Prosecution Insights
Prosecution Insights
Technology area: Computing & Software
9 pending office actions • 5 art units • 8 examiners • 0 of 9 (0%) have an AI response strategy ready • 3 patents granted in the last 365 days
BMC Software Inc. manages 9 pending office actions in the Computing & Software technology area. These actions are spread across 8 distinct examiners and 5 distinct art units. This indicates a diverse set of software technologies currently under review. The presence of 5 distinct art units suggests that the company's patent applications are being evaluated by multiple specialized groups within the patent office, each focusing on different aspects of computing technology.
NGUYEN, AMANDA DANG is the busiest examiner for the portfolio. This examiner is handling 2 pending office actions. The fact that 8 distinct examiners are assigned to 9 pending actions shows a high degree of distribution in the workload. This variety requires the company to adapt its prosecution tactics to the specific preferences of many different examiners. Managing 9 pending office actions across 5 distinct art units involves coordinating responses that align with the technical standards of various examination teams. This profile highlights the complexity of maintaining a software-based patent portfolio across 5 distinct art units.
Based on the USPTO statutory response window for each pending office action. 3 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 3 of the docket's apps have a known mailing date.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 2 (22%) |
| §101 + other | 4 (44%) |
| §103 only | 2 (22%) |
| Multi-statute (no §101) | 1 (11%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| NGUYEN, AMANDA DANG | 2 | — | — |
| SYED, FARHAN M | 1 | 75.1% | +23.1% |
| RIVERA VARGAS, MANUEL A | 1 | 81.1% | +11.9% |
| THOMPSON, ALMA BENNETT | 1 | — | — |
| MANOSKEY, JOSEPH D | 1 | 93.2% | -9.2% |
| BYCER, ERIC J | 1 | 66.9% | +42.4% |
| RIGGINS, ARI FAITH COLEMA | 1 | 57.1% | +100.0% |
| NAULT, VICTOR ADELARD | 1 | 50.0% | +62.5% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17937254 | ANOMALY DETECTION USING HASH SIGNATURE GENERATION FOR MODEL-BASED SCORING | BYCER, ERIC J | 72d |
| 18622305 | ENHANCEMENT EVENT DETERMINATION AND USE IN SYSTEM MONITORING | RIVERA VARGAS, MANUEL A | — |
| 18511543 | PREDICTING PRIORITY OF SITUATIONS | NGUYEN, AMANDA DANG | — |
| 18511530 | ADAPTIVE SCENARIOS GENERATION FROM SITUATIONS | NGUYEN, AMANDA DANG | — |
| 18511550 | PREDICTING CAUSAL IMPACT FROM SCENARIOS | THOMPSON, ALMA BENNETT | — |
| 18194190 | EFFICIENT TRAINING OF MACHINE LEARNING MODELS FOR LOG RECORD ANALYSIS | MANOSKEY, JOSEPH D | — |
| 17810264 | BATCH WORKLOAD CONTROL BASED ON CAPACITY CONSUMPTION | RIGGINS, ARI FAITH COLEMA | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 5 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18743641 | LOG RECOVERY FOR INTER-TABLESPACE TABLE MIGRATION | SYED, FARHAN M | 19d overdue |
| 17657625 | CAUSAL EVENT PREDICTION FOR EVENTS | NAULT, VICTOR ADELARD | 26d |
| 17937254 | ANOMALY DETECTION USING HASH SIGNATURE GENERATION FOR MODEL-BASED SCORING | BYCER, ERIC J | 72d |
| 18622305 | ENHANCEMENT EVENT DETERMINATION AND USE IN SYSTEM MONITORING | RIVERA VARGAS, MANUEL A | — |
| 17810264 | BATCH WORKLOAD CONTROL BASED ON CAPACITY CONSUMPTION | RIGGINS, ARI FAITH COLEMA | — |
| Art Unit | Apps |
|---|---|
| 2161 | 1 |
| 2113 | 1 |
| 2141 | 1 |
| 2197 | 1 |
| 2124 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18743641 | LOG RECOVERY FOR INTER-TABLESPACE TABLE MIGRATION | SYED, FARHAN M | 2161 | §103 | Non-Final OA | 19d overdue | Pending | Jun 14, 2024 |
| 18622305 | ENHANCEMENT EVENT DETERMINATION AND USE IN SYSTEM MONITORING | RIVERA VARGAS, MANUEL A | — | §101 | Non-Final OA | — | Pending | Mar 29, 2024 |
| 18511543 | PREDICTING PRIORITY OF SITUATIONS | NGUYEN, AMANDA DANG | — | §101§103Other | Non-Final OA | — | Pending | Nov 16, 2023 |
| 18511530 | ADAPTIVE SCENARIOS GENERATION FROM SITUATIONS | NGUYEN, AMANDA DANG | — | §101§103 | Non-Final OA | — | Pending | Nov 16, 2023 |
| 18511550 | PREDICTING CAUSAL IMPACT FROM SCENARIOS | THOMPSON, ALMA BENNETT | — | §101§102§103 | Non-Final OA | — | Pending | Nov 16, 2023 |
| 18194190 | EFFICIENT TRAINING OF MACHINE LEARNING MODELS FOR LOG RECORD ANALYSIS | MANOSKEY, JOSEPH D | 2113 | §101 | Non-Final OA | — | Pending | Mar 31, 2023 |
| 17937254 | ANOMALY DETECTION USING HASH SIGNATURE GENERATION FOR MODEL-BASED SCORING | BYCER, ERIC J | 2141 | §101§103 | Non-Final OA | 72d | Pending | Sep 30, 2022 |
| 17810264 | BATCH WORKLOAD CONTROL BASED ON CAPACITY CONSUMPTION | RIGGINS, ARI FAITH COLEMA | 2197 | §103§112 | Non-Final OA | — | Pending | Jun 30, 2022 |
| 17657625 | CAUSAL EVENT PREDICTION FOR EVENTS | NAULT, VICTOR ADELARD | 2124 | §103 | Final Rejection | 26d | Pending | Mar 31, 2022 |
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