diff --git a/benches/encoder.rs b/benches/encoder.rs
index b90b2a4..278244b 100644
--- a/benches/encoder.rs
+++ b/benches/encoder.rs
@@ -1,5 +1,7 @@
 use criterion::{black_box, criterion_group, criterion_main, Criterion};
-use dynamic_data_experiments::{byte_data::{Params,Data}, encoder::{RSEncoder, BLSEncoder}};
+use dynamic_data_experiments::{byte_data::{Params,Data}, encoder::{G8Encoder, BLSEncoder}};
+use dynamic_data_experiments::encoder::BLSFieldEncoder;
+use dynamic_data_experiments::field_matrix::Matrix;
 use dynamic_data_experiments::traits::{DataMatrix, Encoder};
 
 fn bench_rs_encode(c: &mut Criterion) {
@@ -13,11 +15,11 @@ fn bench_rs_encode(c: &mut Criterion) {
     // generate a random data matrix once
     let data = Data::new_random(params.clone());
 
-    c.bench_function("RSEncoder::encode", |b| {
+    c.bench_function("G8Encoder::encode", |b| {
         b.iter(|| {
             // clone data for each iteration to avoid mutating the original
             let mut d = black_box(data.clone());
-            RSEncoder::encode(&mut d).expect("encode failed");
+            G8Encoder::encode(&mut d).expect("encode failed");
         });
     });
 }
@@ -41,5 +43,24 @@ fn bench_bls_encode(c: &mut Criterion) {
     });
 }
 
-criterion_group!(benches, bench_rs_encode, bench_bls_encode);
+fn bench_bls_field_encode(c: &mut Criterion) {
+    // test parameters
+    let k = 100;
+    let p = 100;
+    let n = k + p;
+    let m = 200;
+    let params = Params { k, n, m };
+
+    // generate a random data matrix once
+    let data = Matrix::new_random(params.clone());
+
+    c.bench_function("BLSFieldEncoder::encode", |b| {
+        b.iter(|| {
+            let mut d = black_box(data.clone());
+            BLSFieldEncoder::encode(&mut d).expect("encode failed");
+        });
+    });
+}
+
+criterion_group!(benches, bench_rs_encode, bench_bls_encode, bench_bls_field_encode);
 criterion_main!(benches);
diff --git a/src/byte_data.rs b/src/byte_data.rs
index 5bd6acd..e4143bf 100644
--- a/src/byte_data.rs
+++ b/src/byte_data.rs
@@ -11,6 +11,44 @@ pub struct Params{
     pub n: usize,
     pub m: usize,
 }
+
+impl Params{
+    pub fn check_bounds(&self, r: usize, c: usize) -> anyhow::Result<()>{
+        assert!(
+            r < self.n,
+            "row index {} out of bounds; must be < {}",
+            r,
+            self.n
+        );
+        assert!(
+            c < self.m,
+            "col index {} out of bounds; must be < {}",
+            c,
+            self.m
+        );
+        Ok(())
+    }
+    pub fn check_rows(&self, r: usize) -> anyhow::Result<()>{
+        assert!(
+            r < self.n,
+            "row index {} out of bounds; must be < {}",
+            r,
+            self.n
+        );
+        Ok(())
+    }
+
+    pub fn check_cols(&self, c: usize) -> anyhow::Result<()>{
+        assert!(
+            c < self.m,
+            "col index {} out of bounds; must be < {}",
+            c,
+            self.m
+        );
+        Ok(())
+    }
+}
+
 /// data struct contains shards matrix with dimensions `n`*`m`
 /// the matrix contains n rows, k of which are source data and the rest p = (n-k) are parity
 #[derive(Clone, Debug)]
@@ -20,21 +58,11 @@ pub struct Data<T>{
 }
 
 impl<T> Data<T>{
-    pub fn get_row(&self, idx: usize) -> &Vec<T>{
-        &self.matrix[idx]
-    }
 
     pub fn get_row_mut(&mut self, idx: usize) -> &mut Vec<T>{
         &mut self.matrix[idx]
     }
 
