The　adjoint　code　generator　(ADG)　is　developed　to　produce　the　adjoint　codes,　which　are　used　to　analytically　calculate　gradients　and　the　Hessian-vector　products　with　the　costs　independent　of　the　number　of　the　independent　variables.　Different　from　other　automatic　differentiation　tools,　the　implementation　of　ADG　has　advantages　of　using　the　least　program　behavior　decomposition　method　and　several　static　dependence　analysis　techniques.　In　this　paper　we　first　address　the　concerned　concepts　and　fundamentals,　and　then　introduce　the　functionality　and　the　features　of　ADG.　In　particular,　we　also　discuss　the　design　architecture　of　ADG　and　implementation　details　including　the　recomputation　and　storing　strategy　and　several　techniques　for　code　optimization.　Some　experimental　results　in　several　applications　are　presented　at　the　end.