[Algorithms] Solve Complex Problems in JavaScript with Dynamic Programming

Every dynamic programming algorithm starts with a grid. It entails solving subproblems and builds up to solving the big problem. Let’s break down a problem and solve it in pieces using dynamic programming with JavaScript.

/**
 * 给一个浮点数序列，取最大乘积连续子串的值，例如 -2.5，4，0，3，0.5，8，-1，则取出的最大乘积连续子串为3，0.5，8。也就是说，上述数组中，3 0.5 8这3个数的乘积30.58=12是最大的，而且是连续的
 * @param {*} a 
 */
function MaxProductSubstring (a) {
    let maxEnd = a[0]
    let maxRes = a[0]

    for (let i = 1; i < a.length; i++) {
        maxEnd = Math.max(maxEnd * a[i], a[i])
        maxRes = Math.max(maxRes, maxEnd)
    }

    return maxRes
}