-    pub fn get_col(&self, idx: usize) -> Vec<&T> {
-        self.matrix
-            .iter()
-            .map(|row| &row[idx])
-            .collect()
-    }
-
     pub fn get_col_mut(&mut self, idx: usize) -> Vec<&mut T> {
         self.matrix
             .iter_mut()
@@ -67,9 +95,35 @@ impl DataMatrix<u8> for Data<u8> {
         }
     }
 
+    fn get(&self, r: usize, c: usize) -> anyhow::Result<u8> {
+        self.params.check_bounds(r,c)?;
+        Ok(self.matrix[r][c].clone())
+    }
+
+    fn get_row(&self, r: usize) -> anyhow::Result<Vec<u8>> {
+        self.params.check_rows(r)?;
+
+        Ok(self.matrix[r].to_vec())
+    }
+
+    fn get_col(&self, c: usize) -> anyhow::Result<Vec<u8>> {
+        self.params.check_cols(c)?;
+
+        Ok(self.matrix
+            .iter()
+            .map(|row| row[c].clone())
+            .collect())
+    }
+
+    fn set(&mut self, r: usize, c: usize, elem: u8) -> anyhow::Result<()> {
+        self.params.check_bounds(r,c)?;
+        self.matrix[r][c] = elem;
+        Ok(())
+    }
+
     /// Update col `c` in shards.
     /// given `new_col` will replace the column `c` or `shards[0..k][c]`
-    fn update_col(&mut self, c: usize, new_col: &[u8]) {
+    fn update_col(&mut self, c: usize, new_col: &[u8]) -> anyhow::Result<()>{
         // sanity checks
         assert!(
             new_col.len() == self.params.k,
@@ -77,17 +131,13 @@ impl DataMatrix<u8> for Data<u8> {
             new_col.len(),
             self.params.k
         );
-        assert!(
-            c < self.params.m,
-            "col index {} out of bounds; must be < {}",
-            c,
-            self.params.m
-        );
+        self.params.check_cols(c)?;
 
         // write into each of the k data row at position c
         for i in 0..self.params.k {
             self.matrix[i][c] = new_col[i];
         }
+        Ok(())
     }
 
     /// Print all shards
diff --git a/src/encoder.rs b/src/encoder.rs
index 36dc838..b3b9a99 100644
--- a/src/encoder.rs
+++ b/src/encoder.rs
@@ -7,16 +7,16 @@ use ark_poly::{DenseUVPolynomial, GeneralEvaluationDomain, Polynomial};
 use ark_poly::univariate::DensePolynomial;
 use reed_solomon_erasure::galois_8::ReedSolomon;
 use crate::byte_data::{Data, Params};
-use crate::traits::Encoder;
+use crate::traits::{DataMatrix, Encoder};
 use ark_poly::domain::EvaluationDomain;
 use crate::field_matrix::Matrix;
 // ------------- RS Encoder ------------
 
-pub struct RSEncoder<T>{
+pub struct G8Encoder<T>{
     phantom_data: PhantomData<T>
 }
 
-impl RSEncoder<u8>{
+impl G8Encoder<u8>{
     pub fn new() -> Self{
         Self{
             phantom_data: PhantomData::default()
@@ -24,7 +24,7 @@ impl RSEncoder<u8>{
     }
 }
 
-impl Encoder<u8> for RSEncoder<u8> {
+impl Encoder<u8> for G8Encoder<u8> {
     type Params = Params;
     type DataMatrix<T> = Data<u8>;
 
