Two important trends in computer systems are that applications are moved to the Internet as web applications, and that computer systems are getting an increasing number of cores to increase the performance. It has been shown that JavaScript in web applications has a large potential for parallel execution despite the fact that JavaScript is a sequential language. In this thesis, we show that JavaScript execution in web applications and in benchmarks are fundamentally different and that an effect of this is that Just-in-time compilation does often not improve the execution time, but rather increases the execution time for JavaScript in web applications. Since there is a significant potential for parallel computation in JavaScript for web applications, we show that Thread-Level Speculation can be used to take advantage of this in a manner completely transparent to the programmer. The Thread-Level Speculation technique is very suitable for improving the performance of JavaScript execution in web applications; however we observe that the memory overhead can be substantial. Therefore, we propose several techniques for adaptive speculation as well as for memory reduction. In the last part of this thesis we show that Just-in-time compilation and Thread-Level Speculation are complementary techniques. The execution characteristics of JavaScript in web applications are very suitable for combining Just-in-time compilation and Thread-Level Speculation. Finally, we show that Thread-Level Speculation and Just-in-time compilation can be combined to reduce power usage on embedded devices.