Sangeeta Sangeeta's Outputs (9)

Emotion Classification on Software Engineering Q&A Websites (2025)
Journal Article
Awovi Ahavi-Tete, D., & Sangeeta, S. (2025). Emotion Classification on Software Engineering Q&A Websites. e-Informatica Software Engineering Journal (EISEJ), https://doi.org/10.37190/e-Inf250104

Background: With the rapid proliferation of question-and-answer websites for software
developers like Stack Overflow, there is an increasing need to discern developers’ emotions from
their posts to assess the influence of these emotions on their pr... Read More about Emotion Classification on Software Engineering Q&A Websites.

Emotion Classification on Software Engineering Q&A Websites (2024)
Journal Article
Awovi Ahavi-Tete, D., & Sangeeta, S. (2025). Emotion Classification on Software Engineering Q&A Websites. e-Informatica Software Engineering Journal (EISEJ), 19(1), Article 250104. https://doi.org/10.37190/e-inf250104

Background: With the rapid proliferation of question-and-answer websites for software developers like Stack Overflow, there is an increasing need to discern developers’ emotions from their posts to assess the influence of these emotions on their prod... Read More about Emotion Classification on Software Engineering Q&A Websites.

Empirical Study of the Evolution of Python Questions on StackOverflow (2023)
Journal Article
Syam, G., Lal, S., Chen, T., & Sangeeta, S. (2023). Empirical Study of the Evolution of Python Questions on StackOverflow. e-Informatica Software Engineering Journal (EISEJ), 17(1), 230107. https://doi.org/10.37190/e-inf230107

Background: Python is a popular and easy-to-use programming language. It is constantly expanding, with new features and libraries being introduced daily for a broad range of applications. This dynamic expansion needs a robust support structure for de... Read More about Empirical Study of the Evolution of Python Questions on StackOverflow.

For CS Educators, by CS Educators: An Exploratory Analysis of Issues and Recommendations for Online Teaching in Computer Science (2022)
Journal Article
Lal, S., & Mourya, R. (in press). For CS Educators, by CS Educators: An Exploratory Analysis of Issues and Recommendations for Online Teaching in Computer Science. Societies, 12(4), 116. https://doi.org/10.3390/soc12040116

The COVID-19 pandemic has completely transformed the education sector. Almost all universities and colleges have had to convert their normal classroom teaching to online/remote or hybrid teaching during the COVID-19 pandemic. Online teaching has been... Read More about For CS Educators, by CS Educators: An Exploratory Analysis of Issues and Recommendations for Online Teaching in Computer Science.

An exploratory semantic analysis of logging questions (2021)
Journal Article
Gujral, H., Lal, S., & Li, H. (2022). An exploratory semantic analysis of logging questions. Journal of Software: Evolution and Process, 33(7), Article ARTN e2361. https://doi.org/10.1002/smr.2361

Logging is an integral part of software development. Software practitioners often face issues in software logging, and they post these issues on Q&A websites to take suggestions from the experts. In this study, we perform a three-level empirical anal... Read More about An exploratory semantic analysis of logging questions.

Analysis and Classification of Crime Tweets (2020)
Journal Article
Lal, S., Tiwari, L., Ranjan, R., Verma, A., Sardana, N., & Mourya, R. (2020). Analysis and Classification of Crime Tweets. Procedia Computer Science, 167, 1911-1919. https://doi.org/10.1016/j.procs.2020.03.211

Nowadays social Networking and micro-blogging sites like Twitter are very popular and millions of users are registered on these websites. The users present on these website use these websites as a platform to express their thoughts and opinions. Our... Read More about Analysis and Classification of Crime Tweets.

Developer Recommendation for Stack Exchange Software Engineering Q&A Website based on K-Means clustering and Developer Social Network Metric (2020)
Journal Article
Verma, A., Sardana, N., & Lal, S. (2020). Developer Recommendation for Stack Exchange Software Engineering Q&A Website based on K-Means clustering and Developer Social Network Metric. Procedia Computer Science, 167, 1665-1674. https://doi.org/10.1016/j.procs.2020.03.377

Nowadays Online question answering website platforms are getting popular as it allows the users to get responses from varied experts beyond their reach. Businesses use these sites for their growth and exposure. Enormous volumes of question are posted... Read More about Developer Recommendation for Stack Exchange Software Engineering Q&A Website based on K-Means clustering and Developer Social Network Metric.

Estimation of maintainability parameters for object-oriented software using hybrid neural network and class level metrics (2019)
Journal Article
Kumar, L., Lal, S., & Murthy, L. B. (2019). Estimation of maintainability parameters for object-oriented software using hybrid neural network and class level metrics. International Journal of System Assurance Engineering and Management, 10(5), 1234-1264. https://doi.org/10.1007/s13198-019-00853-2

The various software metrics proposed in the literature can be used to evaluate the quality of software systems written in object-oriented manner. These metrics are broadly categorized into two subcategories i.e., system level software metrics and cl... Read More about Estimation of maintainability parameters for object-oriented software using hybrid neural network and class level metrics.

A Three Dimensional Empirical Study of Logging Questions From Six Popular Q&A Websites (2019)
Journal Article
Gujral, H., Sharma, A., Lal, S., & Kumar, L. (2019). A Three Dimensional Empirical Study of Logging Questions From Six Popular Q&A Websites. e-Informatica Software Engineering Journal (EISEJ), 13(1), 105--139. https://doi.org/10.5277/e-Inf190104

Background: Q&A websites such as StackOverflow, Serverfault, provide an open platform for users to ask questions and to get help from experts present worldwide. These websites not only help users by answering their questions but also act as a knowled... Read More about A Three Dimensional Empirical Study of Logging Questions From Six Popular Q&A Websites.