@@ -53,7 +53,7 @@ impl Encoder<u8> for RSEncoder<u8> {
         Ok(())
     }
 
-    fn encode_col(data: &mut Data<u8>, c: usize) -> Result<Vec<u8>>{
+    fn encode_col(data: &mut Data<u8>, c: usize) -> Result<()>{
         // bounds check
         if c >= data.params.m {
             return Err(anyhow!("col index {} out of bounds (< {})", c, data.params.m));
@@ -66,7 +66,7 @@ impl Encoder<u8> for RSEncoder<u8> {
         // Build the column: data = existing byte, parity = zero
         let mut temp: Vec<Vec<u8>> = (0..n)
             .map(|i| {
-                let byte = data.matrix[i][c];
+                let byte = data.get(i,c).unwrap();
                 if i < k {
                     vec![byte]
                 } else {
@@ -80,17 +80,15 @@ impl Encoder<u8> for RSEncoder<u8> {
         let rse = ReedSolomon::new(k, p)?;
         rse.encode(&mut refs)?;
 
-        // Write back parity and collect full col
-        let mut full_col = Vec::with_capacity(n);
+        // Write back parity
         for i in 0..n {
             let b = refs[i][0];
             if i >= k {
-                data.matrix[i][c] = b;
+                data.set(i,c, b)?;
             }
-            full_col.push(b);
         }
 
-        Ok(full_col)
+        Ok(())
     }
 
     fn reconstruct(params: Params, matrix_opts: &mut Vec<Option<Vec<u8>>>) -> Result<()>{
@@ -133,7 +131,7 @@ impl Encoder<u8> for BLSEncoder<u8> {
         Ok(())
     }
 
-    fn encode_col(data: &mut Self::DataMatrix<u8>, c: usize) -> Result<Vec<u8>> {
+    fn encode_col(data: &mut Self::DataMatrix<u8>, c: usize) -> Result<()> {
         let n = data.params.n.clone();
         let k = data.params.k.clone();
         let mut col = data.get_col_mut(c);
@@ -141,14 +139,13 @@ impl Encoder<u8> for BLSEncoder<u8> {
         let poly_poly = UniPoly381::from_coefficients_slice(&col_f);
         let domain: GeneralEvaluationDomain<F> = EvaluationDomain::<F>::new(n).unwrap();
 
-        let mut new_col: Vec<u8> = vec![];
+        // let mut new_col: Vec<u8> = vec![];
         for i in k..n{
             let eval = poly_poly.evaluate(&domain.element(i));
-            new_col.push(eval.0.0[0] as u8);
             *col[i] = eval.0.0[0] as u8;
         }
 
-        Ok(new_col)
+        Ok(())
     }
 
     fn reconstruct(_params: Params, _matrix_opts: &mut Vec<Option<Vec<u8>>>) -> Result<()> {
@@ -158,7 +155,11 @@ impl Encoder<u8> for BLSEncoder<u8> {
 
 // --------- BLS Encoder over FieldMatrix ----------------
 
-impl Encoder<F> for BLSEncoder<F> {
+pub struct BLSFieldEncoder<T>{
+    phantom_data: PhantomData<T>
+}
+
+impl Encoder<F> for BLSFieldEncoder<F>{
     type Params = Params;
     type DataMatrix<T> = Matrix<F>;
 
@@ -169,23 +170,18 @@ impl Encoder<F> for BLSEncoder<F> {
         Ok(())
     }
 
-    fn encode_col(data: &mut Matrix<F>, c: usize) -> Result<Vec<F>> {
-        // let n = data.params.n.clone();
-        // let k = data.params.k.clone();
-        // let mut col = data.get_col_mut(c);
-        // let col_f: Vec<F> = col.iter().map(|i| <F as PrimeField>::from_le_bytes_mod_order(&i.clone().to_le_bytes())).collect();
-        // let poly_poly = UniPoly381::from_coefficients_slice(&col_f);
-        // let domain: GeneralEvaluationDomain<F> = EvaluationDomain::<F>::new(n).unwrap();
-        //
-        // let mut new_col: Vec<u8> = vec![];
-        // for i in k..n{
-        //     let eval = poly_poly.evaluate(&domain.element(i));
-        //     new_col.push(eval.0.0[0] as u8);
-        //     *col[i] = eval.0.0[0] as u8;
-        // }
-        //
-        // Ok(new_col)
-        todo!()
+    fn encode_col(data: &mut Matrix<F>, c: usize) -> Result<()> {
+        let n = data.params.n.clone();
+        let k = data.params.k.clone();
+        let col: Vec<F> = data.get_col(c)?;
+        let poly = UniPoly381::from_coefficients_slice(&col);
+        let domain: GeneralEvaluationDomain<F> = EvaluationDomain::<F>::new(n).unwrap();
+
+        for i in k..n{
+                let eval = poly.evaluate(&domain.element(i));
+                data.set(i,c,eval)?;
+        }
+        Ok(())
     }
 
