Error-control codes, which are being extensively used in communication systems, have found themselves very useful in data storage as well during the past decade. This thesis deals with two types of codes for data storage, one pertaining to the issue of privacy and the other to reliability. In many scenarios, user accessing some critical data from a server would not want the server to learn the identity of data retrieved. This problem, called Private Information Retrieval (PIR) was rst formally introduced by Chor et al and they gave protocols for PIR in the case where multiple copies of the same data is stored in non-communicating servers. The PIR protocols that came up later also followed this replication model. The problem with data replication is the high storage overhead involved, which will lead to large storage costs. Later, Fazeli, Vardy and Yaakobi, came up with the notion of PIR code that enables information-theoretic PIR with low storage overhead. In the rst part of this thesis, construction of PIR codes for certain parameter values is presented. These constructions are based on a variant of conventional Reed-Muller (RM) codes called binary Projective Reed-Muller (PRM) codes. A lower bound on block length of systematic PIR codes is derived and the PRM based PIR codes are shown to be optimal with respect to this bound in some special cases. The codes constructed here have smaller block lengths than the short block length PIR codes known in the literature. The generalized Hamming weights of binary PRM codes are also studied. Another work described here is the implementation and evaluation of an erasure code called Coupled Layer (CL) code in Ceph distributed storage system. Erasure codes are used in distributed storage to ensure reliability. An additional desirable feature required for codes used in this setting is the ability to handle node repair efficiently. The Minimum Storage Regenerating (MSR) version of CL code downloads optimal amount of data from other nodes during repair of a failed node and even disk reads during this process is optimum, for that storage overhead. The CL-Near-MSR code, which is a variant of CL-MSR, can efficiently handle a restricted set of multiple node failures also. Four example CL codes were evaluated using a 26 node Amazon cluster and performance metrics like network bandwidth, disk read and repair time were measured. Repair time reduction of the order of 3 was observed for one of those codes, in comparison with Reed Solomon code having same parameters. To the best of our knowledge, such large gains in repair performance have never been demonstrated before.