As a Software Engineer at Northside Hospital, you are stepping into a role where your technical expertise directly impacts patient care, clinical operations, and healthcare administration. You will be building and maintaining the critical systems that keep one of the region's leading healthcare providers running smoothly. This is not just about writing code; it is about creating secure, scalable, and highly reliable applications that doctors, nurses, and patients depend on every single day. The impact of this position spans across multiple internal products and user-facing portals. Whether you are optimizing electronic health record (EHR) integrations, building robust internal scheduling tools, or scaling web applications to handle high traffic during peak operational hours, your work ensures that healthcare professionals can focus on saving lives rather than fighting with technology. The complexity here lies in balancing rapid feature development with the strict compliance, security, and high-availability standards required in the healthcare sector. Expect a challenging but deeply rewarding environment. looks for engineers who are not only strong in computer science fundamentals but also adaptable and forward-thinking. You will collaborate with cross-functional teams, navigate complex scaling challenges, and contribute to a mission-driven culture.
Aptitude and Logic Screen
reportedInitial assessment to evaluate problem-solving speed and cognitive abilities through standardized logic puzzles.
What to demonstrate
- Initial assessment to evaluate problem-solving speed and cognitive abilities through standardized logic puzzles
- Depth in Data Structures and Algorithms (DSA)
How to prepare
- Answer aloud and timed: Solve a sequence puzzle: Find the missing number in a complex mathematical series.
- Answer aloud and timed: Calculate the time required for two moving objects to intersect given different speeds and starting points.
Coding Round
reportedDedicated coding interview focused on solving standard algorithmic challenges at medium complexity.
What to demonstrate
- Dedicated coding interview focused on solving standard algorithmic challenges at medium complexity
- Depth in Data Structures and Algorithms (DSA)
How to prepare
- Answer aloud and timed: Deduce the correct seating arrangement of five people based on a set of logical constraints.
- Answer aloud and timed: Given an array of integers, find two numbers such that they add up to a specific target.
Technical Interviews
reportedFinal stages involving deeper technical discussions that blend coding, core computer science trivia, and architectural questions.
What to demonstrate
- Final stages involving deeper technical discussions that blend coding, core computer science trivia, and architectural questions
- Depth in Data Structures and Algorithms (DSA)
How to prepare
- Answer aloud and timed: Write a function to reverse a linked list.
- Answer aloud and timed: Find the longest substring without repeating characters.
PracHub editorial advice for the preparation topics above.
Brush up on your speed math and logic
Do not let the 30-minute aptitude test catch you off guard. Spend a few hours reviewing basic quantitative reasoning and logic puzzles so you can move quickly through the first round.
Communicate before you code
In the technical rounds, always clarify the requirements, discuss your intended approach, and confirm the time and space complexity with your interviewer before writing a single line of code.
Do not ignore system design and DevOps prep
Multiple candidates have reported being asked about scaling, infrastructure, and CI/CD pipelines, even when interviewing for junior full-stack roles. Have high-level concepts prepared.
Relate technical choices to business impact
When answering design or architecture questions, mention how your choices impact reliability, security, and user experience. In a hospital setting, system downtime or data breaches have severe consequences.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Given an array of integers, find two numbers such that they add up to a specific target.
Given an array of integers, find two numbers such that they add up to a specific target.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Write a function to reverse a linked list.
Write a function to reverse a linked list.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Find the longest substring without repeating characters.
Find the longest substring without repeating characters.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Implement a binary search algorithm to find an element in a sorted array.
Implement a binary search algorithm to find an element in a sorted array.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Given a string containing just the characters '(', ')', '{', '}', '[' and ']', determine if the input string i
Given a string containing just the characters '(', ')', '{', '}', '[' and ']', determine if the input string is valid.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
How does garbage collection work in your primary programming language?
How does garbage collection work in your primary programming language?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
What is the difference between an inner join and a left outer join in SQL?
What is the difference between an inner join and a left outer join in SQL?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Solve a sequence puzzle: Find the missing number in a complex mathematical series.
Solve a sequence puzzle: Find the missing number in a complex mathematical series.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Calculate the time required for two moving objects to intersect given different speeds and starting points.
Calculate the time required for two moving objects to intersect given different speeds and starting points.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Deduce the correct seating arrangement of five people based on a set of logical constraints.
Deduce the correct seating arrangement of five people based on a set of logical constraints.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain the concept of polymorphism and provide a real-world coding example.
