Integrating information retrieval, execution and link analysis algorithms to improve feature location in software

Dit, Bogdan; Revelle, Meghan; Poshyvanyk, Denys

doi:10.1007/s10664-011-9194-4

Cited by 83 publications

(75 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…IR-based methods have been applied to support practical tasks. For instance, IR methods have been successfully used to support feature location (Liu et al 2007;Eaddy et al 2008;Revelle and Poshyvanyk 2009;Revelle et al 2010;Dit et al 2012a;Dit et al 2012b;, traceability link recovery (Antoniol et al 2002;Hayes et al 2006;De Lucia et al 2007;Cleland-Huang et al 2010;Oliveto et al 2010;Gethers et al 2011), and impact analysis (Antoniol et al 2000;Canfora and Cerulo 2005;Poshyvanyk et al 2009;Gethers and Poshyvanyk 2010;Gethers et al 2012). We do not discuss other applications of IR-based techniques in the context of software maintenance due to space limitations; however, interested readers are referred to (Binkley and Lawrie 2010a;Binkley and Lawrie 2010b) for such an overview.…”

Section: Conceptual Information In Softwarementioning

confidence: 99%

Integrating conceptual and logical couplings for change impact analysis in software

2012

Self Cite

View full text Add to dashboard Cite

The paper presents an approach that combines conceptual and evolutionary techniques to support change impact analysis in source code. Conceptual couplings capture the extent to which domain concepts and software artifacts are related to each other. This information is derived using Information Retrieval based analysis of textual software artifacts that are found in a single version of software (e.g., comments and identifiers in a single snapshot of source code). Evolutionary couplings capture the extent to which software artifacts were co-changed. This information is derived from analyzing patterns, relationships, and relevant information of source code changes mined from multiple versions in software repositories. The premise is that such combined methods provide improvements to the accuracy of impact sets compared to the two individual approaches.A rigorous empirical assessment on the changes of the open source systems Apache httpd, ArgoUML, iBatis, KOffice, and jEdit is also reported. The impact sets are evaluated at the file and method levels of granularity for all the software systems considered in the empirical evaluation.The results show that a combination of conceptual and evolutionary techniques, across several cutoff points and periods of history, provides statistically significant improvements in accuracy over either of the two techniques used independently. Improvements in F-measure values of up to 14%(from 3% to 17%) over the conceptual technique in ArgoUML at the method granularity, and up to 21% over the evolutionary technique in iBatis (from 9% to 30%) at the file granularity were reported.

show abstract

Section: Conceptual Information In Softwarementioning

confidence: 99%

Integrating conceptual and logical couplings for change impact analysis in software

2012

Self Cite

View full text Add to dashboard Cite

show abstract

“…An extensive survey on feature location is given by Dit et al [8]. Among the techniques proposed for this task are static and dynamic analyses [9] as well as text mining techniques [10], which is what we applied here. Text mining has been used for feature location, e.g., in [11] where features are located based on natural language documents.…”

Section: Related Workmentioning

confidence: 99%

“…Second, we present unused methods to the system expert and identify one use case expressing an unused feature manually for parameter estimation 9 (see Section III).…”

Section: B Study Executionmentioning

confidence: 99%

Which Features Do My Users (Not) Use?

Eder

Femmer

Hauptmann

et al. 2014

2014 IEEE International Conference on Software Maintenance and Evolution

View full text Add to dashboard Cite

Abstract-Maintenance of unused features leads to unnecessary costs. Therefore, identifying unused features can help product owners to prioritize maintenance efforts. We present a tool that employs dynamic analyses and text mining techniques to identify use case documents describing unused features to approximate unnecessary features. We report on a preliminary study of an industrial business information system over the course of one year quantifying unused features and measuring the performance of the approach. It indicates the relevance of the problem and the capability of the presented approach to detect unused features.

show abstract

“…This section presents the details of reproducing an existing feature location technique (FLT) [23] using the CDK and the CL proposed in this paper. We describe the original technique, the details of reproducing it in TraceLab, and compare the results of the original and reproduced technique.…”

Section: Reproducing Existing Experiments and Evaluating New Ideamentioning

confidence: 99%

“…The FLT introduced by Dit et al [23], called IR LSI Dyn bin WM (or IRDynWM for short), was reproduced in 2 http://coest.org/coest-projects/projects/semeru/wiki TraceLab using a subset of components from the proposed CL. The high-level idea behind IRDynWM is to (i) identify a subset of methods from an execution trace with high or low rankings using advanced web mining analysis algorithms and to (ii) remove those methods from the results produced by the SITIR approach [35].…”

Section: A Reproducing a Feature Location Techniquementioning

confidence: 99%

Supporting and Accelerating Reproducible Research in Software Maintenance Using TraceLab Component Library

Dit

Moritz

Linares‐Vásquez

et al. 2013

2013 IEEE International Conference on Software Maintenance

Self Cite

View full text Add to dashboard Cite

Abstract-Research studies in software maintenance are notoriously hard to reproduce due to lack of datasets, tools, implementation details (e.g., parameter values, environmental settings) and other factors. The progress in the field is hindered by the challenge of comparing new techniques against existing ones, as researchers have to devote a lot of their resources to the tedious and error-prone process of reproducing previously introduced approaches. In this paper, we address the problem of experiment reproducibility in software maintenance and provide a long term solution towards ensuring that future experiments will be reproducible and extensible. We conducted a mapping study of a number of representative maintenance techniques and approaches and implemented them as a library of experiments and components that we make publicly available with TraceLab, called the Component Library. The goal of these experiments and components is to create a body of actionable knowledge that would (i) facilitate future research and would (ii) allow the research community to contribute to it as well. In addition, to illustrate the process of using and adapting these techniques, we present an example of creating new techniques based on existing ones, which produce improved results.

show abstract

Integrating information retrieval, execution and link analysis algorithms to improve feature location in software

Cited by 83 publications

References 56 publications

Integrating conceptual and logical couplings for change impact analysis in software

Integrating conceptual and logical couplings for change impact analysis in software

Which Features Do My Users (Not) Use?

Supporting and Accelerating Reproducible Research in Software Maintenance Using TraceLab Component Library

Contact Info

Product

Resources

About