A Survey of Coverage-Based Testing Tools

Yang, Qian; Li, J. Jenny; Weiss, David M.

doi:10.1093/comjnl/bxm021

Cited by 114 publications

(66 citation statements)

References 21 publications

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“…The tools mentioned are not planned to identify TD but can be used to do that. Yang et al [26] survey coverage-based tools and compared 17 tools based on three features: code coverage measurement, coverage criteria, and automation, which includes reporting. Shah et al [27] present the consequences of exploratory testing of TD through systematic review.…”

Section: Identification Of Technical Debt Guo and Seamanmentioning

confidence: 99%

Supporting Technical Debt Cataloging with TD-Tracker Tool

Foganholi

Garcia

Eler

et al. 2015

Advances in Software Engineering

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Technical debt (TD) is an emergent area that has stimulated academic concern. Managers must have information about debt in order to balance time-to-market advantages and issues of TD. In addition, managers must have information about TD to plan payments. Development tasks such as designing, coding, and testing generate different sorts of TD, each one with specific information. Moreover, literature review pointed out a gap in identifying and accurately cataloging technical debt. It is possible to find tools that can identify technical debt, but there is not a described solution that supports cataloging all types of debt. This paper presents an approach to create an integrated catalog of technical debts from different software development tasks. The approach allows tabulating and managing TD properties in order to support managers in the decision process. It also allows managers to track TD. The approach is implemented by TD-Tracker tool, which can integrate different TD identification tools and import identified debts. We present integrations between TD-Tracker and two external tools, used to identify potential technical debts. As part of the approach, we describe how to map the relationship between TD-Tracker and the external tools. We also show how to manage external information within TD-Tracker.

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Section: Identification Of Technical Debt Guo and Seamanmentioning

confidence: 99%

Supporting Technical Debt Cataloging with TD-Tracker Tool

Foganholi

Garcia

Eler

et al. 2015

Advances in Software Engineering

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show abstract

“…Despite the needs of automation, the many problems of automating data flow testing hinder the production of tools, and most tools for structural testing target classic structural elements like statements, branches and conditions, and do not support data flow elements [YLW06].…”

Section: Automating Data Flow Testingmentioning

confidence: 99%

“…This dynamic tracking have to be implemented either by instrumenting the original code or modifying the execution environment, and can generate a significant overhead in terms of execution time [SH07]. Despite the many proposed data flow coverage techniques, there are only few research tools for data flow testing, which support a limited set of programming languages and features, as opposed to classic structural coverage, like statement and branch coverage, that are often supported directly both by the compiler and commercial tools [YLW06].…”

Section: Automating Data Flow Testingmentioning

confidence: 99%

Dynamic data-flow testing

Vivanti

2014

Companion Proceedings of the 36th International Conference on Software Engineering

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“…There are tools such as Agitar [1,45,46], JTest [27,45,46], and Symstra [45], that aim to generate thorough regression test suites. This is achieved by analysing the program, typically through a static analysis methodology [27,45], and then generating test cases to cover as much of the program as possible.…”

Section: Motivationmentioning

confidence: 99%