When the Application Programming Interface (API) of a framework or library changes, its clients must be adapted. This change propagation-known as a ripple effect-is a problem that has garnered interest: several approaches have been proposed in the literature to react to these changes. Although studies of ripple effects exist at the single system level, no study has been performed on the actual extent and impact of these API changes in practice, on an entire software ecosystem associated with a community of developers. This paper reports on an empirical study of API deprecations that led to ripple effects across an entire ecosystem. Our case study subject is the development community gravitating around the Squeak and Pharo software ecosystems: seven years of evolution, more than 3,000 contributors, and more than 2,600 distinct systems. We analyzed 577 methods and 186 classes that were deprecated, and answer research questions regarding the frequency, magnitude, duration, adaptation, and consistency of the ripple effects triggered by API changes.

Modern IDEs such as Eclipse offer static views of the source code, but such views ignore information about the run-time behavior of software systems. Since typical object-oriented systems make heavy use of polymorphism and dynamic binding, static views will miss key information about the run-time architecture. In this paper we show by means of a controlled experiment with 30 professional developers that for typical software maintenance tasks integrating dynamic information into the Eclipse IDE yields a significant 17.5% decrease of time spent while significantly increasing the correctness of the solutions by 33.5%. Furthermore, we describe several enhancements to the Eclipse IDE that integrate static and dynamic information, with the goal of better supporting typical software maintenance activities. We elaborate on a case study which further highlights the usefulness of dynamic information for performance optimizations. We also report on several important efficiency improvements to our dynamic information collection framework, and we present benchmarks evaluating the overhead of our approach.

Artículo de publicación ISIThe dynamic and reflective features of programming languages are powerful constructs that programmers often mention as extremely useful. However, the ability to modify a program at runtime can be both a boon—in terms of flexibility—, and a curse—in terms of tool support. For instance, usage of these features hampers the design of type systems, the accuracy of static analysis techniques, or the introduction of optimizations by compilers. In this paper, we perform an empirical study of a large Smalltalk codebase—often regarded as the poster-child in terms of availability of these features—, in order to assess how much these features are actually used in practice, whether some are used more than others, and in which kinds of projects. In addition, we performed a qualitative analysis of a representative sample of usages of dynamic features in order to uncover (1) the principal reasons that drive people to use dynamic features, and (2) whether and how these dynamic feature usages can be removed or converted to safer usages. These results are useful to make informed decisions about which features to consider when designing language extensions or tool support

Dynamic, unanticipated adaptation of running systems is of interest in a variety of situations, ranging from functional upgrades to on-the-fly debugging or monitoring of critical applications. In this paper we study a particular form of computational reflection, called unanticipated partial behavioral reflection, which is particularly well-suited for unanticipated adaptation of real-world systems. Our proposal combines the dynamicity of unanticipated reflection, i.e., reflection that does not require preparation of the code of any sort, and the selectivity and efficiency of partial behavioral reflection. First, we propose unanticipated partial behavioral reflection which enables the developer to precisely select the required reifications, to flexibly engineer the metalevel and to introduce the meta behavior dynamically. Second, we present a system supporting unanticipated partial behavioral reflection in Squeak Smalltalk, called Geppetto, and illustrate its use with a concrete example of a web application. Benchmarks validate the applicability of our proposal as an extension to the standard reflective abilities of Smalltalk.

No abstract