Abstract

Software engineers work under strict constraints, balancing a complex, multi-phase development process on top of user support and professional development. Despite their best efforts, software engineers experience human errors, which manifest as software defects. While some defects are simple bugs, others can be costly security vulnerabilities. Practices such as defect tracking and vulnerability disclosure help software engineers reflect on the outcomes of their human errors (i.e. software failures), and even the faults that led to those failures, but not the underlying human behaviors. While human error theory from psychology research has been studied and applied to medical, industrial, and aviation accidents, researchers are only beginning to systematically reflect on software engineers' human errors. Some software engineering research has used human error theories from psychology to help developers identify and organize their human errors (mistakes) during requirements engineering activities, but developers need an improved and systematic way to reflect on their human errors during other phases of software development. The goal of this dissertation is to help software engineers confront and reflect on their human errors by creating a process to document, organize, and analyze human errors. To that end, our research comprises three phases: (1) systematization (i.e. identification and taxonomization) of software engineers' human errors from literature and development artifacts into a Taxonomy of Human Errors in Software Engineering (T.H.E.S.E.), (2) evaluation and refinement of T.H.E.S.E. based on software engineers' perceptions and natural language insights, and (3) creation of a human error informed micro post-mortem process and the Human Error Reflection Engine (H.E.R.E.), a proof-of-concept GitHub workflow facilitating human error reflection. In demonstrating the utility of T.H.E.S.E. and our micro post-mortem process, the software development community will be closer to inculcating the wisdom of historical developer human errors, enabling them to engineer higher quality and more secure software.

Library of Congress Subject Headings

Software failures--Evaluation; Errors--Classification; Software engineering--Management

Publication Date

10-2023

Document Type

Dissertation

Student Type

Graduate

Degree Name

Computing and Information Sciences (Ph.D.)

Department, Program, or Center

Computing and Information Sciences Ph.D, Department of

College

Golisano College of Computing and Information Sciences

Advisor

Andrew Meneely

Advisor/Committee Member

Daniel Krutz

Advisor/Committee Member

Mehdi Mirakhorli

Campus

RIT – Main Campus

Plan Codes

COMPIS-PHD

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