Interview guides · Airbus DS Government Solutions

Airbus DS Government Solutions Software Engineer Interview Guide

Airbus DS Government Solutions Software Engineer interview prep: reported rounds, coding and design questions worked through, and a 7-day plan.

The 60-second brief

Candidates describe Airbus DS Government Solutions as a builder and maintainer of software for the defense, space and government sectors. Reported project types include software for satellite systems, secure communication tools for military use, data-analysis applications, interfaces for satellite communication, and performance work on systems already in service. Software Engineers there write and maintain that software alongside product managers, QA engineers and system architects, and take part in code reviews. Reliability and security come up repeatedly in the reported questions, from code security to the design of a satellite-data monitoring system.

This guide is for Software Engineer candidates preparing for the Airbus DS Government Solutions loop. It covers the three reported rounds (Initial Screening, Technical Interviews, Collaborative Discussions), the reported question set across coding, system design, problem solving, technical/domain knowledge and behavioral prompts, and the requirements candidates describe: Java, C++ or Python, Agile practice, algorithms and data structures, and Git, with cloud (AWS, Azure), cybersecurity and DevOps listed as nice-to-haves.

Candidates report three rounds over roughly 3-5 weeks: a video-call Initial Screening, Technical Interviews with technical managers or directors, and a Collaborative Discussions stage built around experiences and ideas.

Focus areas

Technical Knowledge (Domain Expertise)
Change Management (Handling Change Situations)
Mentorship / Student Supervision

Overview

The reported work is software for defense, space and government programmes: satellite systems, secure military communication tools, data-analysis applications and satellite-communication interfaces, plus improving the performance of existing systems. That shapes the question set. Several reported questions are about trustworthy software rather than clever algorithms: how you keep code secure and of high quality, what a secure system design must cover, how you troubleshoot a critical failure, and how you would monitor satellite data. Prepare concrete, defensible answers to these, grounded in your own past work.

The coding questions candidates report are fundamentals: reversing a linked list, two-sum, binary search, explaining time and space complexity, and building a small RESTful API in a framework of your choice. None needs an exotic algorithm. What separates answers here is code that is correct on the edge cases (empty input, one element, duplicates, integer overflow on the midpoint), a stated complexity, and an API with sensible status codes and validation. Practise writing each one cleanly in the language you will use, without an IDE.

The requirements candidates describe list Java, C++ or Python, Agile methodology, algorithms and data structures, and Git, with AWS or Azure, cybersecurity and DevOps as extras. Choose one language as your interview language and be ready for depth in it: memory management and RAII in C++, the JVM and garbage collection in Java, or the GIL and dynamic typing in Python. One reported question asks directly which languages you are strongest in and why, and another asks about your experience with Agile or Scrum, so have specifics about how your teams actually ran.

Candidates also report topic areas beyond the technical: technical/domain knowledge, change management, mentorship, adaptability and software engineering fundamentals. The reported behavioral questions cover a difficult teammate, deadlines and stress, leading an initiative, team communication and motivation. Build a story bank that includes a mentoring story and a story about a requirement or plan changing under you, since neither is covered by the standard conflict and leadership prompts.

The Airbus DS Government Solutions interview process

Candidates report three rounds in this order, over roughly 3-5 weeks. The descriptions below summarise what candidates report and how to prepare for each.

Initial Screening

Candidates report the Initial Screening as a video call covering basic qualifications and motivation. Treat it as a check that your background matches the requirements candidates describe (Java, C++ or Python, Agile, data structures and algorithms, Git) and that your reasons for wanting this work are specific. Keep your background summary short and tie it to the reported project types: satellite systems, secure communications, data-analysis tools, government software. Use the end of the call to confirm the remaining stages and the on-site expectations for the position.

What to demonstrate

Basic qualifications against the role's listed requirements
Motivation for this role and this kind of work

How to prepare

Write a 90-second background summary that names your main language, one system you built or maintained, and one reliability or security problem you handled.
Write a motivation answer for the reported question about what motivates you, tied to a real past example rather than to adjectives.
Have your location and on-site constraints ready, since candidates report that many positions involve on-site presence.
List two questions about the team's projects and the next stages to ask at the end of the call.