     fn reconstruct(_params: Params, _matrix_opts: &mut Vec<Option<Vec<F>>>) -> Result<()> {
diff --git a/src/field_matrix.rs b/src/field_matrix.rs
index 5cb0d45..bf5e7c2 100644
--- a/src/field_matrix.rs
+++ b/src/field_matrix.rs
@@ -1,7 +1,7 @@
 use ark_ff::Field;
-use ark_std::rand::Rng;
-use ark_std::UniformRand;
+use ark_std::{test_rng};
 use crate::byte_data::{Data, Params};
+use crate::traits::DataMatrix;
 
 
 /// a Field matrix with `row` number of rows and `cols` number of columns
@@ -12,34 +12,8 @@ pub struct Matrix<F: Field + Clone> {
 }
 
 impl<F: Field + Clone> Matrix<F> {
-    /// Creates a new matrix from given field data.
-    pub fn new(params: Params, elms: Vec<Vec<F>>) -> Self {
-        assert!(elms.len() == params.n,      "number of rows must match");
-        for row in &elms {
-            assert!(row.len() == params.m,   "each row must have `m` elements");
-        }
-        Matrix { params, elms }
-    }
 
-    /// Generates a random matrix with given dimensions, uses given rng for randomness.
-    pub fn new_random<R: Rng + ?Sized>(params: Params, rng: &mut R) -> Self
-        where
-            F: UniformRand,
-    {
-        let rows = params.n;
-        let cols = params.m;
-        let mut data = Vec::with_capacity(rows);
-        for _ in 0..rows {
-            let mut row = Vec::with_capacity(cols);
-            for _ in 0..cols {
-                row.push(F::rand(rng));
-            }
-            data.push(row);
-        }
-        Matrix { params, elms: data }
-    }
-
-    /// Creates a new matrix from given data struct
+    /// Creates a new matrix from given u8 data struct
     pub fn from_data(data: &Data<u8>) -> Self{
         let rows = data.params.n;
         let cols = data.params.m;
@@ -55,23 +29,10 @@ impl<F: Field + Clone> Matrix<F> {
         Matrix { params: data.params.clone(), elms:field_data }
     }
 
-    /// get the row at 0<idx<n
-    pub fn row(&self, idx: usize) -> Vec<F>{
-        assert!(idx < self.params.n, "Row index out of bounds");
-        self.elms[idx].to_vec()
-    }
-
     /// get mut the row at 0<idx<n
-    pub fn row_mut(&mut self, idx: usize) -> &mut Vec<F>{
-        assert!(idx < self.params.n, "Row index out of bounds");
-        &mut self.elms[idx]
-    }
-
-    pub fn get_col(&self, idx: usize) -> Vec<&F> {
-        self.elms
-            .iter()
-            .map(|row| &row[idx])
-            .collect()
+    pub fn get_row_mut(&mut self, idx: usize) -> anyhow::Result<&mut Vec<F>>{
+        self.params.check_rows(idx)?;
+        Ok(&mut self.elms[idx])
     }
 