Explain the concept of polymorphism and provide a real-world coding example.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Describe the OSI model and explain which layer HTTP operates on.
Describe the OSI model and explain which layer HTTP operates on.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain the difference between optimistic and pessimistic locking in a database.
Explain the difference between optimistic and pessimistic locking in a database.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How would you design a scalable web architecture for a patient portal expecting sudden spikes in traffic?
How would you design a scalable web architecture for a patient portal expecting sudden spikes in traffic?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Explain how you would implement caching to reduce database load.
Explain how you would implement caching to reduce database load.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
What are the benefits of containerizing an application, and how does Docker achieve this?
What are the benefits of containerizing an application, and how does Docker achieve this?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Walk me through how you would set up a CI/CD pipeline from scratch for a new microservice.
Walk me through how you would set up a CI/CD pipeline from scratch for a new microservice.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How do you monitor an application in production, and what metrics are most important to track?
How do you monitor an application in production, and what metrics are most important to track?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Every query on one table stalls for forty seconds mid-deploy
During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.
Approach
- Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
- Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
- Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
- Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.
Follow-up
- The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
- Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?
Built from the rounds and topics Northside Hospital candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Northside Hospital loop
- Write out the reported sequence: Aptitude and Logic Screen, Coding Round, Technical Interviews.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.
02Work Data Structures and Algorithms (DSA)
- Spend the session on Data Structures and Algorithms (DSA), which Northside Hospital candidates report being tested on.
- Write one worked example in Data Structures and Algorithms (DSA) and time yourself on it.
Deliverable: One timed worked example in Data Structures and Algorithms (DSA).
03Work Coding Interviews
- Spend the session on Coding Interviews, which Northside Hospital candidates report being tested on.
- Write one worked example in Coding Interviews and time yourself on it.
Deliverable: One timed worked example in Coding Interviews.
04Work Problem Solving
- Spend the session on Problem Solving, which Northside Hospital candidates report being tested on.
- Write one worked example in Problem Solving and time yourself on it.
Deliverable: One timed worked example in Problem Solving.
05Answer out loud: Aptitude and Logic
- Answer aloud, timed: Solve a sequence puzzle: Find the missing number in a complex mathematical series.
- Answer aloud, timed: Calculate the time required for two moving objects to intersect given different speeds and starting points.
Deliverable: Spoken answers to 2 reported Aptitude and Logic question(s), under time.
06Answer out loud: Data Structures and Algorithms
- Answer aloud, timed: Given an array of integers, find two numbers such that they add up to a specific target.
- Answer aloud, timed: Write a function to reverse a linked list.
Deliverable: Spoken answers to 2 reported Data Structures and Algorithms question(s), under time.
07Answer out loud: Core Computer Science Fundamentals
- Answer aloud, timed: Explain the concept of polymorphism and provide a real-world coding example.
- Answer aloud, timed: What is the difference between an inner join and a left outer join in SQL?
Deliverable: Spoken answers to 2 reported Core Computer Science Fundamentals question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Ship under a deadline and bound the debt you chose
You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.
Approach
- Name the deferred failure precisely instead of calling it slow. OFFSET n makes the database produce and discard n rows, so cost grows with page depth; without an index matching the sort, every matching row is read and sorted before the limit applies; and rows inserted between two page fetches shift across the boundary so items are skipped or repeated with nothing in the response to signal it.
- Bound the blast radius with something mechanical rather than a promise: cap maximum page depth, cap page size, restrict the endpoint to one internal caller, or keep it behind a flag. State which failure each cap removes and which it leaves standing.
- Attach a number to the trigger and wire it to an alarm: the first tenant crossing N resources, or the endpoint's p99 crossing its share of the 400 ms budget, so the debt announces itself instead of waiting to be remembered.
- Write it where the next engineer looks, which is the code and the ticket, not a chat message: what was deferred, why, the cap, and the trigger.
Follow-up
- At what page depth does the offset version breach your latency budget, given your page size and row counts?
- What breaks first when you switch to keyset pagination later, and what does a client holding an old page token see?
Unblock an engineer without taking the keyboard
A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.
Approach
- Ask before diagnosing, and ask for things answerable from data they already have: the attempt count on the job rows that produced duplicates, the handler's observed duration against its lease expiry, and whether the duplicate rows share a natural key that a unique constraint could have caught.
