriched with contextual information about (i) the type of dependencies (inheritance, class reference...), (ii) the proportion of referencing entities, (iii) the proportion of referenced entities. We distinguish independent cycles and stress potentially simple fixes for cycles using coloring information. This work is language independent and has been implemented on top of the Moose reengineering environment. It has been applied to non-trivial case studies among which ArgoUML, and Morphic the UI framework available in two open-source Smalltalks, Squeak and Pharo. Solution to problems identified by eDSM have been performed and retrofitted in Pharo main distribution.