Querying the History of Software Projects Using QWALKEKO

Abstract

Abstract-We present the QWALKEKO meta-programming library for Clojure that enables querying the history of versioned software projects in a declarative manner. Unique to this library is its support for regular path expressions within history queries. Regular path expressions are akin to regular expressions, except that they match a sequence of successive snapshots of a software project along which user-specified logic conditions must hold. Such logic conditions can concern the source code within a snapshot, versioning information associated with the snapshot, as well as patterns of source code changes with respect to other snapshots. We have successfully used the resulting multi-faceted queries to detect refactorings in project histories. In this paper, we discuss how applicative logic meta-programming enabled combining the heterogenous components of QWALKEKO into a uniform whole. We focus on the applicative logic interface to a new implementation of a well-known change distilling algorithm. We use the problem of detecting and categorizing changes made to SELENIUM-based test scripts for illustration purposes.

Githru: Visual Analytics for Understanding Software Development History Through Git Metadata Analysis

“…Bird and Kalliamvakou provided a set of recommendations for researchers on how to approach Git and GitHub data [16,43]. Stevens [65] presented the QWALKEKO metaprogramming library, which enables querying the history of versioned software projects in a declarative manner. Barik [13] proposed Commit Bubbles, which supports developers in constructing commit histories with their coding workflows.…”

[Engineering Paper] Graal: The Quest for Source Code Knowledge

“…The first category includes tools like Gitana [18], CVS-AnalY [19], Churrasco [20], Moose [21], SPO [22], Met-ricMiner [23], SonarQube [12], QWALKEKO [24] and Codacy. However, when compared to Graal, the project data they cover is limited [19], [21]- [24] (or do not include code information [18]) and they do not provide an easy way to extract their data [12]. Furthermore, these tools do not rely on schema-less data structures as Graal does, thus hampering their extensions with new project data by non-technical users.…”

Querying distilled code changes to extract executable transformations

“…In summary, existing approaches either do not include low-level source code changes, or do not feature a dedicated query language. In this paper, we have presented such a query language and have integrated it in the history querying tool QwalKeko by Stevens and De Roover (2014).…”

“…A change distilling algorithm (Fluri et al 2007;Chawathe et al 1996;Palix et al 2015;Stevens and De Roover 2014) can be used to obtain more finegrained information about the differences between two revisions. Such an algorithm takes two Abstract Syntax Trees (ASTs) as input, called the source AST and the target AST respectively.…”