     pub fn get_col_mut(&mut self, idx: usize) -> Vec<&mut F> {
@@ -80,9 +41,54 @@ impl<F: Field + Clone> Matrix<F> {
             .map(|row| &mut row[idx])
             .collect()
     }
+}
+
+impl<F: Field + Clone> DataMatrix<F> for Matrix<F> {
+    type Params = Params;
+
+    /// Generates a random matrix with given dimensions, uses given rng for randomness.
+    fn new_random(params: Params) -> Self
+    {
+        let mut rng = test_rng();
+        let rows = params.n;
+        let cols = params.m;
+        let mut data = Vec::with_capacity(rows);
+        for _ in 0..rows {
+            let mut row = Vec::with_capacity(cols);
+            for _ in 0..cols {
+                row.push(F::rand(&mut rng));
+            }
+            data.push(row);
+        }
+        Matrix { params, elms: data }
+    }
+
+    fn get(&self, r: usize, c: usize) -> anyhow::Result<F> {
+        self.params.check_bounds(r,c)?;
+        Ok(self.elms[r][c].clone())
+    }
+
+    fn set(&mut self, r: usize, c: usize, elem: F) -> anyhow::Result<()>{
+        self.params.check_bounds(r,c)?;
+        Ok(self.elms[r][c] = elem)
+    }
+
+    /// get the row at 0<idx<n
+    fn get_row(&self, idx: usize) -> anyhow::Result<Vec<F>>{
+        self.params.check_rows(idx)?;
+        Ok(self.elms[idx].to_vec())
+    }
+
+    fn get_col(&self, idx: usize) -> anyhow::Result<Vec<F>> {
+        self.params.check_cols(idx)?;
+        Ok(self.elms
+            .iter()
+            .map(|row| row[idx].clone())
+            .collect())
+    }
 
     /// Print matrix
-    pub fn pretty_print(&self) {
+    fn pretty_print(&self) {
         for (i, shard) in self.elms.iter().enumerate() {
             print!("row {:>2}: ", i);
             for &b in shard {
@@ -91,6 +97,24 @@ impl<F: Field + Clone> Matrix<F> {
             println!();
         }
     }
+
+    fn update_col(&mut self, c: usize, new_col: &[F]) -> anyhow::Result<()> {
+        self.params.check_cols(c)?;
+
+        // ensure the provided column has exactly `k` entries
+        assert!(
+            new_col.len() == self.params.k,
+            "new_col length ({}) must equal k ({})",
+            new_col.len(),
+            self.params.k
+        );
+
+        for (r, val) in new_col.iter().enumerate() {
+            self.elms[r][c] = val.clone();
+        }
+
+        Ok(())
+    }
 }
 
 
diff --git a/src/kzg.rs b/src/kzg.rs
index 3d43fa1..9b94c1d 100644
--- a/src/kzg.rs
+++ b/src/kzg.rs
@@ -18,7 +18,7 @@ use ark_poly_commit::marlin_pc::MarlinKZG10;
 use ark_poly_commit::sonic_pc::UniversalParams;
 use crate::byte_data::Params;
 use crate::field_matrix::Matrix;
-use crate::traits::PolynomialCommitmentScheme;
+use crate::traits::{PolynomialCommitmentScheme, DataMatrix};
 use ark_crypto_primitives::sponge::poseidon::{PoseidonSponge, PoseidonConfig};
 use ark_poly_commit::kzg10::Proof;
 
@@ -67,7 +67,8 @@ impl PolynomialCommitmentScheme for KZGPolyComm {
         let mut row_polynomials = vec![];
         let timer = start_timer!(|| format!("Poly evaluations and interpolation for {} rows", degree));
         for i in 0..matrix.params.n{
-            let poly_evals = Evaluations::from_vec_and_domain(matrix.row(i), srs.ploycommit_domain.clone());
+            let row = matrix.get_row(i)?.to_vec();
+            let poly_evals = Evaluations::from_vec_and_domain(row, srs.ploycommit_domain.clone());
             let row_poly = poly_evals.interpolate();
             let label = String::from(format!("row_poly_{}", i));
             let labeled_poly = LabeledPolynomial::new(
diff --git a/src/test.rs b/src/test.rs
index d130d30..1b8989e 100644
--- a/src/test.rs
+++ b/src/test.rs
@@ -5,7 +5,7 @@ mod tests {
     use crate::kzg::{F, KZGPolyComm};
     use crate::field_matrix::Matrix;
     use ark_poly_commit::{Polynomial};
-    use crate::encoder::{BLSEncoder, RSEncoder};
+    use crate::encoder::{BLSEncoder, BLSFieldEncoder, G8Encoder};
     use crate::traits::{DataMatrix, Encoder, PolynomialCommitmentScheme};
 
