Production Engineering

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Write code to parse regular expressions including * (0 or more characters), + (1 or more characters), and . (1 exact character). For example: parse(a., ab) should return true. parse(a*, aaa) should return true. parse(a+, a) should return true. parse(a+, ) should return false. parse(a.*b, axyzb) should return true. parse(a.*b, axyz) should return false. parse(abc, abc) should return true. parse(abc, abd) should return false. Your function should take two strings as input: the regular expression and the string to match against. It should return a boolean indicating whether the string matches the regular expression. Focus on handling the special characters ., *, and +. Assume that other characters in the regular expression must match literally. Explain your approach and provide a clear, well-documented code implementation. Consider edge cases such as empty strings and null inputs. Also think about the time and space complexity of your solution, and try to optimize it for performance. Can you provide a solution using dynamic programming?

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Design a System for Real-Time Twitter Trending Topics Let's design a system to identify trending topics on Twitter in real-time. Consider the following: Data Ingestion: How would you ingest the massive stream of tweets from Twitter? Processing: How would you process the tweets to extract relevant information (e.g., hashtags, keywords)? Trending Detection: How would you identify trending topics based on the processed data? What algorithms or techniques would you use? Scalability: How would you design the system to handle a large volume of tweets and users? Storage: What storage solutions would you use to store the tweets and trending topics? Consider both short-term and long-term storage. Network Requirements: Estimate the network bandwidth required for data ingestion and processing. Performance Optimization: How would you optimize the system for low latency and high throughput? For example, assume that Twitter generates 500 million tweets per day. Design a system that can identify trending topics within a few minutes, considering the computational resources, storage, and network bandwidth needed.

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