A History Querying Tool and Its Application to Detect Multi-version Refactorings

Journal of Systems and Software

Noguera

et al. 2016

• We argue for a general-purpose source code analysis tool that is aware of aspects.• We present the logic program querying tool GASR, the first such tool..• We discuss its implementation along with its library of logical predicates.• We show how it can automatically verify previously published aspectual assumptions. AbstractAspect-oriented programming languages extend existing languages with new features for supporting modularization of crosscutting concerns. These features however make existing source code analysis tools unable to reason over this code. Consequently, all code analysis efforts of aspect-oriented code that we are aware of have either built limited analysis tools or were performed manually. Given the significant complexity of building them or manual analysis, a lot of duplication of effort could have been avoided by using a general-purpose tool.To address this, in this paper we present Gasr: a source code analysis tool that reasons over AspectJ source code, which may contain metadata in the form of annotations. Gasr provides multiple kinds of analyses that are general enough such that they are reusable, tailorable and can reason over annotations. We demonstrate the use of Gasr in two ways: we first automate the recognition of previously identified aspectual source code assumptions. Second, we turn implicit assumptions into explicit assumptions through annotations and automate their verification. In both uses Gasr performs detection and verification of aspect assumptions on two well-known case studies that were manually investigated in earlier work. Gasr finds already known aspect assumptions and adds instances that had been previously overlooked.

Section: Predicatementioning

confidence: 99%

AspectJ code analysis and verification with GASR

Fabry

Journal of Systems and Software

Noguera

et al. 2016

“…qn. Here q is one of the regular path primitives provided by the QWAL library [23]: q=> skips a single node, q=> * skips zero or more nodes, and q=>+ skips one or more nodes on the path. Primitive qcurrent evaluates logic goals against the current node on the path, possibly involving one of the v 1 ...vn logic variables.…”

Section: ) Predicates Reifying Structural Relationsmentioning

confidence: 99%

“…Of the graph traversal predicates at the bottom of Table II, path/n is of special interest as it embodies the implementation of parametric regular path expressions [25], [26] in EKEKO (which we have applied in earlier work to query the history of versioned software [23]). Regular path expressions are an intuitive formalism for quantifying over the paths through a graph.…”

Section: ) Predicates Reifying Behavioral Relationsmentioning

confidence: 99%

Aspectual source code analysis with GASR

Fabry

2013 IEEE 13th International Working Conference on Source Code Analysis and Manipulation (SCAM)

Jonckers

2013

Abstract-To be able to modularize crosscutting concerns, aspects introduce new programming language features, often in a new language, with a specific syntax. These new features lead to new needs for source code analysis tools, resulting in the requirement for a general-purpose aspectual source code analysis tool. Ignoring this requirement has led to a nontrivial duplication of effort in the aspect-oriented software development community. This is because all code analysis efforts that we are aware of have either built ad-hoc analysis tools or were performed manually. In this paper we present GASR: a source code analysis tool in the tradition of logic program querying that reasons over ASPECTJ source code. By hooking into the IDE plugins for ASPECTJ, GASR provides a library of predicates that can be used to query aspectual source code. We demonstrate the use of GASR by automating the recognition of a number of previously identified aspectual source code assumptions. We then detect assumption instances on two well-known case studies that were manually investigated in the earlier work. In addition to finding the already known aspect assumptions, GASR encounters assumption instances that were overlooked before.

“…Finally, in the last three lines we retrieve the corresponding compilation unit of the added file and verify whether it is a SELENIUM script. 1 Identifying whether a compilation unit is a SELENIUM script is done purely using EKEKO. On line 2 we define three new logic variables using fresh.…”

Section: A Identifying Selenium Scriptsmentioning

confidence: 99%

“…QWAL navigates through the graph, while EKEKO is used to specify source code characteristics that have to hold in a specific version. QWALKEKO has been applied successfully to detect refactorings [1] and classify changes made to SELENIUM scripts [2]. The source code, installation instructions 2 , code 3 and video used in this paper can be found on Github.…”

Section: Introductionmentioning

confidence: 99%

Querying the History of Software Projects Using QWALKEKO

Stevens

2014 IEEE International Conference on Software Maintenance and Evolution

2014

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.