# US 10,120,747 B2 · 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 10,120,747 B2 - Document ID: US10120747B2 - Status: Granted - Kind: B2 - Application number: 15/248,140 - Filed: 2016-08-26 - Published: 2018-03-01 - Granted: 2018-11-06 - 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/US10120747B2 ## 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 Systems, methods and tools for performing a root cause analysis and improvements to the root cause detection by changing the way analysts and troubleshooters interact with the error reporting files to detect injection points that indicate the root cause of a system error. The systems, methods and tools record the observable behavior of users as the users review files to identify behavioral clues of the user to infer a level of interest in sections of the files being viewed. The systems identify correlations between user behavior and emotive expression to calculate a probability of event data being the root cause of an error. The systems may manually or automatically generate one or more tags in the reviewed file for each of the sections of the file that has a probability of being a root cause of a defect and the tags may vary as a function of the probability. ## Claims ### Claim 1 A computer system, comprising: a central processing unit (CPU); a memory device coupled to the CPU; a biometric input 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: opening, by the CPU, a file comprising event data; recording, by the CPU, a user's observable behavior viewing the event data of the file recorded via the biometric input device, wherein the user's observable behavior includes the user's eye gaze; identifying, by the CPU, a presence of one or more events of interest as a function of the user's observable behavior while viewing the event data of the file; calculating, by the CPU, an interest score for each of the identified events of interest, wherein the interest score is a probability of each of the identified events of interest being a root cause of a defect; and tagging, by the CPU, each of the events of interest within the file with a tag as a function of each calculated interest score; wherein said identifying comprises: tracking, by the CPU, a focal point of the 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 the file; identifying, by the CPU, as a function of the viewing position, the event data being viewed and an amount of time that the event data is viewed by the user; and further identifying, by the CPU, an emotive expression of the user during an amount of time focused on the viewing position, and wherein said calculating comprises: assigning, by the CPU, a numerical value to the viewing position, amount of time, emotive expression and event data viewed by the user; and inserting, by the CPU, the numerical value assigned to the viewing position, amount of time, 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, a value of the interest score. ### Claim 2 (depends on 1) The system of claim 1, wherein the file comprising event data is selected from the group consisting of a log file, configuration file and source code. ### Claim 3 (depends on 1) The system of claim 1, wherein said tagging the file comprises automatically generating a color coded tag in the file, and wherein the color coded tag generated is based on severity of the events of interest. ### Claim 4 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: opening, by the CPU, a file comprising event data; recording, by the CPU, a recordation of the user's observable behavior while viewing the event data of the file, wherein the user's observable behavior includes the user's eye gaze; identifying, by the CPU, a presence of one or more events of interest as a function of the user's observable behavior while viewing the event data of the file; calculating, by the CPU, an interest score for each of the identified events of interest as a function of the user's observable behavior, wherein the interest score is a probability of the identified events of interest being a root cause of a defect; and tagging, by the CPU, each of the events of interest within the file with a tag as a function of each calculated interest score; wherein said identifying comprises: tracking, by the CPU, a focal point of the 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 the file; identifying, by the CPU, as a function of the viewing position, the event data being viewed and an amount of time that the event data is viewed by the user; and further identifying, by the CPU, an emotive expression of the user during an amount of time focused on the viewing position, and wherein said calculating comprises: assigning, by the CPU, a numerical value to the viewing position, amount of time, emotive expression and event data viewed by the user; and inserting, by the CPU, the numerical value assigned to the viewing position, amount of time, 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, a value of the interest score. ### Claim 5 (depends on 4) The computer program product of claim 4, wherein the file comprising event data is selected from the group consisting of a log file, configuration file and source code. ### Claim 6 (depends on 4) The computer program product of claim 4, wherein said tagging the file comprises automatically generating a color coded tag in the file, and wherein the color coded tag generated is based on severity of the events of interest. ### Claim 7 (depends on 4) The computer program product of claim 4, wherein the linear regression model outputs a value of the interest score between 0-1 inclusively. ### Claim 8 (depends on 1) The system of claim 1, wherein the linear regression model outputs a value of the interest score between 0-1 inclusively.