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Toward Fixing Bad Practices in Software Engineering Hiring Process.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Toward Fixing Bad Practices in Software Engineering Hiring Process./
作者:	Behroozi, Mahnaz.
面頁冊數:	1 online resource (186 pages)
附註:	Source: Dissertations Abstracts International, Volume: 83-11, Section: B.
Contained By:	Dissertations Abstracts International83-11B.
標題:	Problem solving. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29100680click for full text (PQDT)
ISBN:	9798426885936

Toward Fixing Bad Practices in Software Engineering Hiring Process.
Behroozi, Mahnaz.

Toward Fixing Bad Practices in Software Engineering Hiring Process. - 1 online resource (186 pages)

Source: Dissertations Abstracts International, Volume: 83-11, Section: B.

Thesis (Ph.D.)--North Carolina State University, 2022.

Includes bibliographical references

A technical interview for software engineering roles consists of one or more stages within the interview life cycle. It begins with an initial screening of the candidate, usually conducted over the phone or through an online coding platform, such as CoderPad, Skype Interviews, and interviewing.io. Depending on their performance, the candidate may be invited for an on-site visit. This on-site visit consists of a series of one-on-one interviews (each 45 minutes to an hour, over a period of half a day to several days) with engineers, and sometimes managers. The interviews primarily focus on technical coding or algorithms, either on the whiteboard or using a simple text editor on a computer. During these sessions, candidates write code while thinking aloud as they work towards a solution, under the watchful eye of the interviewer(s). In other words, technical interviews are primarily a test of the candidates' problem-solving or "analytical ability."Despite the intended usage of these technical interviews, they can be notoriously unreliable method of assessing candidates' qualifications. Identity-related aspects of a technical interview candidate (e.g., race, gender, disability, age) can affect interviewers' behavior and the interview outcome. However, discrimination might not necessarily be the result of explicit bias on the interviewers' part. An implicit bias may take place due to hidden factors in the existing technical interviews' nature (e.g., breaking candidates' thought process by asking them to think aloud or interrupting them.) These hidden factors may prevent certain candidates from performing properly despite their qualifications.The thesis of this dissertation is that the presence of an interviewer can disrupt a candidate's problem-solving ability during a technical interview. Enhancing a candidate's privacy can improve their problem-solving performance by reducing the stress arising from a social-evaluative threat.This dissertation intends to provide a top-down framework that first studies the software engineering hiring process as a set of stages. It then focuses on identifying the problems in the most critical phase of the hiring process-the technical interviews. It further explores the barriers-mostly cognitive-related-associated with technical interviews that can form implicit bias against certain candidates. The ultimate goal of the dissertation is to reduce these barriers and promote fairness and inclusion in software engineering hiring practices.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798426885936Subjects--Topical Terms:

516855
Problem solving.
Index Terms--Genre/Form:

542853
Electronic books.

Toward Fixing Bad Practices in Software Engineering Hiring Process.
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520 $a A technical interview for software engineering roles consists of one or more stages within the interview life cycle. It begins with an initial screening of the candidate, usually conducted over the phone or through an online coding platform, such as CoderPad, Skype Interviews, and interviewing.io. Depending on their performance, the candidate may be invited for an on-site visit. This on-site visit consists of a series of one-on-one interviews (each 45 minutes to an hour, over a period of half a day to several days) with engineers, and sometimes managers. The interviews primarily focus on technical coding or algorithms, either on the whiteboard or using a simple text editor on a computer. During these sessions, candidates write code while thinking aloud as they work towards a solution, under the watchful eye of the interviewer(s). In other words, technical interviews are primarily a test of the candidates' problem-solving or "analytical ability."Despite the intended usage of these technical interviews, they can be notoriously unreliable method of assessing candidates' qualifications. Identity-related aspects of a technical interview candidate (e.g., race, gender, disability, age) can affect interviewers' behavior and the interview outcome. However, discrimination might not necessarily be the result of explicit bias on the interviewers' part. An implicit bias may take place due to hidden factors in the existing technical interviews' nature (e.g., breaking candidates' thought process by asking them to think aloud or interrupting them.) These hidden factors may prevent certain candidates from performing properly despite their qualifications.The thesis of this dissertation is that the presence of an interviewer can disrupt a candidate's problem-solving ability during a technical interview. Enhancing a candidate's privacy can improve their problem-solving performance by reducing the stress arising from a social-evaluative threat.This dissertation intends to provide a top-down framework that first studies the software engineering hiring process as a set of stages. It then focuses on identifying the problems in the most critical phase of the hiring process-the technical interviews. It further explores the barriers-mostly cognitive-related-associated with technical interviews that can form implicit bias against certain candidates. The ultimate goal of the dissertation is to reduce these barriers and promote fairness and inclusion in software engineering hiring practices.
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