Evaluating a Conceptual Framework for Supporting Technical Debt Management in Testing Activities - A Feasibility Study
Resumo
Context: Test-related technical debt (TRTD) refers to debt items that affect software testing activities, compromising their quality. Having information on indicators of their presence, causes, effects, and preventive practices can support the management of TRTD items. Although several works have investigated TD indicators, causes, effects, and prevention, there is a need to investigate how to use this information for supporting the management of debt items in the context of testing activities. Aims: This work (i) presents an updated version of a conceptual framework that organizes a set of indicators, causes, effects, and preventive practices of TRTD and (ii) evaluates it with respect to its ease of use, usefulness, and possible future use. Method: We analyzed 46 answers given to a global family of industrial surveys to assemble a conceptual framework for TRTD management and evaluate it by applying the technology acceptance model (TAM) in a feasibility study with 95 participants. Results: The conceptual framework can be useful for supporting the management of TRTD items, as pointed out by 89% of the participants. Most of the participants also indicated that they would gain productivity, performance, agility, and effectiveness by using the conceptual framework. Conclusion: Results indicate that the data embedded into the conceptual framework and the conceptual framework itself are promising to support the management of TRTD items.
Palavras-chave:
Technical debt effects, Technical debt causes, Test-related technical debt, Technical debt prevention
Publicado
03/10/2022
Como Citar
ROCHA, Verusca; FREIRE, Sávio; MENDONÇA, Manoel; SPÍNOLA, Rodrigo.
Evaluating a Conceptual Framework for Supporting Technical Debt Management in Testing Activities - A Feasibility Study. In: SIMPÓSIO BRASILEIRO DE TESTES DE SOFTWARE SISTEMÁTICO E AUTOMATIZADO (SAST), 7. , 2022, Uberlândia.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 69–78.