Technical Interviews

Candidates report in-depth interviews with technical managers or directors, centred on problem-solving and technical knowledge. Prepare for depth rather than breadth: be ready to explain why your approach works, what it costs, and where it fails. The reported technical question set spans coding fundamentals, design and architecture, debugging and legacy code, and language and OOP knowledge, so prepare all of it rather than guessing which part this stage uses. When solving anything, say your assumptions, work the edge cases aloud, and state complexity or trade-offs without being asked.

What to demonstrate

Problem-solving: how you break down and reason through a problem
Technical knowledge in your languages and software engineering fundamentals

How to prepare

Write the linked-list reversal, two-sum and binary search solutions by hand in your interview language, each with its complexity and three edge-case tests.
Outline the satellite-data monitoring design end to end: ingestion, buffering, limit checks, alerting, storage and replay, plus how it handles gaps and duplicate packets.
Rehearse a step-by-step troubleshooting walkthrough for a production failure you actually handled, from mitigation to root cause to prevention.
Prepare a one-page note on your strongest language: memory model, concurrency primitives, and one bug you hit that was specific to that language.

Collaborative Discussions

Candidates describe this stage as an open conversation about past experience and ideas. Prepare to talk through your own projects in depth and to discuss ideas as a two-way exchange: explain your reasoning, invite challenges, and adjust when given new information. The reported behavioral questions and the reported topics of mentorship, change management and adaptability are the natural material to rehearse for a discussion-style stage.

What to demonstrate

How clearly you explain your past work and the decisions in it
How you discuss and build on ideas with others

How to prepare

Build a bank of six stories: a hard technical problem, a difficult teammate, a deadline, a project you led, a mentoring relationship, and a plan that changed mid-stream.
For each story, write the decision you personally made and the measurable result, in first person singular.
Pick one design idea from your past work (or the satellite monitoring design) and practise explaining it, then defending or revising it against two objections.
Prepare questions about the team's current projects, review practices and how work is split with QA and system architects.

Where candidates lose points

Binary search or linked-list reversal written with a boundary bug: an infinite loop from lo = mid, an off-by-one on hi, or losing the rest of the list by overwriting next before saving it.

Write the loop invariant first, then trace your code by hand on an empty input, one element, two elements, and a target not present. Practise until you can write both without running them.

Starting the satellite monitoring design by naming technologies before asking about data rates, contact passes, alert latency and retention, and never covering gaps, duplicates or a silent pipeline.

Open every design answer with requirements and numbers, then build the pipeline from them. For telemetry specifically, say how you deduplicate, how you show missing data differently from nominal data, and how you alert when data stops arriving.

Answering the code security and secure-design questions with a list of buzzwords (encryption, firewalls, best practices) and no threat model or concrete control.

Name the assets and trust boundaries, then map each threat to a specific control, and back it with one example from your own code where a review, test or scanner caught a real issue.

Claiming equal depth in Java, C++ and Python, then stalling on a follow-up about memory management, garbage collection or the GIL.

Lead with one language and prepare its internals: ownership and RAII for C++, the JVM and GC for Java, the GIL and the cost of dynamic typing for Python. Mention the others honestly as secondary.

Reusing one story for both the challenging-technical-problem and complex-problem prompts, telling stories in 'we', and having nothing for the reported mentorship and change-management topics.

Build a bank of at least six distinct stories, including one mentoring story and one where requirements or plans changed mid-stream, and rehearse each in first person singular with a measurable result.

Questions & practice

Write a function to reverse a linked list.

Medium · Coding / Algorithms

Approach

Iterate with three pointers: prev = null, curr = head; at each step save next = curr.next, set curr.next = prev, then advance prev = curr and curr = next. Return prev as the new head.
Complexity: O(n) time and O(1) extra space.
Mention the recursive version (reverse the rest, then head.next.next = head and head.next = null), which is O(n) time but uses O(n) call stack and can overflow on long lists.
Test the edge cases aloud: empty list, one node, two nodes; the classic bug is overwriting curr.next before saving it.

Follow-up

Reverse the list in groups of k nodes.
Reverse only the sublist between positions m and n.
How does the solution change for a doubly linked list?

Given an array of integers, find two numbers that add up to a specific target.