     #[test]
@@ -31,7 +31,7 @@ mod tests {
         let original: Vec<Vec<u8>> = data.matrix[..k].to_vec();
 
         // encode
-        RSEncoder::encode(&mut data).expect("encode failed");
+        G8Encoder::encode(&mut data).expect("encode failed");
         println!("data after encoding:");
         data.pretty_print();
 
@@ -44,7 +44,7 @@ mod tests {
         matrix_opts[k] = None;
 
         // reconstruct missing rows
-        RSEncoder::reconstruct(data.params.clone(), &mut matrix_opts).expect("reconstruction should succeed");
+        G8Encoder::reconstruct(data.params.clone(), &mut matrix_opts).expect("reconstruction should succeed");
 
         // verify reconstruction for data shards
         for i in 0..k {
@@ -54,7 +54,7 @@ mod tests {
     }
 
     #[test]
-    fn test_bls_encodeer() {
+    fn test_bls_encoder() {
         // test parameters
         let k = 4;
         let p = 4;
@@ -98,6 +98,54 @@ mod tests {
         // }
     }
 
+    #[test]
+    fn test_bls_field_encoder() {
+        // test parameters
+        let k = 4;
+        let p = 4;
+        let n = k + p;
+        let m = 8;
+
+        // generate Data with random content
+        let params = Params {
+            k,
+            n,
+            m,
+        };
+        let data = Data::new_random(params);
+        println!("data #row ={}", data.matrix.len());
+        println!("data #col ={}", data.matrix[0].len());
+        println!("data before encoding:");
+        data.pretty_print();
+        // original data matrix
+        let mut original = Matrix::from_data(&data);
+        let original_copy = Matrix::from_data(&data);
+        println!("data as Field elements:");
+        original.pretty_print();
+
+        // encode
+        BLSFieldEncoder::encode(&mut original).expect("encode failed");
+        println!("data after encoding:");
+        original.pretty_print();
+
+        // verify data matrix unchanged
+        assert_eq!(original.elms[..k], original_copy.elms[..k]);
+
+        // simulate loss of one data and one parity rows
+        let mut matrix_opts: Vec<_> = data.matrix.iter().cloned().map(Some).collect();
+        matrix_opts[1] = None;
+        matrix_opts[k] = None;
+
+        // TODO: reconstruct missing rows
+        // BLSEncoder::reconstruct(data.params.clone(), &mut matrix_opts).expect("reconstruction should succeed");
+
+        // verify reconstruction for data shards
+        // for i in 0..k {
+        //     let recovered = matrix_opts[i].clone().unwrap();
+        //     assert_eq!(recovered, &original[i][..]);
+        // }
+    }
+
     #[test]
     fn test_commit_rows() {
         // dimensions: 8 rows (4 parity), 8 columns
@@ -112,7 +160,7 @@ mod tests {
             m,
         };
         let mut data = Data::new_random(params.clone());
-        RSEncoder::encode(&mut data).expect("encode failed");
+        G8Encoder::encode(&mut data).expect("encode failed");
 
         // make a random n×m matrix
         let matrix = Matrix::from_data(&data);
@@ -136,7 +184,7 @@ mod tests {
 
         // check that each polynomial really interpolates its original rows
         for (i, poly) in row_polys.iter().enumerate() {
-            let row = matrix.row(i);
+            let row = matrix.get_row(i).unwrap();
             // evaluate poly at each domain point and collect
             let evals: Vec<_> = srs
                 .ploycommit_domain
@@ -161,7 +209,7 @@ mod tests {
             m,
         };
         let mut data = Data::new_random(params.clone());
-        RSEncoder::encode(&mut data).expect("encode failed");
+        G8Encoder::encode(&mut data).expect("encode failed");
 
