How much does unused code matter for maintenance?

Eder,; Junker,; Jurgens,; Hauptmann,; Vaas,; Prommer,

doi:10.1109/icse.2012.6227109

Cited by 28 publications

(20 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We expect this effect to be small, since developers told us there are no such mechanisms. The collection procedure itself has shown to be working with sufficient accuracy in earlier research [9,8].…”

Section: Threats To Validitymentioning

confidence: 95%

See 1 more Smart Citation

Selecting manual regression test cases automatically using trace link recovery and change coverage

Eder¹,

Hauptmann²,

Junker³

et al. 2014

Proceedings of the 9th International Workshop on Automation of Software Test

Self Cite

View full text Add to dashboard Cite

Regression tests ensure that existing functionality is not impaired by changes to an existing software system. However, executing complete test suites often takes much time. Therefore, a subset of tests has to be found that is sufficient to validate whether the system under test is still valid after it has been changed. This test case selection is especially important if regression tests are executed manually, since manual execution is time intensive and costly.To select manual test cases, many regression testing techniques exist that aim on achieving coverage of changed or even new code. Many of these techniques base on coverage data from prior test runs or logical properties such as annotated pre and post conditions in the source code. However, coverage information becomes outdated if a system is changed extensively. Also annotated logical properties are often not available in industrial software systems.We present an approach for test selection that is based on static analyses of the test suite and the system's source code. We combine trace link recovery using latent semantic indexing with the metric change coverage, which assesses the coverage of source code changes. The proposed approach works automatically without the need to execute tests beforehand or annotate source code. Furthermore, we present a first evaluation of the approach.

show abstract

Section: Threats To Validitymentioning

confidence: 95%

“…For calculating change coverage (see the following section), we use profiling data from an ephemeral profiler [21] as in our earlier work [8,9]. The profiler does not record how often a method was called, just whether it was called during a fixed time interval.…”

Section: Starting Pointmentioning

confidence: 99%

Selecting manual regression test cases automatically using trace link recovery and change coverage

Eder¹,

Hauptmann²,

Junker³

et al. 2014

Proceedings of the 9th International Workshop on Automation of Software Test

Self Cite

View full text Add to dashboard Cite

show abstract

“…‚ Usage data collected by an ephemeral profiler 2 [19]. The resulting log files list the executed methods 3 . ‚ Source code of the software system 4 .…”

Section: Inputmentioning

confidence: 99%

“…This could produce less unused methods, which leads to less unused features. However, this profiler was used for several years in the environment under consideration (see [3], [21], [22]) without significant or visible errors. Therefore, we are confident that the errors introduced are small, if existent.…”

Section: E Threats To Validitymentioning

confidence: 99%

See 1 more Smart Citation

Which Features Do My Users (Not) Use?

Eder

Femmer

Hauptmann

et al. 2014

2014 IEEE International Conference on Software Maintenance and Evolution

Self Cite

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

Explainable and Transparent AI and Multi-Agent Systems

2021

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Enterprise Resource Planning (ERP) software is used by businesses and extended via customisation. Automated custom code analysis and migration is a critical issue at ERP release upgrade times. Despite research advances, automated code analysis and transformation require a huge amount of manual work related to parser adaptation, rule extension and post-processing. These operations become unmanageable if the frequency of updates increases from yearly to monthly intervals. This article describes how the process of custom code analysis to custom code transformation can be automated in an explainable way. We develop an aggregate taxonomy for explainability and analyse the requirements based on roles. We explain in which steps on the new code migration process machine learning is used. Further, we analyse additional effort needed to make the new way of code migration explainable to different stakeholders.

show abstract

How much does unused code matter for maintenance?

Cited by 28 publications

References 17 publications

Selecting manual regression test cases automatically using trace link recovery and change coverage

Selecting manual regression test cases automatically using trace link recovery and change coverage

Which Features Do My Users (Not) Use?

Explainable and Transparent AI and Multi-Agent Systems

Contact Info

Product

Resources

About