Medium · Coding / Algorithms

Approach

Brute force checks every pair in O(n^2) time; improve it with a hash map from value to index.
Single pass: for each element x at index i, check whether target - x is already in the map; if so return the two indices, otherwise insert x. Checking before inserting stops an element pairing with itself.
Complexity: O(n) time, O(n) space. Alternative: sort and use two pointers for O(n log n) time and O(1) extra space, but sorting loses the original indices unless you carry them along.
Edge cases: no solution (say what you return), duplicate values such as [3, 3] with target 6, negative numbers, and integer overflow when computing sums in Java or C++.

Follow-up

Return all unique pairs that sum to the target.
How would you solve it if the array were already sorted?
Extend it to three numbers that sum to the target.

Explain the time and space complexity of your solution.

Medium · Coding / Algorithms

Approach

State time and space separately, in terms of the input size n, for the worst case unless asked otherwise.
Derive it from the code: count nested loops, write recurrences for recursion (binary search gives T(n) = T(n/2) + O(1), so O(log n)), and include auxiliary space such as hash maps and the recursion stack.
Distinguish average from worst case (hash map lookups are O(1) on average but O(n) in the worst case) and amortised cost (appending to a dynamic array is O(1) amortised).
Apply it to the reported problems: linked-list reversal O(n)/O(1) iterative, two-sum O(n)/O(n), binary search O(log n)/O(1) iterative.

Follow-up

Explain amortised analysis using a dynamic array.
When does a hash map degrade to O(n) per lookup?
What is the space complexity of the recursive linked-list reversal?

How would you implement a binary search algorithm?

Medium · Coding / Algorithms

Approach

Requires sorted input. Keep lo = 0 and hi = n - 1, loop while lo <= hi, compute mid = lo + (hi - lo) / 2 to avoid integer overflow, compare and move lo = mid + 1 or hi = mid - 1.
State the loop invariant (if the target exists, it lies in [lo, hi]) and you will get the boundary updates right.
Complexity: O(log n) time and O(1) space iteratively (O(log n) stack if recursive).
Edge cases: empty array, a single element, target smaller than all or larger than all, and duplicates; for duplicates, write the lower-bound variant that finds the first index with a value of at least the target.

Follow-up

Find the first and last occurrence of a target in a sorted array with duplicates.
Search in a rotated sorted array.
Use binary search on the answer, for example to compute an integer square root.

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

Explain a challenging technical problem you've solved and the approach you took.

Medium · Technical / Domain Questions

Approach

Pick a problem with real technical depth (a race condition, a performance cliff, a data-corruption bug, an integration with an unreliable system), not a process or people problem; save those for the behavioral prompts.
Structure it as constraint, options, decision, result: what made it hard, the two or three approaches you considered, why you chose one, and a measured outcome (latency, error rate, defect count).
Speak in first person about your own contribution; name what teammates did separately so your part is unambiguous.
Close with what you would do differently, which shows the reasoning was yours and not luck.

Follow-up

Which alternative did you reject, and what would have happened if you had chosen it?
How did you verify the fix actually solved the problem?
What part of the solution would not hold up at ten times the load or data?

How do you ensure the quality and security of your code?

Medium · Technical / Domain Questions

Approach

Answer in layers rather than a list: design (threat modelling and design review), code (review checklists, input validation, least privilege), automated checks (unit and integration tests that cover failure paths, static analysis such as SpotBugs, clang-tidy or Bandit, dependency scanning), and release (CI gates that block merges).
Name specific security habits: validating and encoding untrusted input, parameterised queries, no secrets in source control, pinned and scanned dependencies, and failing closed on errors.
Give one concrete example where a test, a review comment or a scanner caught a real defect or vulnerability before release.
Mention the trade-off: what you require on every change versus what you reserve for high-risk code paths.

Follow-up

Tell me about a vulnerability or serious bug that got past your process. What changed afterwards?
How do you handle a critical CVE in a third-party library you depend on?
How do you decide how much test coverage is enough?

What programming languages are you most proficient in, and why?

Medium · Technical / Domain Questions

Approach

Lead with one language you can go deep in, ideally one the role lists (Java, C++ or Python), and say what you have built with it.
Justify with technical properties, not taste: C++ for deterministic performance and memory control (RAII, smart pointers), Java for a mature JVM ecosystem, strong typing and garbage collection, Python for fast development, scripting and data tooling.
Show you know each language's costs: undefined behaviour and manual lifetime issues in C++, GC pauses and verbosity in Java, the GIL and runtime type errors in Python.
Say how you would choose between them for a given task, such as a high-rate telemetry parser versus an internal analysis script.

