To install, download the files in vtsttools/vtstcode, choose a version, and copy the files in the directory into your vasp source directory. The file chain.F is replaced, so back up the old version. There are other files in the package: neb.F, dynmat.F, dimer.F, lanczos.F, sd.F, cg.F, qm.F, lbfgs.F, bfgs.F, fire.F, and opt.F in and vtstcode6.4/ directories. The vtstcode6.4/ directory contains another file called ml_pyamff.F and directory named pyamff_fortran/, which interface to a machine learning package PyAMFF.
In my situation, I put it in /usr/local/vasp-6.4.2-vtst/vasp.6.4.2/src
$ cd /usr/local/vasp-6.4.2-vtst/vasp.6.4.2/src
$ tar -zxvf vtstcode-198.tgz
$ cd vtstcode-198/vtstcode6.4
$ cp -Rv * /usr/local/vasp-6.4.2-vtst/vasp.6.4.2/src
Step 3: Find the variable SOURCE in the .objects file (a hidden file in src/)
Find the variable SOURCE in the .objects file (a hidden file in src/), which defines which objects will be built, and add the following objects before chain.o:
$ cd /usr/local/vasp-6.4.2-vtst/vasp.6.4.2/src
$ ls -al .objects
$ vim .objects
Around line 126, before chain.o, insert the following