- Teach the shape rather than the answer. A lease cannot distinguish a dead worker from a slow one, so a handler that outruns its lease is running twice by design, and deploys deliver the other half by killing handlers mid-run on every rollout. Both of their candidate theories produce identical duplicate rows, which is why the evidence has to come from timings rather than from argument.
- Hand over a checklist they execute: a natural key on every write the handler performs so the second copy collides rather than appends, the record of intent written before any external effect, a lease heartbeat while running, and the metric that shows it working.
- Keep ownership with them deliberately. Pair on the first write, then step back; if you finish it yourself you have closed one ticket and left the same person stuck on the next redelivery.
Follow-up
- How would you distinguish a genuine double-delivery from a lease expiry using only the data already stored?
- Their handler calls an external endpoint before recording that it did. What do you tell them to change first?
Narrate an outage you owned from page to postmortem
Pick an incident you personally drove, ideally one where writes were affected rather than reads. In six to eight minutes: state the symptom as it first appeared on a dashboard, the blast radius you established before you knew the cause, the mitigation you applied and when, the mechanism you eventually proved, and the follow-up that would prevent a repeat. Bring numbers: error rate, tenants affected, minutes to mitigate, minutes to resolve. If you cannot name what you measured, choose a different incident.
Approach
- Open on the signal rather than the cause: which metric at which percentile moved, on which service, at what time, so the listener follows the same evidence you had rather than a conclusion you already reached.
- Separate mitigation from diagnosis out loud. State what you did to stop the bleeding (flag off, shed traffic, drain a lease, roll back a deploy) and say plainly that you did it before the mechanism was known, because those are two jobs with different deadlines.
- Establish blast radius in countable terms: how many tenants, how many writes, and crucially whether the effect was loss or only delay. An append-only revision table or a pending outbox row means the change survived and the projection was merely behind, which is a repair rather than a data-loss incident.
- Prove the mechanism instead of asserting it. Name the trace span that grew, the plan that flipped to a sequential scan, the lease that expired, plus one alternative you ruled out and the signal that stayed flat while you ruled it out.
Follow-up
- What would you do differently in the first five minutes, given the same dashboard and no more information?
- Which follow-up action did you deliberately not take, and why was dropping it the right call?
- 01
You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.
- 02
A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.
- 03
Pick an incident you personally drove, ideally one where writes were affected rather than reads. In six to eight minutes: state the symptom as it first appeared on a dashboard, the blast radius you established before you knew the cause, the mitigation you applied and when, the mechanism you eventually proved, and the follow-up that would prevent a repeat. Bring numbers: error rate, tenants affected, minutes to mitigate, minutes to resolve. If you cannot name what you measured, choose a different incident.
How difficult are the technical interviews at Northside Hospital?
The difficulty is generally considered average to slightly above average. While the algorithmic questions rarely exceed a "medium" level, the inclusion of an initial aptitude test and deep-dive questions into DevOps and system scaling can make the process feel rigorous, especially for junior candidates.
Northside Hospital Software Engineer candidate reports ↗How much preparation time is typical for this role?
Most successful candidates spend 3 to 4 weeks preparing. You should dedicate time evenly across practicing medium-level DSA problems, reviewing core CS fundamentals (OS, networking, databases), and brushing up on basic system design and deployment concepts.
Northside Hospital Software Engineer candidate reports ↗What differentiates successful candidates from the rest?
Successful candidates do not just write code that works; they write code that is clean and maintainable. Furthermore, candidates who can confidently discuss how their code fits into a larger, scalable system—and who show an understanding of deployment and infrastructure—stand out significantly.
Northside Hospital Software Engineer candidate reports ↗What is the culture like for an engineer at Northside Hospital?
The culture is highly professional, mission-driven, and collaborative. Interviewers are known to be friendly and eager to share details about the hospital. The environment values stability, security, and teamwork over "move fast and break things," given the critical nature of healthcare data.
Northside Hospital Software Engineer candidate reports ↗Will I be penalized if I cannot answer a complex DevOps question as a junior developer?
Not necessarily. Interviewers often ask advanced questions to find the limits of your knowledge. If you do not know the answer, be honest, explain how you would go about finding the solution, and rely on your core CS fundamentals to make an educated guess.
Northside Hospital Software Engineer candidate reports ↗What topics does Northside Hospital test in interviews?
Northside Hospital interviews most often cover Problem Solving, Stakeholder Communication, Analytical Thinking, Communication Skills, and Financial Analysis. The exact emphasis depends on the specific role you apply for.
Northside Hospital Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Northside Hospital Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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