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2018

Chowdhury, S., Borle, S., Romansky, S., Hindle, Abram

Software energy consumption is a performance related non-functional requirement that complicates building software on mobile devices today. Energy hogging applications (apps) are a liability to both the end-user and software developer. Measuring software energy consumption is non-trivial,...

2012

Davies, J., German, D.M., Godfrey, M.W., Hindle, Abram

Deployed software systems are typically composed of many pieces, not all of which may have been created by the main development team. Often, the provenance of included components—such as external libraries or cloned source code—is not clearly stated, and this uncertainty can introduce technical...

2017

Aggarwal, K., Timbers, F., Rutgers, T., Hindle, Abram, Stroulia, E., Greiner, R.

Bug deduplication, ie, recognizing bug reports that refer to the same problem, is a challenging task in the software-engineering life cycle. Researchers have proposed several methods primarily relying on information-retrieval techniques. Our work motivated by the intuition that domain knowledge...

2020

Bangash, A., Sahar, H., Hindle, Abram, Ali, K.

Researchers in empirical software engineering often make claims based on observable data such as defect reports. Unfortunately, in many cases, these claims are generalized beyond the data sets that have been evaluated. Will the researcher’s conclusions hold a year from now for the same software...

2013

Hindle, Abram, Ernst, N.A., Godfrey, M.W., Mylopoulos, J.

Software repositories provide a deluge of software artifacts to analyze. Researchers have attempted to summarize, categorize, and relate these artifacts by using semi-unsupervised machine-learning algorithms, such as Latent Dirichlet Allocation (LDA). LDA is used for concept and topic analysis to...

2014

Hindle, Abram, Bird, C., Zimmermann, T., Nagappan, N.

Large organizations like Microsoft tend to rely on formal requirements documentation in order to specify and design the software products that they develop. These documents are meant to be tightly coupled with the actual implementation of the features they describe. In this paper we evaluate the...

2013

Hindle, Abram

Power consumption is becoming more and more important with the increased popularity of smart-phones, tablets and laptops. The threat of reducing a customer’s battery-life now hangs over the software developer, who now asks, “will this next change be the one that causes my software to drain a...

2018

McIntosh, A., Hassan, S., Hindle, Abram

Machine learning is a popular method of learning functions from data to represent and to classify sensor inputs, multimedia, emails, and calendar events. Smartphone applications have been integrating more and more intelligence in the form of machine learning. Machine learning functionality now...

2023

Sun, W., Kalmady, S.V., Sepehrvand, N., Salimi, A., Nademi, Y., Bainey, K., Ezekowitz, J.A., Greiner, R., Hindle, Abram, McAlister, F.A., Sandhu, R.K., Kaul, P.

The feasibility and value of linking electrocardiogram (ECG) data to longitudinal population-level administrative health data to facilitate the development of a learning healthcare system has not been fully explored. We developed ECG-based machine learning models to predict risk of mortality...

2021

Viggiato, M., Lin, D., Hindle, Abram, Bezemer, C.P.

Sentiment analysis is a popular technique to identify the sentiment of a piece of text. Several different domains have been targeted by sentiment analysis research, such as Twitter, movie reviews, and mobile app reviews. Although several techniques have been proposed, the performance of current...