Follow-up

What is the GIL, and how would you parallelise CPU-bound Python work?
How does C++ RAII compare with Java's garbage collection for managing resources?
Describe a bug you hit that was specific to your main language.

Can you explain the concept of object-oriented programming and its principles?

Medium · Technical / Domain Questions

Approach

Name the four principles with a one-line definition each: encapsulation (state hidden behind methods), abstraction (callers depend on what, not how), inheritance (reuse and subtyping), polymorphism (one interface, many implementations through dynamic dispatch).
Ground them in one small example, such as a Sensor interface with TemperatureSensor and PressureSensor implementations read through a common read() method.
Add the judgement: prefer composition over deep inheritance, and know the Liskov substitution principle (the classic Square/Rectangle violation).
If asked for more, connect to SOLID and to language specifics such as Java interfaces versus abstract classes, or virtual functions in C++.

Follow-up

When would you use an interface instead of an abstract class in Java?
Why does a C++ base class with virtual functions need a virtual destructor?
Give an example where inheritance made a codebase harder to change.

Design a system for monitoring satellite data and its requirements.

Medium · System Design / Architecture

Approach

Start with requirements: number of satellites, telemetry rate and packet format, whether data arrives only during ground-station contact passes (bursty), alert latency targets, retention period, and who consumes the data (operators, analysts).
Lay out the pipeline: ground-station receivers, a decoder that parses and validates frames, a durable queue such as Kafka to absorb bursts, a stream processor that applies limit and trend checks and raises alerts, a time-series store for recent data, and a raw archive for replay and audit.
Handle the realities of the link: out-of-order and duplicate packets (deduplicate on satellite id plus sequence number or timestamp), gaps when contact is lost, and a clear distinction between no data and nominal data on the dashboards.
Cover security and reliability: network segmentation, authenticated and encrypted links, role-based access to commands and data, redundant ingestion, and an alert on the pipeline itself when data stops arriving.

Follow-up

Contact is lost mid-pass. How does the system and the operator dashboard behave?
How would you change alert thresholds without redeploying the processor?
How would you reprocess a week of archived telemetry after fixing a decoder bug?

How would you approach scaling a web application for increased user load?

Medium · System Design / Architecture

Approach

Measure before scaling: identify whether the bottleneck is application CPU, the database, external calls or network, using load tests and metrics.
Make the application tier stateless (sessions in a shared store or tokens) so it scales horizontally behind a load balancer, with autoscaling on a meaningful signal.
Reduce load on the database: indexes for hot queries, connection pooling, cache-aside with Redis for read-heavy data, read replicas, and partitioning only once those are exhausted.
Move slow work off the request path with a queue and workers, put static content behind a CDN, and add rate limiting to protect the system under spikes.

Follow-up

How do you prevent a cache stampede when a popular key expires?
A user writes data and immediately reads stale data from a replica. How do you fix that?
Which metric would you autoscale on, and why not CPU alone?

Discuss the trade-offs between microservices and monolithic architecture.

Medium · System Design / Architecture

Approach

Monolith strengths: one deployable, in-process calls, local transactions, simpler debugging and testing. Costs: every change redeploys everything, the whole application scales as one unit, and boundaries erode over time.
Microservices strengths: independent deployment and scaling, fault isolation, team ownership of a service. Costs: network latency and partial failure, no cross-service ACID transactions (sagas instead), distributed tracing and much more operational work.
Name the deciding factors: team size, deployment frequency, how clear the domain boundaries are, and the operational maturity to run many services.
Offer the middle path: a modular monolith with enforced module boundaries, extracting services later with the strangler fig pattern.

Follow-up

How would you split an existing monolith without a big-bang rewrite?
How do you keep data consistent across services that each own their database?
What observability do you need before running microservices in production?

What considerations must you account for when designing a secure software system?

Medium · System Design / Architecture

Approach

Begin with a threat model: assets, actors, trust boundaries and entry points, using a framework such as STRIDE to enumerate threats.
Map controls to threats: strong authentication and least-privilege authorisation (role-based access), TLS or mutual TLS in transit, encryption at rest with managed keys and rotation, and input validation at every trust boundary.
Cover operations: secrets management, patching and dependency scanning, tamper-resistant audit logs that never contain sensitive data, and monitoring for anomalous access.
State the principles: defence in depth, secure defaults, fail closed, and minimising attack surface, with the trade-off that each control adds cost or friction.

