Conclave: ontology-driven measurement of semantic relatedness between source code elements and problem domain concepts

Software maintainers are often challenged with source code changes to improve software systems, or eliminate defects, in unfamiliar programs. To undertake these tasks a sufficient understanding of the system (or at least a small part of it) is required. One of the most time consuming tasks of this process is locating which parts of the code are responsible for some key functionality or feature. Feature (or concept) location techniques address this problem. This paper introduces Conclave, an environment for software analysis, and in particular the Conclave-Mapper tool that provides a feature location facility. This tool explores natural language terms used in programs (e.g. function and variable names), and using textual analysis and a collection of Natural Language Processing techniques, computes synonymous sets of terms. These sets are used to score relatedness between program elements, and search queries or problem domain concepts, producing sorted ranks of program elements that address the search criteria, or concepts. An empirical study is also discussed to evaluate the underlying feature location technique.info:eu-repo/semantics/publishedVersio

Contextual documentation referencing on stack overflow

Software engineering is knowledge-intensive and requires software developers to continually search for knowledge, often on community question answering platforms such as Stack Overflow. Such information sharing platforms do not exist in isolation, and part of the evidence that they exist in a broader software documentation ecosystem is the common presence of hyperlinks to other documentation resources found in forum posts. With the goal of helping to improve the information diffusion between Stack Overflow and other documentation resources, we conducted a study to answer the question of how and why documentation is referenced in Stack Overflow threads. We sampled and classified 759 links from two different domains, regular expressions and Android development, to qualitatively and quantitatively analyze the links’ context and purpose, including attribution, awareness, and recommendations. We found that links on Stack Overflow serve a wide range of distinct purposes, ranging from citation links attributing content copied into Stack Overflow, over links clarifying concepts using Wikipedia pages, to recommendations of software components and resources for background reading. This purpose spectrum has major corollaries, including our observation that links to documentation resources are a reflection of the information needs typical to a technology domain.We contribute a framework and method to analyze the context and purpose of Stack Overflow links, a public dataset of annotated links, and a description of five major observations about linking practices on Stack Overflow. Those observations include the above-mentioned purpose spectrum, its interplay with documentation resources and applications domains, and the fact that links on Stack Overflow often lack context in form of accompanying quotes or summaries. We further point to potential tool support to enhance the information diffusion between Stack Overflow and other documentation resources.Sebastian Baltes, Christoph Treude, Martin P. Robillar

A classification of crosscutting concerns and the implications for aspect-oriented refactoring

Refactoring software to apply aspect oriented solutions requires a clear understanding of what are the potential crosscutting concerns and which aspect solutions to replace them with. This process can benefit from the recognition of recurring generic concerns and their reusable aspect solutions. In this paper, we propose a classification of crosscutting concerns in sorts based on the analysis of various refactoring efforts. We discuss how sorts help concern understanding and refactoring, how they support the identification of crosscutting concerns, and how they can contribute to the evolution of aspect languages

SNIFF: A Search Engine for Java using Free-Form Queries

Abstract. Reuse of existing libraries simplifies software development efforts. However, these libraries are often complex and reusing the APIs in the libraries involves a steep learning curve. A programmer often uses a search engine such as Google to discover code snippets involving library usage to perform a common task. A problem with search engines is that they return many pages that a programmer has to manually mine to discover the desired code. Recent research efforts have tried to address this problem by automating the generation of code snippets from user queries. However, these queries need to have type information and therefore require the user to have a partial knowledge of the APIs. We propose a novel code search technique, called SNIFF, which retains the flexibility of performing code search in plain English, while obtaining a small set of relevant code snippets to perform the desired task. Our technique is based on the observation that the library methods that a user code calls are often well-documented. We use the documentation of the library methods to add plain English meaning to an otherwise undocumented user code. The annotated user code is then indexed for the purpose of free-form query search. Another novel contribution of our technique is that we take a type-based intersection of the candidate code snippets obtained from a query search to generate a set of small and highly relevant code snippets. We have implemented SNIFF for Java and have performed evaluations and user studies to demonstrate the utility of SNIFF. Our evaluations show that SNIFF performed better than most of the existing online search engines as well as related tools.