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Crowdsourced Software Engineering (CSE) offers outsourcing work to software practitioners by leveraging a global online workforce. However, these software practitioners struggle to identify suitable tasks due to the variety of options…
Recommender systems for software engineering (RSSE) play a crucial role in automating development tasks by providing relevant suggestions according to the developer's context. However, they suffer from the so-called popularity bias, i.e.,…
In today's world, we need to ensure that AI systems are fair and unbiased. Our study looked at tools designed to test the fairness of software to see if they are practical and easy for software developers to use. We found that while some…
With the increasing deployment of machine learning models in many socially sensitive tasks, there is a growing demand for reliable and trustworthy predictions. One way to accomplish these requirements is to allow a model to abstain from…
Regression testing is an essential activity to assure that software code changes do not adversely affect existing functionalities. With the wide adoption of Continuous Integration (CI) in software projects, which increases the frequency of…
Recommender systems often rely on models which are trained to maximize accuracy in predicting user preferences. When the systems are deployed, these models determine the availability of content and information to different users. The gap…
Software testing is a complex, intellectual activity based (at least) on analysis, reasoning, decision making, abstraction and collaboration performed in a highly demanding environment. Naturally, it uses and allocates multiple cognitive…
Recommendation system is a type of information filtering systems that recommend various objects from a vast variety and quantity of items which are of the user interest. This results in guiding an individual in personalized way to…
Recent studies have shown that recommendation systems commonly suffer from popularity bias. Popularity bias refers to the problem that popular items (i.e., frequently rated items) are recommended frequently while less popular items are…
Personality traits influence most, if not all, of the human activities, from those as natural as the way people walk, talk, dress and write to those most complex as the way they interact with others. Most importantly, personality influences…
Peer reviews, evaluations, and selections are a fundamental aspect of modern science. Funding bodies the world over employ experts to review and select the best proposals from those submitted for funding. The problem of peer selection,…
Analysing and improving productivity has been one of the main goals of software engineering research since its beginnings. A plethora of studies has been conducted on various factors that resulted in several models for analysis and…
Based on decision trees, many fields have arguably made tremendous progress in recent years. In simple words, decision trees use the strategy of "divide-and-conquer" to divide the complex problem on the dependency between input features and…
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the performance of collaborative filtering depends on the number of…
Large-scale e-commerce sites can collect and analyze a large number of user preferences and behaviors, and thus can recommend highly trusted products to users. However, it is very difficult for individuals or non-corporate groups to obtain…
We detail some lessons learned while designing and testing a decision-theoretic advising support tool for undergraduates at a large state university. Between 2009 and 2011 we conducted two surveys of over 500 students in multiple majors and…
In recent years, many studies have applied wearable devices to capture psychophysiological data from software developers. However, the current literature lacks investigations that classify the studies and point out gaps to be explored. This…
The choice of the tools and programming technologies for information systems creation is relevant. For every projected system, it is necessary to define a number of criteria for development environment, used libraries and technologies. The…
Decision-making is a cognitively intensive task that requires synthesizing relevant information from multiple unstructured sources, weighing competing factors, and incorporating subjective user preferences. Existing methods, including large…
Recommendation is the task of ranking items (e.g. movies or products) according to individual user needs. Current systems rely on collaborative filtering and content-based techniques, which both require structured training data. We propose…