Follow-up

How would you design for an insider threat?
How do you rotate an encryption key without downtime?
What would you log for an audit trail, and what must you never log?

How do you prioritize features during the design phase?

Medium · System Design / Architecture

Approach

Separate non-negotiables first: safety, security, regulatory or contractual requirements that must ship regardless.
Rank the rest on value against effort and risk, using a method such as MoSCoW or a simple value and effort matrix, and account for dependencies between features.
Build the riskiest or most uncertain part early so problems surface while there is time to react.
Agree priorities with stakeholders in writing and revisit them when requirements change; give a real example where you did this.

Follow-up

Two stakeholders both insist their feature is a must-have. What do you do?
A must-have turns out to be twice the estimate. How do you respond?
How do you say no to a feature request?

How would you approach optimizing a legacy codebase?

Medium · Problem-Solving / Case Studies

Approach

Clarify what optimise means: runtime performance, maintainability, build time or defect rate. Each needs a different plan.
Measure a baseline first (profiling for performance, churn and complexity metrics for maintainability) and target the hotspots where change frequency and complexity overlap.
Pin current behaviour with characterisation tests before refactoring, then change in small, reversible steps, using feature flags or the strangler pattern for larger replacements.
Argue against a big-bang rewrite unless the system cannot be safely changed, and explain how you would show progress to stakeholders.

Follow-up

There are no tests at all. Where do you start?
When is a full rewrite justified?
How would you convince management to fund refactoring work?

Given a set of requirements, how do you determine the best solution?

Medium · Problem-Solving / Case Studies

Approach

Clarify the requirements, including the non-functional ones (latency, reliability, security, maintainability), the constraints (budget, schedule, existing systems) and which requirements are fixed versus negotiable.
Generate two or three candidate solutions rather than jumping to the first one.
Compare them against explicit criteria, for example with a weighted decision matrix, and prototype the riskiest assumption if the decision depends on it.
Record the decision and its reasoning (an architecture decision record) so it can be revisited when requirements change.

Follow-up

What do you do when a requirement is ambiguous and the stakeholder is unavailable?
Two non-functional requirements conflict, such as security and latency. How do you decide?
When would you revisit a decision you already made?

Describe a complex problem you've encountered and how you solved it.

Medium · Problem-Solving / Case Studies

Approach

Use a different story from your hardest-technical-problem answer; this one should show how you decomposed a problem with many unknowns.
Explain how you broke it into sub-problems, which unknown you resolved first and why, and how you validated each part.
Make your individual contribution clear and quantify the outcome.
Close with a lesson you have applied since, which shows the experience changed how you work.

Follow-up

What was the hardest sub-problem, and why?
Who else was involved, and what exactly was your part?
What would you do differently with what you know now?

Create a simple RESTful API using your preferred language/framework.

Medium · Coding / Algorithms

Approach

Pick a framework you know well (Flask or FastAPI in Python, Spring Boot in Java) and model one resource, for example /tasks, with GET list, GET by id, POST create, PUT or PATCH update and DELETE.
Return correct status codes: 200 for reads, 201 with a Location header on create, 204 on delete, 400 for invalid input, 404 for a missing resource, 409 for conflicts, and a consistent JSON error body.
Validate input at the boundary, keep handlers thin with storage behind a separate layer, and write tests for success and error cases.
Mention production concerns: authentication, pagination for lists, idempotency (PUT and DELETE are idempotent; POST needs an idempotency key for safe retries), and versioning such as /v1.

Follow-up

How would you version this API without breaking existing clients?
A client retries a POST after a timeout. How do you avoid creating a duplicate?
How would you detect and reject two clients updating the same resource at once?

Can you walk us through your troubleshooting process for a critical software failure?

Medium · Problem-Solving / Case Studies

Approach

Stabilise first: assess impact, communicate status, and mitigate through rollback, failover or disabling a feature before hunting the root cause.
Gather evidence: logs, metrics, traces, and what changed recently (deployments, configuration, dependencies, traffic).
Form hypotheses and test them in order of likelihood and cost; reproduce in a safe environment, and bisect changes when the cause is unclear.
Fix the root cause with a regression test, then run a blameless postmortem with actions that prevent recurrence, such as alerts or safeguards; illustrate with a real incident.