         // make a random n×m matrix
         let matrix = Matrix::from_data(&data);
@@ -178,7 +226,7 @@ mod tests {
             for col in 0..m {
                 let proof = KZGPolyComm::open(&kzg_comm, &srs, row, col)
                     .expect("open should succeed");
-                let expected: F = matrix.row(row)[col].clone();
+                let expected: F = matrix.elms[row][col].clone();
 
                 assert!(
                     KZGPolyComm::verify(&kzg_comm, &srs, row, col, expected, &proof)
@@ -206,7 +254,7 @@ mod tests {
         };
         // snapshot of original
         let mut data = Data::new_random(params);
-        RSEncoder::encode(&mut data).expect("encode failed");
+        G8Encoder::encode(&mut data).expect("encode failed");
         println!("original data:");
         data.pretty_print();
 
@@ -230,7 +278,7 @@ mod tests {
             );
         }
 
-        let _coded_row = RSEncoder::encode_col(&mut data, c).unwrap();
+        let _coded_row = G8Encoder::encode_col(&mut data, c).unwrap();
         println!("data after encoding update:");
         data.pretty_print();
     }
@@ -250,7 +298,7 @@ mod tests {
         };
         // snapshot of original
         let mut data = Data::new_random(params.clone());
-        RSEncoder::encode(&mut data).expect("encode failed");
+        G8Encoder::encode(&mut data).expect("encode failed");
 
         // Build a matrix where entry (i,j) = i * m + j
         let mut matrix = Matrix::<F>::from_data(&data);
@@ -266,7 +314,7 @@ mod tests {
 
         // a row to update
         let row_idx = 1;
-        let old_row = matrix.row(row_idx);
+        let old_row = matrix.get_row(row_idx)?;
 
         // a new row by adding a constant to each element
         let new_row: Vec<_> = old_row.iter()
@@ -275,7 +323,7 @@ mod tests {
 
         // Apply the change to the in-memory matrix
         {
-            let row_slice = matrix.row_mut(row_idx);
+            let row_slice = matrix.get_row_mut(row_idx)?;
             for (j, val) in new_row.iter().enumerate() {
                 row_slice[j] = *val;
             }
@@ -291,7 +339,7 @@ mod tests {
                 .elements()
                 .map(|x| poly.polynomial().evaluate(&x))
                 .collect();
-            assert_eq!(evals, matrix.row(i));
+            assert_eq!(evals, matrix.get_row(i)?);
         }
 
         // === new fresh commit on updated matrix ===
diff --git a/src/traits.rs b/src/traits.rs
index 9e8e8cc..3c3bea2 100644
--- a/src/traits.rs
+++ b/src/traits.rs
@@ -4,7 +4,11 @@ use crate::byte_data::Params;
 pub trait DataMatrix<T>{
     type Params;
     fn new_random(params: Self::Params) -> Self;
-    fn update_col(&mut self, c: usize, new_col: &[T]);
+    fn get(&self, r: usize, c: usize) -> Result<T>;
+    fn get_row(&self, r: usize) -> Result<Vec<T>>;
+    fn get_col(&self, c: usize) -> Result<Vec<T>>;
+    fn set(&mut self, r: usize, c: usize, elem: T) -> Result<()>;
+    fn update_col(&mut self, c: usize, new_col: &[T]) -> Result<()>;
     fn pretty_print(&self);
 }
 
@@ -17,7 +21,7 @@ pub trait Encoder<T>{
     /// encode in place the input data matrix
     fn encode(data: &mut Self::DataMatrix<T>) -> Result<()>;
     /// encode a single column in place
-    fn encode_col(data: &mut Self::DataMatrix<T>, c: usize) -> Result<Vec<T>>;
+    fn encode_col(data: &mut Self::DataMatrix<T>, c: usize) -> Result<()>;
     /// reconstruct in place
     fn reconstruct(params: Params, matrix_opts: &mut Vec<Option<Vec<T>>>) -> Result<()>;
 }