What recommendation systems for software engineering recommend: A systematic literature review

Gašparić, Marko; Janes, Andrea

doi:10.1016/j.jss.2015.11.036

Cited by 61 publications

(21 citation statements)

References 18 publications

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“…Could it be that some researchers wait to find an algorithm whose experimentation is acceptable before publishing, a tendency known as publication bias? This bias has already been documented in systematic reviews on recommender systems (Gasparic & Janes, 2016).…”

Section: Discussionmentioning

confidence: 71%

Recommender systems to support learners’ Agency in a Learning Context: a systematic review

Deschênes

2020

Int J Educ Technol High Educ

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Recommender systems for technology-enhanced learning are examined in relation to learners’ agency, that is, their ability to define and pursue learning goals. These systems make it easier for learners to access resources, including peers with whom to learn and experts from whom to learn. In this systematic review of the literature, we apply an Evidence for Policy and Practice Information (EPPI) approach to examine the context in which recommenders are used, the manners in which they are evaluated and the results of those evaluations. We use three databases (two in education and one in applied computer science) and retained articles published therein between 2008 and 2018. Fifty-six articles meeting the requirements for inclusion are analyzed to identify their approach (content-based, collaborative filtering, hybrid, other) and the experiment settings (accuracy, user satisfaction or learning performance), as well as to examine the results and the manner in which they were presented. The results of the majority of the experiments were positive. Finally, given the results introduced in this systematic review, we identify future research questions.

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Section: Discussionmentioning

confidence: 71%

Recommender systems to support learners’ Agency in a Learning Context: a systematic review

Deschênes

2020

Int J Educ Technol High Educ

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“…We used the SLR approach as a major tool in previous studies [48]- [50], as it methodically supports primary assessments [45] and for which we transcribed SLR protocols (taken from [49]) to formulate a strategic plan for the present work. According to Kitchenham and others [25], [45], [51]- [54], the SLR process comprises three main stages: planning, conducting and reporting, we have identified 6 critical communication and coordination challenges (CCCC) and 75 practices from a sample of 164 papers.…”

Section: Stage-1: Identification Of Communication and Coordination Chmentioning

confidence: 99%

An Evaluation Framework for Communication and Coordination Processes in Offshore Software Development Outsourcing Relationship: Using Fuzzy Methods

et al. 2019

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“…In a recent literature review on recommendation systems for software engineering [11], the authors highlighted the gap that exists on the lack of decision support systems for software testing. Similarly, based on our limited search to nd relevant papers on visualization and decision support for software testing, many papers were found to be still at a stage of proposing and/or developing a theory.…”

Section: Discussionmentioning

confidence: 99%

Decision making and visualizations based on test results

Strandberg¹,

Afzal

Sundmark

2018

Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

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Background: Testing is one of the main methods for quality assurance in the development of embedded software, as well as in software engineering in general. Consequently, test results (and how they are reported and visualized) may substantially in uence business decisions in software-intensive organizations. Aims: This case study examines the role of test results from automated nightly software testing and the visualizations for decision making they enable at an embedded systems company in Sweden. In particular, we want to identify the use of the visualizations for supporting decisions from three aspects: in daily work, at feature branch merge, and at release time. Method: We conducted an embedded case study with multiple units of analysis by conducting interviews, questionnaires, using archival data and participant observations. Results: Several visualizations and reports built on top of the test results database are utilized in supporting daily work, merging a feature branch to the master and at release time. Some important visualizations are: lists of failing test cases, easy access to log les, and heatmap trend plots. The industrial practitioners perceived the visualizations and reporting as valuable, however they also mentioned several areas of improvement such as better ways of visualizing test coverage in a functional area as well as better navigation between di erent views. Conclusions: We conclude that visualizations of test results are a vital decision making tool for a variety of roles and tasks in embedded software development, however the visualizations need to be continuously improved to keep their value for its stakeholders. CCS CONCEPTS • Software and its engineering → Software creation and management; Software testing and debugging; Empirical software validation;

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What recommendation systems for software engineering recommend: A systematic literature review

Cited by 61 publications

References 18 publications

Recommender systems to support learners’ Agency in a Learning Context: a systematic review

Recommender systems to support learners’ Agency in a Learning Context: a systematic review

An Evaluation Framework for Communication and Coordination Processes in Offshore Software Development Outsourcing Relationship: Using Fuzzy Methods

Decision making and visualizations based on test results

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