Follow-up

The failure cannot be reproduced outside production. What next?
How do you decide between rolling back and shipping a hotfix?
What changed in your process after the incident?

How do you approach debugging an application?

Medium · Problem-Solving / Case Studies

Approach

Reproduce the bug reliably and shrink it to the smallest failing case.
Read the evidence before guessing: error message, stack trace, logs, and the inputs that trigger it.
Form a hypothesis and test it with a debugger or targeted logging; for regressions, bisect commits with git bisect.
Use language-specific tools where they fit (gdb, Valgrind or AddressSanitizer for C++, an IDE debugger for Java, pdb for Python), then fix and add a regression test that fails without the fix.

Follow-up

How would you debug an intermittent bug you suspect is a race condition?
How would you track down a memory leak?
How do you debug a problem that only happens in production?

Suggested practice checklist

Each day targets one part of the reported question set, in an order that moves from coding fundamentals to design, debugging and then the screening and discussion stages. Every task produces something written or coded that you can review the night before the loop.

Day 1 — Linked lists, binary search and complexity

Write iterative and recursive linked-list reversal in your interview language and test both on empty, single-node and two-node lists.
Write binary search plus its lower-bound variant, stating the loop invariant in a comment before the code.
For each solution, write its time and space complexity with a one-line derivation.

Deliverable: Two tested solution files with invariants and a complexity note for each.

Day 2 — Two-sum and a small REST API

Solve two-sum with a hash map in one pass, then with sorting and two pointers, and write down when each is preferable.
Build a small CRUD API for one resource in Flask, FastAPI or Spring Boot, with validation, correct status codes and a JSON error format.
Add a version column to the API's update path so a stale concurrent update returns 409, using the concurrent-edit practice question as the model.

Deliverable: Two two-sum implementations with a comparison note, and a working API with tests for success, validation, missing-resource and conflict cases.

Day 3 — Language depth, OOP and code quality

Write a one-page note on your main language: memory model, concurrency, standard collections and one language-specific bug you have hit.
Code a small class hierarchy that shows encapsulation, abstraction, polymorphism and composition, and write one Liskov violation with its fix.
Outline your layered answer on code quality and security, with one real example of a defect caught before release.

Deliverable: A language note, an OOP example file, and a written quality-and-security answer with its example.

Day 4 — Satellite monitoring and scaling designs

Sketch the satellite-data monitoring pipeline from ground station to dashboard, with requirements and numbers written first.
Write how the design handles lost contact, duplicate and out-of-order packets, and a silent pipeline.
Sketch a plan for scaling a web application, from measuring the bottleneck to caching, replicas and queues, and answer the cache-stampede and replica-lag follow-ups.

Deliverable: Two design diagrams with written requirements, failure handling and answers to their follow-ups.

Day 5 — Architecture trade-offs, security and requirements

Write a comparison table for monolith, modular monolith and microservices, and a strangler-fig migration plan for one system you know.
Write a STRIDE threat model for the satellite monitoring design, with one control per threat.
Practise aloud how you go from a set of requirements to a chosen solution, and how you prioritise features, each with a real example.

Deliverable: An architecture comparison table, a threat model, and two recorded answers on requirements and prioritisation.

Day 6 — Debugging, legacy code and problem stories

Write your incident walkthrough for a real failure: mitigation, evidence, hypotheses, root cause, regression test and postmortem actions.
Write your general debugging sequence with the tools you use in your language, including a git bisect example.
Write the legacy-optimisation plan for a codebase you know, and two distinct STAR stories for the hard technical problem and complex problem prompts.

Deliverable: An incident write-up, a debugging checklist, a legacy-code plan and two distinct problem stories.

Day 7 — Screening, behavioral stories and a mock loop

Write and time your 90-second background summary and your motivation answer.
Write STAR answers for the difficult teammate, deadline, leadership, team communication and Agile experience prompts, plus a mentoring story and a change-of-plan story.
Run a mock of all three stages with a peer: screen questions, one coding question from day 1 or 2, one design question, and two behavioral stories.

