# US 2019/0377627 A1 · Root cause analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0377627 A1 - Document ID: US20190377627A1 - Status: Published application - Kind: A1 - Application number: 16/545,096 - Filed: 2019-08-20 - Published: 2019-12-12 - Earliest claimed: 2016-08-26 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Hernan A. Cunico; Jonathan Dunne; Jeremiah O'Connor; Asima Silva - Web page: https://patentgrep.com/patent/US20190377627A1 ## CPC - G06F 11/079: {Root cause analysis, i.e. error or fault diagnosis (in a hardware test environment G06F11/22; in a software test environment G06F11/36)} - G06F 3/012: {Head tracking input arrangements} - G06F 3/013: {Eye tracking input arrangements (G06F3/015 takes precedence)} - G06F 3/023: Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes - G06F 3/033: Pointing devices displaced or positioned by the user {, e.g. mice, trackballs, pens or joysticks}; Accessories therefor (digitisers characterised by the transducing means G06F3/041) - G06F 11/0706: {the processing taking place on a specific hardware platform or in a specific software environment} - G06F 11/0787: {Storage of error reports, e.g. persistent data storage, storage using memory protection} - G06F 2203/011: Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method and system for performing a root cause analysis. A central processing unit (CPU) tracks a focal point of a user's eye gaze. The CPU correlates the focal point of the user's eye gaze to a viewing position of a display device displaying a file that includes event data being viewed by the user. The CPU identifies, as a function of the viewing position, events of interest in the event data and an amount of time that the event data is viewed by the user. The CPU outputs, as a function of a linear regression model, an interest score pertaining to one or more events of interest that were previously identified as a function of the user's eye gaze. The interest score is a probability of each identified event of interest being a root cause of a defect. ## Claims ### Claim 1 A method for performing a root cause analysis, said method comprising: tracking, by a central processing unit (CPU), a focal point of a user's eye gaze; correlating, by the CPU, the focal point of the user's eye gaze to a viewing position of a display device displaying a file that includes event data being viewed by the user; identifying, by the CPU, as a function of the viewing position, events of interest in the event data and an amount of time that the event data is viewed by the user; identifying, by the CPU, an emotive expression of the user during an amount of time the user's eye glaze is focused on the viewing position, inserting, by the CPU, a numerical value assigned to the viewing position, the amount of time, the emotive expression and text of the event data, into a linear regression model; and outputting, by the CPU, as a function of the linear regression model, an interest score pertaining to one or more events of interest that were previously identified as a function of the user's eye gaze, said interest score being a probability of each identified event of interest being a root cause of a defect. ### Claim 2 (depends on 1) The method of claim 1, said method further comprising: recording, by the CPU, recordation data of the user's eye gaze while viewing the event data of the file. ### Claim 3 (depends on 1) The method of claim 1, wherein the file including event data is selected from the group consisting of a log file, a configuration file, and source code. ### Claim 4 (depends on 1) The method of claim 1, wherein the linear regression model outputs a value of the interest score between 0-1 inclusively. ### Claim 5 (depends on 1) The method of claim 1, said method further comprising: generating a color-coded tag in the file, based on severity of the one or more events of interest. ### Claim 6 (depends on 1) The method of claim 1, said method further comprising: tagging, by the CPU, each event of interest within the file with a tag as a function of each interest score. ### Claim 7 (depends on 1) The method of claim 1, wherein the closer the emotive expression of the user is to a center of a Plutchik wheel of emotion, the higher is the probability that one or more of the identified events of interest is the root cause of the defect. ### Claim 8 A computer program product comprising: one or more computer readable hardware storage devices having computer readable program code stored therein, said program code containing instructions executable by a central processing unit (CPU) to implement a method for performing a root cause analysis, said method comprising: tracking, by the CPU, a focal point of a user's eye gaze; correlating, by the CPU, the focal point of the user's eye gaze to a viewing position of a display device displaying a file that includes event data being viewed by the user; identifying, by the CPU, as a function of the viewing position, events of interest in the event data and an amount of time that the event data is viewed by the user; identifying, by the CPU, an emotive expression of the user during an amount of time the user's eye glaze is focused on the viewing position, inserting, by the CPU, a numerical value assigned to the viewing position, the amount of time, the emotive expression and text of the event data, into a linear regression model; and outputting, by the CPU, as a function of the linear regression model, an interest score pertaining to one or more events of interest that were previously identified as a function of the user's eye gaze, said interest score being a probability of each identified event of interest being a root cause of a defect. ### Claim 9 (depends on 8) The computer program product of claim 8, said method further comprising: recording, by the CPU, recordation data of the user's eye gaze while viewing the event data of the file. ### Claim 10 (depends on 8) The computer program product of claim 8, wherein the file including event data is selected from the group consisting of a log file, a configuration fife, and source code. ### Claim 11 (depends on 8) The computer program product of claim 8, wherein the linear regression model outputs a value of the interest score between 0-1 inclusively. ### Claim 12 (depends on 8) The computer program product of claim 8, said method further comprising: generating a color-coded tag in the file, based on severity of the one or more events of interest. ### Claim 13 (depends on 8) The computer program product of claim 8, said method further comprising: tagging, by the CPU, each event of interest within the file with a tag as a function of each interest score. ### Claim 14 (depends on 8) The computer program product of claim 8, wherein the closer the emotive expression of the user is to a center of a Plutchik wheel of emotion, the higher is the probability that one or more of the identified events of interest is the root cause of the defect. ### Claim 15 A computer system, comprising: a central processing unit (CPU); a memory device coupled to the CPU; and a computer readable storage device coupled to the processor, wherein the storage device contains program code executable by the CPU via the memory device to implement a method for performing a root cause analysis, said method comprising: tracking, by the CPU, a focal point of a user's eye gaze; correlating, by the CPU, the focal point of the user's eye gaze to a viewing position of a display device displaying a file that includes event data being viewed by the user; identifying, by the CPU, as a function of the viewing position, events of interest in the event data and an amount of time that the event data is viewed by the user; identifying, by the CPU, an emotive expression of the user during an amount of time the user's eye glaze is focused on the viewing position, inserting, by the CPU, a numerical value assigned to the viewing position, the amount of time, the emotive expression and text of the event data, into a linear regression model; and outputting, by the CPU, as a function of the linear regression model, an interest score pertaining to one or more events of interest that were previously identified as a function of the user's eye gaze, said interest score being a probability of each identified event of interest being a root cause of a defect. ### Claim 16 (depends on 15) The computer system of claim 15, said method further comprising: recording, by the CPU, recordation data of the user's eye gaze while viewing the event data of the file. ### Claim 17 (depends on 15) The computer system of claim 15, wherein the file including event data is selected from the group consisting of a log file, a configuration file, and source code. ### Claim 18 (depends on 15) The computer system of claim 15, wherein the linear regression model outputs a value of the interest score between 0-1 inclusively. ### Claim 19 (depends on 15) The computer system of claim 15, said method further comprising: generating a color-coded tag in the file, based on severity of the one or more events of interest. ### Claim 20 (depends on 15) The computer system of claim 15, said method further comprising: tagging, by the CPU, each event of interest within the file with a tag as a function of each interest score.