Identifying, categorizing and mitigating threats to validity in software engineering secondary studies

Ampatzoglou, Apostolos; Bibi, Stamatia; Avgeriou, Paris; Verbeek, Marijn; Chatzigeorgiou, Alexander

doi:10.1016/j.infsof.2018.10.006

Cited by 172 publications

(160 citation statements)

References 39 publications

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“…The use of such systematised guidelines for conducting the current report synthesis has been considered helpful to deal with validity concerns. Validity concerns have been gaining increasing importance associated with the growth of systematic reviews in the literature [30]. Following the study from Zhou et al [31], the main threats to validity were considered and mitigation actions included to minimise their effect, which is reflected in the specified research exclusion criteria.…”

Section: Methodsmentioning

confidence: 99%

A Review of the Relation between Household Indoor Temperature and Health Outcomes

2020

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This paper provides a review of research that addresses the relationship between indoor temperatures and health outcomes, taking into consideration studies that focus heat or cold exposure within the household context. It aims to extend previous research by considering both indoor temperatures from existing housing, and empirical studies that focus on energy efficiency measures and subsequent health impacts. To achieve this aim, a literature review was undertaken, combining engineering and health databases. The review established that, overall, inadequate indoor temperatures are associated with poor health status, whereas energy efficiency measures have been associated to improved indoor temperatures and occupant’s health namely regarding cardiovascular, respiratory and mental health disorders. These health conditions are among the most prevalent non-communicable diseases (NCD). The review also highlighted the need for more empirical studies with an extended timeframe to deal with climate change challenges. It underlined the potential advantages of the convergence between health and energy efficiency studies, for better modelling and planning.

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Section: Methodsmentioning

confidence: 99%

A Review of the Relation between Household Indoor Temperature and Health Outcomes

2020

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“…171 secondary studies 2018 [58] A tertiary study on technical debt 13 secondary studies 2018 [59] Identifying, categorizing and mitigating threats to validity in SE secondary studies 165 secondary studies 2018 [60] A tertiary study on model-based testing areas, tools and challenges 10 secondary studies 2018 [61] (2) Reasons for exclusions: (1) The list of secondary studies was not available. (2) Download of paper is not available.…”

Section: Survey On the Application Of Secondary Studies In Research Pmentioning

confidence: 99%

Secondary studies in the academic context: A systematic mapping and survey

Felizardo

Souza

Vijaykumar

et al. 2020

Journal of Systems and Software

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Context: Several researchers have reported their experiences in applying secondary studies (Systematic Literature Reviews-SLRs and Systematic Mappings-SMs) in Software Engineering (SE). However, there is still a lack of studies discussing the value of performing secondary studies in an academic context. Goal: The main goal of this study is to provide an overview on the use of secondary studies in an academic context. Method: Two empirical research methods were used. Initially, we conducted an SM to identify the available and relevant studies on the use of secondary studies as a research methodology for conducting SE research projects. Secondly,

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“…e rest of the authors thoroughly reviewed, improved, and agreed upon the DEF before properly starting the data extraction process. e proper use of the DEF facilitates a detailed, systematic, explicit, and consistent approach to conduct the data extraction process of an SLR study [60,61].…”

Section: Data Extraction Processmentioning

confidence: 99%

“…In this study, we have considered the five most frequently reported validity threats of software engineering research [60,86]. ese validity threats include descriptive validity, interpretive validity, theoretical validity, generalizability, and reliability.…”

Section: Validity Threatsmentioning

confidence: 99%

A Systematic Literature Review on Using Machine Learning Algorithms for Software Requirements Identification on Stack Overflow

Ahmad

Feng

Khan

et al. 2020

Security and Communication Networks

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Context. The improvements made in the last couple of decades in the requirements engineering (RE) processes and methods have witnessed a rapid rise in effectively using diverse machine learning (ML) techniques to resolve several multifaceted RE issues. One such challenging issue is the effective identification and classification of the software requirements on Stack Overflow (SO) for building quality systems. The appropriateness of ML-based techniques to tackle this issue has revealed quite substantial results, much effective than those produced by the usual available natural language processing (NLP) techniques. Nonetheless, a complete, systematic, and detailed comprehension of these ML based techniques is considerably scarce. Objective. To identify or recognize and classify the kinds of ML algorithms used for software requirements identification primarily on SO. Method. This paper reports a systematic literature review (SLR) collecting empirical evidence published up to May 2020. Results. This SLR study found 2,484 published papers related to RE and SO. The data extraction process of the SLR showed that (1) Latent Dirichlet Allocation (LDA) topic modeling is among the widely used ML algorithm in the selected studies and (2) precision and recall are amongst the most commonly utilized evaluation methods for measuring the performance of these ML algorithms. Conclusion. Our SLR study revealed that while ML algorithms have phenomenal capabilities of identifying the software requirements on SO, they still are confronted with various open problems/issues that will eventually limit their practical applications and performances. Our SLR study calls for the need of close collaboration venture between the RE and ML communities/researchers to handle the open issues confronted in the development of some real world machine learning-based quality systems.

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Identifying, categorizing and mitigating threats to validity in software engineering secondary studies

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Cited by 172 publications

References 39 publications

A Review of the Relation between Household Indoor Temperature and Health Outcomes

A Review of the Relation between Household Indoor Temperature and Health Outcomes

Secondary studies in the academic context: A systematic mapping and survey

A Systematic Literature Review on Using Machine Learning Algorithms for Software Requirements Identification on Stack Overflow

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