Deliverable: A timed screen script, a written story bank of eight stories, and notes from a full mock loop on what to fix.

Behavioural preparation

Candidates report a Collaborative Discussions stage built around past experience and ideas, plus behavioral questions on teamwork, deadlines, leadership, communication and motivation, and topic areas of mentorship, change management and adaptability. Prepare stories that show a decision you made, how you worked with others on it, and a measurable result.

Tell me about a time you mentored a less experienced engineer. What changed in their work?
Describe a time requirements or plans changed partway through a project. How did you adapt?

Describe your experience with software development methodologies (e.g., Agile, Scrum).

Medium · Technical / Domain Questions

Approach

Describe how your team actually ran: iteration length, which ceremonies you held, how work was estimated and how a story reached done (tests, review, demo).
State your own role in it: running stand-ups, breaking down stories, writing acceptance criteria or improving the retrospective process.
Show judgement about where the method strained, for example fixed external requirements, heavy documentation needs or hardware and integration dependencies, and how the team adapted.
Contrast briefly with plan-driven approaches (waterfall, V-model) and when their up-front requirements and verification are a better fit.

Follow-up

Describe a sprint that went badly. What did the retrospective change?
How do you handle a requirement change in the middle of a sprint?
How do you estimate work you have never done before?

Describe a time when you had to work with a difficult team member and how you managed the situation.

Medium · Behavioral / Leadership

Approach

Use a STAR structure and describe the specific behaviour that caused friction (missed handoffs, dismissive reviews), not the person's character.
Show what you did first: a private conversation to understand their view, then agreed working norms such as review turnaround or clear ownership.
Say when and why you escalated, if you did, and only after direct attempts.
End with a concrete outcome and what you changed in your own behaviour; avoid stories where you come across as blameless and the other person as the villain.

Follow-up

What would you have done if the situation had not improved?
How do you think that person would describe the episode?
What did you learn about your own working style?

How do you handle tight deadlines and stress at work?

Medium · Behavioral / Leadership

Approach

Tell one specific deadline story rather than describing general habits.
Show the mechanics: breaking work down, cutting or deferring scope by priority, and raising the risk to stakeholders early instead of on the last day.
State what you protected, such as tests on the critical path or code review, and what you deliberately deferred.
Give the result and how you kept the pace sustainable, then one thing you would do earlier next time.

Follow-up

Tell me about a deadline you missed. How did you handle it?
What exactly did you cut, and who agreed to it?
How do you stop urgent work from crowding out quality?

Share an experience where you had to lead a project or initiative.

Medium · Behavioral / Leadership

Approach

Pick an initiative where you owned the outcome, even without a formal title: a migration, a tooling improvement, a feature delivered across teams.
Cover scope and plan, how you split work and unblocked others, one hard decision you made, and how you tracked progress.
Quantify the result (time saved, defects reduced, delivery date met) and name the team's contribution separately from yours.
Include a setback and how you adjusted, since a story with no friction says little about leading.

Follow-up

How did you handle a team member who was not delivering?
Which decision would you reverse now?
How did you keep stakeholders informed?

How do you ensure effective communication within your team?

Medium · Behavioral / Leadership

Approach

Describe concrete practices you have used: short written design notes before building, stand-ups focused on blockers, a decision log, agreed code review norms, and written status updates for people outside the team.
Give an example of a miscommunication that caused a problem and the specific practice you introduced to stop it recurring.
Show adaptation to the audience: technical detail for engineers and QA, impact and risk for product managers and non-technical stakeholders.
Mention how you handle disagreement in reviews or design discussions so it stays about the work.

Follow-up

How does this change for a distributed or partly remote team?
How do you explain a technical risk to a non-technical stakeholder?
Describe a design disagreement and how it was settled.

What motivates you to perform well in your role?

Medium · Behavioral / Leadership

Approach

Give a specific, honest motivation and back it with evidence from your past work, such as the kind of problem you sought out or stayed late to solve.
Connect it to the reported nature of this work (satellite systems, secure communications, government software) without flattering the company.
Mention a concrete source of drive, such as owning a system end to end or seeing it run reliably in use.
Avoid generic answers such as 'I love challenges'; they say nothing that distinguishes you.

Follow-up

What demotivates you, and how do you handle it?
Tell me about a time your motivation dipped. What did you do?
Why this role over a commercial software role?